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International Journal of Industrial Engineering, 19(1), 1-13, 2012.

INTERNET USER RESEARCH IN PRODUCT DEVELOPMENT: RAPID AND LOW COST DATA COLLECTION A.Shekar and J.McIntyre School of Engineering and Advanced Technology Massey University, Auckland New Zealand Small to Medium Enterprises (SMEs) face enormous financial risks when developing new products. A key element of risk minimization is an early emphasis on gathering information about the end users of the product quickly. SMEs are often overwhelmed by the prospect of expected research costs, lack of expertise, and financial pressures to rush to market. Too often the more conventional path is chosen, whereby a solution is, developed and tested in the market to “see if it sticks”. Such methodologies are less effective and subject the SME to increased financial risk. This study demonstrates how SMEs can make use of freely available internet resources to reproduce aspects of more sophisticated customer research techniques. Internet resources such as the YouTube and Forums enable SMEs to research customers rapidly, and in a cost effective manner. This study examines New Zealand SMEs and presents two case studies to support the use of modern web-based user research in new product development. Keywords: product development, user information, web research, New Zealand (Received 27 October 2010; Accepted in revised form 24 June 2011)

1. INTRODUCTION Small and Medium Enterprises (SMEs) are a large and vital component of most developed nation’s economies. The prevalence of such firms is so large that in sectors such as manufacturing, their numbers often dominate the economic landscape (Larsen and Lewis 2007). Their accrued success contributes substantially to employment, exports, and Gross Domestic Product (GDP). The sheer quantity of firms and their individual contributions build flexibility and robustness into a nation’s economy. Governments generally recognize this fact (Massey 2002) and support innovation in SMEs through funding research and incentive programs. The ability to launch new products and services is a critical element of success for all companies, large and small. Launching a new product or service is often the most significant financial risk a firm may face since its own inception. New product launches are typically characterized by large expenditures associated with research, production tooling, marketing and promotions. The successful recovery of expenditures and the prospect of generating profits depend entirely upon the product’s success in the consumer marketplace. The losses incurred from a failed product can be devastating for the small organisation. In one study of SMEs based in the Netherlands, 40% of firms were found not to survive their first 5 years in business (Vos, Keizer et al. 1998). Surveys of NZ SMEs indicate that the risks are well understood; however, NPD is still identified as a weakness within their organisation (McGregor and Gomes 1999). 1.1 SME Challenges and New Product Development Innovation poses inherent risks, yet remains an essential activity of businesses both large and small (Boag and Rinholm 1989). While SMEs are typically described as being more entrepreneurial “risk-takers” than their larger counterparts, in reality their situation may be more precarious. Small businesses are often more sensitive to the risks of new product development (NPD) activities due to limited financial resources. Indeed, an unsuccessful product introduction can spell disaster for the small business. While structured approaches have been successfully implemented in larger firms, smaller organisations are found to be less enthusiastic about incorporating them and struggle to adopt and make use of them (Enright 2001). The reasons for this are varied and not well understood. Many SMEs operate without the benefit of academic partnerships and may simply not be aware of the information available. Others may recognize that structured NPD approaches generally cater to the specific needs of larger firms and the results may impose unnecessary bureaucracy on the smaller organisations. It is generally recognized that smaller firms are distinct in both principle and practice from their larger counterparts. Successful large firms deal efficiently with multiple project ideas, communications involving large numbers of participants, and documentation to retain and share corporate knowledge. Smaller firms participating in the NPD process face different challenges. SMEs typically address smaller numbers of projects, involving fewer participants, and enjoy opportunities for more frequent face to face communications. Challenges to successful NPD efforts are the results of operating constraints and the culture found within smaller organisations. A partial summary of the unique issues faced by SMEs is presented in Table 1. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(1), 14-25, 2012.

AN INVESTIGATION OF INTERNAL LOGISTICS OF A LEAN BUS ASSEMBLY SYSTEM VIA SIMULATION: A CASE STUDY Aric Johnson11, Patrick Balve2, and Nagen Nagarur1 1

Department of Systems Science and Industrial Engineering Binghamton University P.O. Box 6000 Binghamton, NY. 13902-6000, USA 2 Production und Logistics Department Heilbronn University 39 Max-Planck-Straße, Heilbronn 74081, Germany

Corresponding author’s email: {Aric Johnson, [email protected]} This study involves the internal logistics of a chosen bus assembly plant that follows a lean assembly process dictated by takt time production. The assembly system works according to a rigid sequential order of assembly of different models of buses, called the String of Pearls. The logistics department is responsible for supplying kitted components to assembly workstations for the right model at the right time. A simulation model was developed to study this assembly system, with an objective of finding the minimum number of kit carts for multiple production rates and kitting methods. The implementation of JIT kitting was the ultimate goal in this case. The research focused on a specific assembly plant and therefore, the numerical results are applicable to the selected plant only. However, some of the trends in the output may be generalized to any assembly plant of similar type. Significance: This study illustrates the use of simulation to plan further lean transformation within a major bus assembly plant. This assembly plant had recently transformed their assembly operations according to lean principles with much success. The next step was to transform the logistical support to this system, and this was planned via simulation. This paper makes an original contribution to this area of research, and to the best of the authors’ knowledge such a work has not been published so far. Keywords: Bus assembly, kitting, takt time, simulation, internal logistics, JIT (Received 21 March 2011; Accepted in revised form 12 March 2012)

1. INTRODUCTION Automotive industries, including bus assemblies, have been forced to cut costs to remain competitive in a global environment. For customers, price is often an important criterion, and so automotive plants strive to cut costs, while at the same time struggle to improve their throughput. The industry has mostly adopted lean manufacturing methods as the means of reducing costs and increasing throughput. Auto plants typically follow an assembly-line type of manufacturing, in which all the operations are done in stations or cells connected sequentially with a set of operations assigned for each station. This is because there are a large number of operations that need to be completed to produce a finished automobile; breaking the operations into stations allows the system to operate more efficiently and at a much faster rate. Most plants also implement a balanced assembly line of workstations that allows assemblies to flow through the system at a specific, predetermined rate, termed takt time. This balanced, sequential workstation design promotes a smooth flow throughout the plant. However, this type of system then inherits a new challenge of physically getting the required parts to the workstations on time. This problem can be described as a problem of internal logistics between parts storage (warehouse) and the many workstations. A well-coordinated logistics system is vital since a single workstation that does not receive its required parts/components on time results in delaying the entire assembly line. An assembly plant operating at a takt time production rate has little or no slack built into its schedule. Hence, getting the required parts/components to the right workstation at the right time is critical in this setting. One internal supply strategy would be to stage required parts at the workstations and replenish them as necessary. This is often not feasible in bus assembly. For one thing, the parts may be of large size and storage of such parts at a workstation may be prohibitive. In addition, if the line is producing multiple models, storing all the combinations of parts makes it more complex and tends to become more error prone. Hence, the standard practice under such situations is to let the product flow through the stations and have the parts/components for an individual assembly be brought to the appropriate workstation at the exact time they are needed. The majority of the parts/components are stored in a warehouse, and the required set of ISSN 1943-670X

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International Journal of Industrial Engineering, 19(1), 26-32, 2012.

RESEARCH-BASED ENQUIRY IN PRODUCT DEVELOPMENT EDUCATION: LESSONS FROM SUPERVISING UNDERGRADUATE FINAL YEAR PROJECTS A. Shekar School of Engineering and Advanced Technology Massey University, Auckland New Zealand (Received 27 October 2010; Accepted in revised form 24 June 2011)

This paper presents an interesting perspective on enquiry-based learning by engineering students through a project and research-based course. It discusses the lessons learned from coordinating and supervising undergraduate research-based project courses in Product Development engineering, at Massey University in New Zealand. Research is undertaken by students at the start and throughout the development project in order to understand the background and trends in the literature and incorporate them in their projects. Further research is done regarding the product’s technologies, problem and motivation behind the development, as well as a thorough knowledge of the context and user environment are undertaken. The multi-disciplinary nature of product development, requires students to research widely across disciplinary borders, and then to integrate the results for the goals of designing a new product and journal-style research papers. The Product Development process is a research-based decision-making process and one that needs an enquiring mind and an independent learning approach, as often the problems are open-ended and ill-defined. Both explicit and tacit knowledge are gained through this action-research methodology of learning. Tacit knowledge is gained through the hands-on project experience, experimentation, and learning by doing. Several implications for educators are highlighted, including the need for a greater emphasis on self-learning through research and hands-on practical experience, the importance of developing student research skills, and the value of learning from peer interaction. Keywords: Product development, research-based enquiry, project-based learning. (Received 1 May 2009; Accepted in revised form 1 June 2010)

1. INTRODUCTION Engineering design programs are increasingly aware, ‘that the project-based approach results in the development of competencies that are expected by employers’ (DeVere, 2010). One of these competencies is independent research skills and learning. Several new design-engineering programs have emerged and many see the need for engineers to demonstrate design and management (business) thinking in addressing product design problems. Most of these programs build the curriculum by combining courses from business, design and engineering faculties, leaving the integration to the students. We have found that this integration does not take place well. Often students tend to compartmentalise papers, do not appreciate the links between papers or sometimes lecturers from other departments are not aware of how engineers may use some of the material they cover, hence may not provide relevant examples. Hence project-based learning is an attempt to address this issue. A broad definition of project-based learning (PBL) given by Prince and Felder is: ‘Project-based learning begins with an assignment to carry out one or more tasks that lead to the production of a final product—a design, a model, a device or a computer simulation. The culmination of the project is normally a written and/or oral report summarizing the procedure used to produce the product and presenting the outcome.’ In practice, many engineering education activities developed on the basis of inductive instructional methods – active research, inquiry-led learning and problem-based learning focus on a fixed deliverable and therefore fall within this definition of PBL. Massey University is currently reorganizing the curriculum towards overcoming the gap between theory and practice, the lack of good integration of disciplines and taking on a more student-centred approach to learning. Students follow courses in engineering sciences, physicals, mathematics, statistics and the like; however in tackling practical design projects, they fail to apply this knowledge to the extent that their design would benefit. The new curriculum proposes to have more project-based learning and less of the traditional ‘chalk and talk’ teacher centred approach in all of the majors offered. This approach follows worldwide trends in engineering education, and has already been practiced within the current product development major with success, hence is presented in this paper.

ISSN 1943-670X

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International Journal of Industrial Engineering, 19(1), 33-46, 2012.

A HYBRID BENDERS/GENETIC ALGORITHM FOR VEHICLE ROUTING AND SCHEDULING PROBLEM Ming-Che Lai 1, Han-Suk Sohn 2, Tzu-Liang (Bill) Tseng 3, and Dennis L. Bricker 4 1

Department of Marketing and Logistics Management, Yu Da University, Miao-Li County 361, Taiwan 2 Dept. of Industrial Engineering, New Mexico State University, Las Cruces, NM 88003, USA 3 Dept. of Industrial Engineering, University of Texas, El Paso, TX 79968, USA 4 Dept. of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242, USA Corresponding author: Han-Suk Sohn, [email protected]

This paper presents an optimization model and its application to a classical vehicle routing problem. The proposed model is exploited effectively by the hybrid Benders/genetic algorithm which is based on the solution framework of Benders’ decomposition algorithm, together with the use of genetic algorithm to effectively reduce the computational difficulty. The applicability of the hybrid algorithm is demonstrated in the case study of the Rockwell Collin’s fleet management plan. The results demonstrate that the model is a practical and flexible tool in solving realistic fleet management planning problems. Keywords: Vehicle Routing, Hybrid Algorithm, Genetic Algorithm, Benders’ Decomposition, Lagrangian Relaxation, Mixed-integer programming. (Received 9 June 2011; Accepted in revised form 28 February 2012)

1. INTRODUCTION The vehicle routing problem (VRP) involves a number of delivery customers to be serviced by a set of identical vehicles at a single home depot. The objective of the problem is to find a set of delivery routes such that all customers are served exactly once and the total distance traveled or time consumed by all vehicles is minimized, while at the same time the sum of the demanded quantities in any routes does not exceed the capacity of the vehicle. The VRP is one of the most challenging combinatorial optimization problems and it was first introduced by Dantzig and Ramser (1959). Since then, the VRP has stimulated a large amount of researches in the operations research and management science community (Miller, 1995). There are substantial numbers of heuristic solution algorithms proposed in the literature. Early heuristics for this problem are those of Clarke and Wright (1964), Gillett and Miller (1974), Christofides et al. (1979), Nelson et al. (1985), and Thompson and Psaraftis (1993). A number of more sophisticated heuristics have been developed by Osman (1993), Thangiah (1993), Gendreau et al. (1994), Schmitt (1994), Rochat and Taillard (1995), Xu and Kelly (1996), Potvin et al. (1996), Rego and Roucairol (1996), Golden et al. (1998), Kawamura et al. (1998), Bullnheimer et al. (1998 and 1999), Barbarosoglu and Ozgur (1999), and Tom and Vigo (2003). As well, exact solution methods have been studied by many authors. These include branch-and-bound procedures, typically with the basic combinatorial relaxations (Laporte et al., 1986; Laporte and Nobert, 1987; Desrosiers et al., 1995; Hadjiconstantinou et al., 1995) or Lagrangiran relaxation (Fisher, 1994; Miller, 1995; Toth and Vigo, 1997), branch-and-price procedure (Desrochers et al., 1992), and branch-and-cut procedure (Augerat et al, 1995; Ralphs, 1995; Kopman, 1999; Blasum and Hochstattler, 2000). Unlike many other mixed-integer linear programming applications, however, Benders’ decomposition algorithm was not successful in this problem domain because of the difficulty of solving the master system. In mixed-integer linear programming problems, where Benders’ algorithm is most often applied, the master problem selects values for the integer variables (the more difficult decisions) and the subproblem is a linear programming problem which selects values for the continuous variables (the easier decisions). For the VRP problem, the master problem of Benders’ decomposition is more amenable to solution by a genetic algorithm (GA) which searches the solution space in parallel fashion. The fitness function of the GA is, in this case, evaluated quickly and simply by evaluating a set of linear functions. In this short paper, therefore, a hybrid algorithm is presented in order to overcome the difficulty in implementing the Benders’ decomposition for the VRP problem. It is based on the solution framework of Benders’ decomposition algorithm, together with the use of GA to effectively reduce the computational difficulty. The rest of this paper is organized as follows. In section 2 the classical vehicle routing problem is presented. The application of the hybrid algorithm is described in section 3. In Section 4, a case study on the fleet management planning of the Rockwell Collin, Inc. is presented. Some concluding remarks are presented in Section 5. Finally, Section 6 lists references used in this paper.

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International Journal of Industrial Engineering, 19(1), 47-56, 2012.

A NEW TREND BASED APPROACH FOR FORECASTING OF ELECTRICITY DEMAND IN KOREA Byoung Chul Lee, Jinsoo Park, Yun Bae Kim Department of Systems Management Engineering, Sungkyunkwan University, Suwon, Republic of Korea Corresponding author: Yun Bae Kim, [email protected] Many forecasting methods for electric power demand have been developed. In Korea, however, these kinds of methods do not work correctly. A peculiar seasonality in Korea increases the forecasting error produced by previous methods. Two big festivals, Chuseok and Seol, also produce forecasting errors. Therefore, a new demand forecasting model is required. In this paper, we introduce a new model for electric power demand forecasting which is appropriate to Korea. We start the research using the concept of weekday average. The final goal is to forecast hourly demand for both the long and short term. We finally obtain the result with accuracy of over 95%. Keywords: Demand forecasting, electric power, moving average (Received 7 April 2010; Accepted in revised form 24 June 2011)

1. INTRODUCTION There have been many studies related to forecasting electric demand. These studies have contributed to achieving greater accuracy. Shahiderhpour et al. (2002) introduced market operation in electric power systems. Price modeling for electricity markets was described by Bunn (2004). Kawauchi et al. (2004) developed a forecasting method based on conventional chaos theory for short term forecasting. Gonzalez-Romera et al. (2007) used neural network theory, Oda et al. (2005) forecasted demand with regression analysis, and Pezzulli et al. (2006) focused on seasonal forecasting with a Bayesian hierarchical model . These attempts, while valuable, are inappropriate for Korea because there are four distinct seasons, which have their own feature such as a cycle of three cold days and four warm days in winter. In addition, Korean demand trend has a cycle by weekly unit. Therefore we have two sources of seasonality, seasonal factor and weekly factor. Therefore, the previous methods are not proper due to double seasonality. To examine double seasonality, we analyzed past data to determine properties of Korean electric demand. Using these properties, we defined a new concept of weekday average, (WA), and developed models for forecasting hourly demand of electric power in Korea. The organization of this paper is as follows. In Section 2, the concept of WA is used for 24 hours as the first step in forecasting hourly demand. In Section 3, we deal with the methods of forecasting WA and non-weekday demand, including holidays and festivals. We apply our model to the actual demand data and show the results in Section 4. We conclude the research and suggest further studies in Section 5.

2. CONCEPT OF WEEKDAY AVERAGE We found two special properties related to the hourly demand of electric power in Korea; one is the character of weekdays, and the other is a connection between weekdays and non-weekdays (a weekday means the days from Tuesday to Friday). Holidays and festival seasons are regarded as non-weekdays even though they are in a weekday period. The demands during each weekday are almost similar to one another at the same hour; this is the first property. However, the demands of Monday and weekends are less than those of weekdays by an invariable ratio; this is the second property. Therefore, our research starts by developing a method for forecasting the hourly demand of weekdays. We then find the relation between weekdays and non-week days. Let us define the hourly demand: ... (1) Dn i (h) : demand from (h − 1) : 00 to h : 00

(h = 1,  ,24 and i = 1, ,7). where n is the number of weeks from the base week; for example, if the base week is the first week in 2007, then Dec. 31st, 2007 has the value of n = 52 . i is the day of the week (1=Monday, 7= Sunday). ISSN 1943-670X

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International Journal of Industrial Engineering, 19(2), 57-67, 2012.

RELIABILITY EVALUATION OF A MULTISTATE NETWORK UNDER ROUTING POLICY Yi-Kuei Lin Department of Industrial Management National Taiwan University of Science and Technology Taipei, Taiwan 106, R.O.C. Tel: +886-2-27303277, Fax: +886-2-27376344 Corresponding author: Lin, [email protected] A multistate network is a stochastic network composed with multistate arcs in which each arc has several possible capacities and may fail due to failure, maintenance, etc. Different from the deterministic case, the minimum transmission time in a multistate network is not a fixed number. We evaluate the probability that a given amount of data/commodity can be sent from a source port to a sink port through a pair of minimal path (MP) simultaneously under the time constraint. Such a probability is named the system reliability. An efficient solution procedure is first proposed to calculate it. In order to enhance the system reliability, the network administrator decides the routing policy in advance to indicate the first and the second priority pairs of MP. Subsequently, we can evaluate the system reliability under the routing policy. An easy criterion is then proposed to derive an ideal routing policy with higher system reliability. We can treat the system reliability as a performance index to measure the transmission ability of a multistate network such as computer, logistics, urban traffic, telecommunication systems, etc. Keywords: Multistate network; commodity transmission; system reliability; transmission time; routing policy (Received 1 March 2010; Accepted in revised form 27 February 2012)

1. INTRODUCTION For a deterministic network in which each arc has a fixed length attribute, the shortest path problem is to find a path with minimum total length. When commodities are transmitted from a source to a sink through a flow network, it is desirable to adopt the shortest path, least cost path, largest capacity path, shortest delay path, or some combination of multiple criteria (Ahuja, 1998; Bodin et al., 1982; Fredman and Tarjan, 1987; Golden and Magnanti, 1977), which are all variants of the shortest path problem. From the point of view of quality management and decision making, it is an important task to reduce the transmission time through a flow network. Hence, a version of the shortest path problem called the quickest path problem proposed by Chen and Chin (1990) arises. This problem finds a quickest path with minimum transmission time to send a given amount of data/commodity through the network. In this problem, each arc has the capacity and the lead time contributes (Chen and Chin, 1990; Hung and Chen, 1992; Martins and Santos, 1997; Park et al., 2004). More specifically, the capacity and the lead time are both assumed to be deterministic. Several variants of quickest path problems are thereafter proposed; constrained quickest path problem (Chen and Hung, 1994; Chen and Tang, 1998), the first k quickest paths problem (Chen, 1993; Chen, 1994; Clímaco et al., 2007; Pascoal et al., 2005), and all-pairs quickest path problem (Chen and Hung, 1993; Lee and Papadopoulou, 1993). However, due to failure, partial failure, maintenance, etc., each arc should be considered as multistate in many real-life flow networks such as computer, logistics, urban traffic, telecommunication systems, etc. That is, each arc has multiple possible capacities or states (Jane et al., 1993; Lin et al., 1995; Lin, 2003, 2004, 2007a,b, 2009; Yeh, 2007, 2008). Then the transmission time thorough a network is not a fixed number if each arc has the time attribute. Such a network is named a multistate network throughout this paper. For instance, a logistics system with each node representing the shipping port and each arc representing the shipping itinerary between two ports is a typical multistate network. The capacity of each arc is counted in terms of number of container, and is stochastic due to that either containers or traffic tools (e.g., cargo airplane, cargo ship, etc.) through each arc may be in maintenance, reserved by other suppliers or in other conditions. The purpose of this paper is to design a performance index to measure the transmission ability for a multistate network. In order to reduce the transmission time, the data/commodity can be transmitted through several minimal paths (MPs) simultaneously, where an MP is a sequence of arcs without loops. For convenience, we first concentrate on commodity transmission through two MPs. We mainly evaluate the probability that the multistate network can send d units of commodity from a source port to a sink port through a pair of MP under the time constraint T. Such a probability is named the system reliability, which can be treated as a performance index. Under the same time constraint and demand requirement, the system owns a better transmission ability if it obtains the higher system reliability. In order to boost the transmission ability, the network administrator decides the routing policy in advance to indicate the first and the second ISSN 1943-670X

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International Journal of Industrial Engineering, 19(2), 68-79 2012.

DETERMINING THE CONSTANTS OF RANGE CHART FOR SKEWED POPULATIONS Shih-Chou Kao Graduate School of Operation and Management, Kao Yuan University, No.1821, Jhongshan Rd., Lujhu Dist., Kaohsiung City 821, Taiwan (R.O.C.). Corresponding author email: [email protected] The probability of a false alarm rate (type I risk) in Shewhart control charts based on a normal distribution will increase as the skewness of a process increases. However, the distribution of a range is a positively–skewed one. It is unstable for monitoring range values by using three-sigma control limits that is from the concept of a normal assumption. Moreover, most studies employ a simulation method to compute the type I risks of the range control chart for non–normal processes. To provide an alternative method, this study utilizes the probability density function of the distribution of the range to construct the appropriated control limits of a range control chart for a skewed process. The control limits of the range chart were determined by setting that the type I risk is equal to 0.0027 and the standardized Weibull, lognormal and Burr distributions. Furthermore, compared to range charts that use type I risks and type II risks, weighted variance (WV), skewness correction (SC) and traditional Shewhart control charts, the proposed range chart is superior to other control chart, in terms of the type I risks and type II risks for a skewed process. An example of the yield strength for the deformed bar in coil is presented to illustrate these findings. The study utilized the probability density function of range distribution and α=0.0027 probability limits with considering the three distributions, Weibull, lognormal and Burr to construct the R control chart. The computed constants of the R control chart were listed in a table that can be consulted by for practitioners. R chart using the proposed method is superior to other control chart, in terms of the type I risks and type II risks for a skewed process. Keywords: Range chart, skewed distribution, normality, type I risk. (Received 22 March 2010; Accepted in revised form 24 June 2011)

1. INTRODUCTION The development of control charts became rapid and diverse after W. A. Shewhart proposed a traditional control chart. Control charts have the superior ability for monitoring a process in manufacturing, and they have been applied successfully in other areas, such as finance, health care and information. The Shewhart range (R) control chart is one of the most frequently used control charts since it is easily operated and interpreted by practitioners. In general, traditional variable control charts, such as an average and a R control charts, are based on the normality assumption. However, many processes in industry violate this assumption. These skewed processes involve chemical processes, cutting tool wear processes and lifetime in an accelerated life test (Bai and Choi, 1995). Moreover, the range distribution is a positively–skewed one (Montgomery, 2005). If the traditional control charts are used to monitor a non–normal process, the probabilities of a type I error (α) in the control charts increases as the skewness of the process increases (Bai and Choi, 1995; Chang and Bai, 2001). Bai and Choi (1995), Chang and Bai (2001) and Montgomery (2005) considered four methods for improving the capabilities of control charts for monitoring a skewed process. The first method increased the sample sizes on the basis of the central limit theorem. When the samples are larger, the skewed distribution will become a normal or approximately normal distribution. However, the method is often expensive due to sampling. The second method is to assume that the distribution of a process is known and then to derive a suitable control chart from this known distribution. Ferrell (1958) designed geometric midrange and range control charts for a lognormally distributed process. Nelson (1979) proposed median, range, scale and location control charts for a Weibull distribution. The third method is to construct the traditional control chart using approximately normal data that result from transforming skewed data. Various criteria were proposed to transform exponential data, such as maximum likelihood and Bayesian methods (Box and Cox, 1964), Kullback–Leibler (K–L) information numbers (Hernandez and Johnson, 1980; Yang and Xie, 2000), measure of symmetry (zero skewness; Nelson, 1994), ease of use (Kittlitz, 1999) and minimizing the sum of the absolute differences (Kao et al., 2006), to assess transformation efficiency. The shortcoming of this method is that it is difficult to identify an exact distribution of a process with the second method. The last method is to construct control charts using heuristic methods with no assumption on the form of the distribution. Choobineh and Ballard (1987) proposed the WV method to determine the constants of average and R charts based on the semivariance estimation of Choobineh and Branting (1986). Bai and Choi (1995) considered the three skewed distributions (Weibull, lognormal and Burr) and determined the constants of average and R charts using the weighted variance (WV) method by splitting a skewed distribution in two parts at the mean. Chang and Bai (2001) decided the constants of average control chart by replacing a variance of WV method with a standard deviation. Chan and Cui (2003) proposed the skewness correction (SC) method based on the Cornish–Fisher expansion (Johnson et al., ISSN 1943-670X

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International Journal of Industrial Engineering, 19(2), 80-89 , 2012.

PERFORMANCE MODELING AND AVAILABILITY ANALYSIS OF SOLE LASTING UNIT IN SHOE MAKING INDUSTRY: A CASE STUDY Vikas Modgil 1, S.K. Sharma2, JagtarSingh3 1

Dept of Mechanical Engineering, D.C.R.U.S.T., Murthal, Sonepat, Haryana, India 2 Dept of Mechanical Engineering, N.I.T Kurukshetra, Haryana, India 3 Dept of Mechanical Engineering, S.L.I.E.T Longowal, Sangrur, Punjab, India Corresponding author: Vikas Modgil, [email protected]

In the present work Performance modelling of the sole lasting unit, a part of shoe making industry has been done on the basis of Markov birth-death process using probabilistic approach for the purpose to compute and improve the time dependent system availability (TDSA). The kolmogorov-differential equations based on mnemonic rule are formulated using the performance model and are solved to estimate the availability of the system as a function of time month wise for the whole year using a more sensitive and advance numerical technique, known as adaptive step-size control RungeKutta method. The input contributors for the computation of time dependent system availability of the system are the existing failure and repair rate are taken from plant maintenance history sheets. The new repair rates are also devised for the purpose of maximum improvement in the availability. The analysis finding helps the plant management for adapting the best possible maintenance strategies. Performance modeling and availability analysis of a practical system is conducted in the paper with the purpose to improve its operational availability. The time dependent system availability (TDSA) is computed with the existing failure and repair rates on the monthly basis for the whole year. New devised repair rates are also proposed through which one can assure maximum availability of the system with existing equipments/or machines. It is also explored that the, the knowledge of TDSA minimizes the chances of sudden failure and assure the maximum availability of the system and exposes the critical subsystems which needs more attention and due consideration as far as the maintenance is concerned. The improvement in the availability of the system is mostly from 2% to 5% in most of the month. However it increases drastically to 9% in the month of April. Further the assured increase in availability increases productivity as well as the balance between demand and supply such that the manufacturer delivers its product properly in time to the market/society, which in turn increases the profit and the reputation of industry in the market. Keywords: Performance Modelling, Time Dependent System Availability (TDSA); Runge-Kutta; Sole Lasting. Kolmogorov-Differential equation, Shoe Making. (Received 25 September 2011; Accepted in revised form 27 February 2012)

1. INTRODUCTION With increasing advancement and automation, the industrial systems are getting complex and thus maintaining their failure-free operation is not only costly but also difficult. Thus maximum availability levels are desirable to reduce the cost of production and maintaining them in working order for a long duration. The industrial operating conditions and repair facility play also an important role in this regard. Several attempts have been made by various researchers and authors to find the availability of practical industrial system using different techniques. Dhillon and Natesan (1983) examined the availability of power system in fluctuating environment. Singh I.P. (1989) studied the reliability analysis of a complex system having four types of components with pre-emptive priority repairs. Singh and Dayal (1992) studied the reliability analysis of a repairable system in a fluctuating environment. Gupta et al. (2005) evaluated the reliability parameters for butter manufacturing system in a diary plant considering exponentially distributed failure rates of various components. Solanki et al (2006) evaluated the reliability of thermal-hydraulic passive systems using thermal hydraulic code RELAP 5/MOD 3.2(which operate in two phase natural circulation). Rajpal et al (2006) employed artificial neural network for modelling reliability, availability and maintainability of a repairable helicopter transport facility. Kumar et al. (2007) developed a simulated availability model for CO2 cooling system of a fertilizer plant. Goyal et al. (2009) discusses the steady state availability analysis of a part of rubber tube production system under pre-emptive priority repair using Laplace transform technique. Garg S.et al. (2010) computed the availability of crank-case manufacturing in a 2-wheeler automobile industry and block board system under pre-emptive priority discipline. In this paper a sub-system of the practical plant “Liberty Shoes Limited” which is a continuous production system is taken and the time dependent system availability of the system is estimated using a more advance and sensitive numerical technique known as adaptive step-size runge-kutta method. The earlier work carried out by most of the research groups do not entertain this aspect of time dependent availability. They just provide the long run or steady state availability of the system by taking time infinity. The liberty shoe making plant situated in Karnal, Haryana, India is chosen for study. Numerical results based upon the true data collected from industry are presented to illustrate the

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International Journal of Industrial Engineering, 19(2), 90-100, 2012.

SIMULATION MODELING OF OUTBOUND LOGISTICS OF SUPPLY CHAIN: A CASE STUDY OF TELECOM COMPANY Arvind Jayant1, S. Wadhwa2, P.Gupta3, S.K.Garg4 1,3

Department of Mechanical Engineering Sant Longowal Institute of Engg. & Technology, Longowal, Sangrur, Punjab – 148106 (INDIA) 2 Department of Mechanical Engineering, Indian Institute of Technology, Delhi (INDIA) 4 Department of Mechanical Engineering, Delhi Technological University, Delhi-110042 Corresponding author: Arvind Jayant, [email protected] The present work has been done for a telecom company with a focus on cost and flexibility in effectively deals with changing scenario. In this paper, the major problems faced by company at upper end of supply chain and sales outlet are analyzed and a complete inventory analysis on one of a company product is done by developing an Inventory model for the company bound store/distribution center and optimal inventory policy is suggested for the outbound logistics on the basis of simulation analysis. This model is flexible enough to respond to the market fluctuations more efficiently and effectively. The model is developed in Microsoft EXCEL. Significance: Increasing competitive pressures and market globalization are forcing the firms to develop supply chains that can quickly respond to customer needs. The inventory model for the company’s bound store/outbound logistics has been developed & simulated to reduce the operating cost, stock out, to make supply chain agile. Key words: Supply Chain, Outbound Logistics, Information Technology, Simulation, Operating Cost, Inventory. (Received 4 August 2010; Accepted in revised form 28 February 2012)

1. INTRODUCTION The basis of global competition has changed. No longer are companies competing against other companies, but rather supply chains are competing against supply chains. Indeed, the success of a business is now invariably measured neither by the sophistication of its product nor by the size of the market share. It is usually seen in the light of the ability to sometimes forcefully and deliberately harness its supply chain to deliver responsively to the customers as and when they demand it. Flexible Supplier-manufacturer relationship is the key enabler in the supply chain management, without the flexibility at the vendor side the supply chain can’t respond fast. Therefore, the relationship with the supplier should be flexible enough to meets the changing market needs [2]. In this paper several experiments were carried out on the model for visualizing the impact of the various decision variables on the total cost and then fixing up the values of (s) and (S). The graphs showing the impact of these parameters on the performance of the individuals and the system were plotted. Based on the system’s performance under different sets of operating decisions we shall try to analyze the effect of the different parameters and in what manner their decisions affect the performance of others across the chain. The parameters whose impact was studied are stock level (S), reorder level (s); this paper deals with the impact of increase in stock levels and reorder level of the warehouse on overall system performance [6].

2. ABOUT THE PRODUCT Bharti -Teletech is a giant in the manufacturing of all kind of telephone sets for the Department of Telecommunication, open market and for exports. The company share in this segment is highest in India. This company has 35% share in telephone segment in India. The company is producing the seven model of telephone with brand name of beetal. § The company is currently facing the problem of delivering the CORAL & MILL –I model of phones on schedule date. Though the number of shortage is small but any delivery made beyond schedule will be considered as the lost opportunity of sale. § The coral is general model for the open market and its demand is highly uncertain therefore frequent stock outs are going on at the end of bound store and warehouse side. § The forecasts generated using the 6-month average were not giving the appropriate results. § The warehouse is not using the any inventory policy and the reorder level of the warehouse was made intuitively made. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(2), 101-115, 2012.

SIMULATION-BASED OPTIMIZATION FOR RESOURCE ALLOCATION AT THIRD-PARTY LOGISTICS SYSTEMS Yanchun Pan1, Ming Zhou2, Zhimin Chen3 1,3 2

College of Management, Shenzhen University, P.R. China

Center for Systems Modeling and Simulation, Indiana State University Corresponding author: Ming Zhou, [email protected]

Allocating resource at third-party logistics systems differs significantly from traditional private logistics systems. The resources are considered commodities sold to customers of different types. Total yield suffers when over-allocate to lower-rate or price-sensitive customers; but the resource become “spoiled” when reserve too much for full-rate or time-sensitive customers that do not arrive as expected. Uncertain order characteristics make the optimization of such decisions very hard, if not impossible. In this paper we proposed a simulation-based optimization to address related issues. A genetic algorithm based optimization module is developed to generate/search good solutions; and a discrete-event simulation model is created to evaluate the solutions generated. The two modules are integrated to work in evolutionary cycles to achieve the optimization. The study also compared GA/Simulation model with more traditional approach such as response surface methodology via designed experiments. The models were validated through experimental analysis. Keywords: resource allocation; simulation; genetic algorithm; optimization; third-party logistics (Received 2 September 2010; Accepted in revised form 1 March 2012)

1. INTRODUCTION Studies on third-party logistics (TPL) systems have been thriving since last two decades, as TPL systems gain popularity in many parts of the world through the flexibility and convenience they provide to improve the quality and efficiency of logistics services and customer satisfaction (Lambert et al, 1998; Bowersox et al, 2002). Resource or capacity allocation (e.g. allocation of warehouse space for temporary storage of customer goods) at TPL systems differs significantly from traditional private logistics system. Unlike private systems, TPL companies use “public warehouses” that are usually more efficient than private ones through better productivity, shared resources, economy of scale, and transportation (delivery) consolidation (Ackerman, 1994); and consider the resources to be allocated as commodities sold directly to different customers repeatedly via services generated based on the resources, such as storing, handling, or transporting goods. Also such resources are considered “perishable” when they are not sold at or during a period of time, i.e. they cause the loss of possible revenue that could have been otherwise generated if they were sold (Phillips, 2005). As in airline or hospitality industries, there are mainly two types of customer demands, and accordingly two different approaches for allocating resource to customer orders. First, many customers prefer to have their orders placed in advance a period of time to expect a discounted rate of service. Once allocated, the chunk of resource is “locked in” and subtracted (from available stock) for the usage period of the order, which is a time period during which the allocated resource is consumed to generate service for the order. This type of customer is price-sensitive. The risk of over-allocating resource to this kind of orders is that we may lose opportunities to serve more profitable full-rate customers (or customers willing to pay higher rates). This is known as the “risk of spill” (Humphreys, 1994; Phillips, 2005). On the other hand, there are customers who are less price-sensitive, but more time-sensitive, i.e. they place orders often at a time very close to (or at) the ISSN 1943-670X

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International Journal of Industrial Engineering, 19(3), 117-127, 2012.

TRACKING AND TRACING OF LOGISTICS NETWORKS: PERSPECTIVE OF REAL-TIME BUSINESS ENVIRONMENT AHM Shamsuzzoha and Petri T Helo Department of Production University of Vaasa, PO BOX 700, FI-65101, Finland Today’s business environments are full of complexities in terms of managing the value adding supply chain and logistics networks. In recent years, the development of locating and identifying technologies contribute to fulfill the growing demands of tracking and tracing the logistics and/or transportation chain. The importance of tracking and tracing of shipments is considered quite high for manufacturing firms in respect to managing logistics networks efficiently and satisfying high customers demand. This paper presents a theoretical overview of sophisticated technology-based methodology or approach required for solving the complex tracking and tracing system in the logistics and supply chain network. A real-life case example is presented in this paper with the view to demonstrate the tracking technology in terms of identifying the location and related conditions of the case shipment. The overall outcomes from this research are concluded with future research direction too. Significance: This work basically reviews the existing tracking and tracing technologies available over the areas of logistics and supply chain management. It also demonstrates the methodology for implementing such technologies in reallife business cases and provides insight of tracking and tracing technology with respect to identifying location, position and conditions of the shipped items. Keywords: Logistics tracking and tracing, IT-based solution, Transportation and Distribution network, Real-time information flow, Business competition. (Received 3 June 2011; Accepted in revised form 31 July 2011)

1. INTRODUCTION The identification of location and knowing the conditions of the transported items on real-time business environment are growing increasing concern in today’s business. This is very much expected for the manufacturing firms in terms of their business growth and making the customers happy. The importance of tracking and tracing of shipments is considered quite high for manufacturing firms in terms of customer service and essential for managing logistics networks efficiently. Global industries are facing problems both from tracking and tracing in their logistics networks that creates huge coordination problems in the overall product development sites. This problem looses the track among production, delivery and distribution in the complete logistics chain from source to destination, which is responsible for opportunity cost through customers’ dissatisfaction. Tracking system helps to identify the position of the shipment and informed the customer in well advance. Without tracking system it is almost impossible to find out delivered items and often considered as lost or stolen item that causes business loss. This system might fulfill the needs of project manager to map the production process from transportation to material management (Helo et al., 2005, Helo, 2006). Recently evolved technologies supports the fundamental needs for tracking and tracing the logistics network. The tracking technology ensures the real-time status update of the target shipment and provides the detailed information corresponding to location, conditions of the shipments (vibration, damage, missing, etc). In practice, there are several tracking systems available through GPS, GTIN (EAN Int., 2001), RFID (ISO/IEC, 2000; Chang, 2011), Barcode etc; however, all these systems are not fully compatible for industry. Most of the available tracking and tracing systems utilize proprietary tracking numbers defined by the individual companies operating systems and are based on information architecture, where the tracking information is centralized to the provider of the tracking service. Existing tracking systems can not able to identify the contents within a box for example, whether the box is open or the contents are lost or stolen etc. In order to tackle such misalignments in the logistics channel, a state-of-the art technologies or tools are needed to be developed for sustainable production process. These tools are needed to be cost effective and at the same time possibility for reuse or recycling for any circumstances. Before proceed towards the real-time tracking technology, it is crucial to analyze its possible cause and effects. Optimal performance measures for the technologies could ensure projects success for any industries. Tracking technologies in logistics networks are implemented fairly little in the global technology industry. Mostly high volume of global industries are implemented this technology with limited capabilities. The basic methods for all these tracking systems are usually confined for the customer to access the tracking information are within the area of tracing the shipments through manual queries such as using a www-site or telephone call, e-mailing, fax or to engage in developing ISSN 1943-670X

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International Journal of Industrial Engineering, 19(3), 128-136, 2012.

A MATHEMATICAL PROGRAMMING FOR AN EMPLOYEES CREATIVITY MATRIX CUBIC SPACE CLUSTERING IN ORGANIZATIONS Hamed Fazlollahtabar*1, Iraj Mahdavi2, Saber Shiripour2, Mohammad Hassan Yahyanejad3 1 Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran 2 Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran 3 Mazandaran Gas Company, Sari, Iran *Corresponding author’s email: [email protected] We investigate different structural aspects teams’ network organization and their creativity within a knowledge development program (KDP). Initially, a pilot group of employees in an organization is selected. This group is evaluated through creativity parameters using a questionnaire. Considering the questionnaires’ data, a creativity matrix is configured by a binary scoring. Applying the creativity matrix, clustering is performed via mathematical programming. The pilot group is divided into some research teams. The research subjects are submitted to the teams. Finally, an allocated problem is solved and some new research subjects are evolved to be assigned to the next configured teams. This procedure is repeated dynamically for different time periods. Keywords: Creativity matrix; Intelligent clustering; Cubic space clustering (Received 28 September 2011; Accepted in revised form 20 December 2011)

1. INTRODUCTION In today’s knowledge-intensive environment, Knowledge Development Programs (KDPs) are increasingly employed for executing innovative efforts (Oxley and Sampson, 2004; Smith and Blanck, 2002). Researchers and practitioners mainly agree that effective management plays a critical role in the success of such KDPs (Pinto and Prescott, 1988). Unfortunately, the knowledge and experience base of most managers refer to smaller-scale projects consisting of only a few project teams. This may be responsible for what Flyvbjerg et al. (2003) call a ‘performance paradox’: ‘‘At the same time as many more and much larger infrastructure projects are being proposed and built around the world, it is becoming clear that many such projects have strikingly poor performance records ...”. KDPs employ follow a project-management like approach with the team as the organizational nucleus (e.g., van Engelen et al., 2001). The information network of these teams defines the opportunities available to them to create new knowledge (e.g., Uzzi, 1996). As many scholars have argued, networks of organizational linkages are critical to a host of organizational processes and outcomes (e.g., Baum and Ingram, 1998; Darr et al., 1995; Hansen, 1999; Reagans and McEvily, 2003; Szulanski, 1996). New knowledge is the result of creative achievements. Creativity, therefore, molds the foundation for poor or high degree of performance. The extent to which teams in KDPs produce creative ideas depends not only on their internal processes and achievements, but also on the work environment in which they operate (e.g., Amabile et al., 2004; Perry-Smith and Shalley, 2003; Reiter-Palmon and Illies, 2004). Since new knowledge is mainly created when existing bases of information are disseminated through interaction between interacting teams with varying areas of expertise, creativity is couched in interaction networks (e.g., Leenders et al., 2003; Hansen, 1999; Ingram and Robert, 2000; Reagans and Zuckerman, 2001; Tsai, 2001; Uzzi, 1996). Any organization needs team work among employees for productivity purposes in problem solving. Organizations face various problems in their determined missions. A useful approach to address these problems is to configure teams consisting of expert employees. Due to their knowledge and experience of the organization, these teams understand the organization's problems better more than external research groups and thus may solve the problems more effectively. Hence, the significant decision to be made is configuration of the teams. Creative teams would be able to propose more practical and beneficial solutions for organization's problems. Since creativity is a qualitative concept, analyzing and decision making require knowledge management algorithms and methodologies. These methodologies are employed in the different steps of configuring teams, task assignment to teams, teams' progress assessment and executive solution proposals for problems. In the present work, we propose a creativity matrix analyzing creativity parameters of a pilot group in an organization. Then, using an intelligent clustering technique, research teams are configured and research subjects are allocated to them.

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International Journal of Industrial Engineering, 19(3), 137-148, 2012.

ACCEPTANCE OF E-REVERSE AUCTION USE: A TEST OF COMPETING MODELS Fethi Calisir and Cigdem Altin Gumussoy Department of Industrial Engineering Istanbul Technical University This study aims to understand factors affecting e-reverse auction usage in companies by comparing three models: Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) and the integrated model (integration of TAM and TPB). The comparison of the models will answer two important questions: First, with the integration of the models, whether the explanation rate of behavioral intention to use and actual use is increased. Second, in explaining e-reverse auction usage, whether TAM is the most powerful method. Since TAM is developed only to explain usages of information technologies (IT). Using LISREL 8.54, data collected from 156 employees working in the procurement department of companies in 40 different countries were used to test the models. Results indicated that, TPB may be more appropriate than the TAM and the integrated model for explaining behavioral intention to use e-reverse auction. Further, the explanation rate of both behavioral intention to use and actual use is not increased with the integration of the models. The other result suggests that behavioral intention to use is explained- by only attitude towards use in TAM; by subjective norms, perceived behavioral control and attitude towards use in both TPB and the integrated model. Actual use of e-reverse auction is directly predicted by behavioral intention to use in all three models. This study concludes with the discussion of the findings, implications for practitioners and recommendations for possible future research. Significance:

This paper aims to identify significant factors affecting e-reverse auction usage among buyers working in the procurement department of companies by comparing three models: TAM, TPB and the integrated model. The comparisons will explore that whether the explanation rates of behavioral intention to use and actual use is increased with the integration of the models and whether TAM is the most powerful method in explaining the usage behavior of e-reverse auction users.

Keywords: E-reverse auction, TAM, TPB, Integrated model, Actual use, Model comparison (Received 7 June 2011; Accepted in revised form 18 September 2011)

1. INTRODUCTION E-reverse auction is an online- and real-time auction between a buying company and two or more suppliers (Carter et al., 2004). Use of the e-reverse auction tool was first offered by FreeMarkets in 1999 and has since then been progressively adopted more intensively by firms. Several Fortune Global 2000 companies use e-reverse auction as a purchasing tool (Giampietro and Emiliani, 2007). For example, General Electric spends 50-60 billion $ per year and people in positions of responsibility believe that 50-66% of this amount can be auctioned (Hannon, 2001). Using e-reverse auction offers many advantages to buyers as well as suppliers. Price reduction is undoubtedly the most important one. Suppliers may have to make higher price reductions to win the auction (Giunipero and Eltantawy, 2004). In addition to the price advantage, increase in buyer productivity, reduction in cycle time, access to many suppliers at the same time, creating a more competitive environment, standardization, and transparency in purchasing process are the other advantages of e-reverse auction. All these advantages create more opportunities for companies by reduction in cost and time, enabling these companies can offer higher quality products (Carter et al., 2004; Bartezzaghi and Ronchi, 2003). In 2000, General Electric saved $480 million by using e-reverse auction from its $6.4 billion expenditure (Hannon, 2001). Ereverse auction has benefits not only for buyers but also for suppliers. These are growing markets, accessed by system users all over the world, who are enabled to compare their own competitiveness in the market and follow up auctions by potential customers on the Internet. Besides, they can estimate their customers’ needs and market trends by checking the e-reverse auctions’ specifications and conditions for the products and services. Thus, suppliers can not only see areas for improvement and but also their own needs for improvement (Emiliani, 2000; Mullane et al., 2001). Therefore, it is important to explain and understand the factors that affect the use of e-reverse auctions as they aim at improving performances of company and employees to complement each other. To our knowledge, the only study that compares models in the context of e-auction is Bosnjak et al. (2006). In their study, they aim to explain English auction use, which is generally used in business-to-customer and customer-to-customer markets, whereas the current study is related with ereverse auction technology, used for procurement of products or services in the business-to-business markets. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(3), 149-160, 2012.

A METHODOLOGY FOR PERFORMANCE MEASUREMENT IN MANUFACTURING COLLABORATION 1

Jae-Yoon Jung1, JinSung Lee1, Ji-Hwan Jung2, Sang-Kuk Kim1, and Dongmin Shin3 Department of Industrial and Management Systems Engineering, Kyung Hee University, Korea 2 Business Innovation Center, LG Display, Korea 3 Department of Industrial and Management Engineering, Hanyang University, Korea Corresponding author: Dongmin Shin, [email protected]

Effective performance measures must be developed in order to effectively maintain successful collaboration. This paper presents a methodology of collaborative performance measures to evaluate the overall performance of a collaboration process between multiple manufacturing partners. The partners first define collaborative key performance indicators (cKPI), and they then measure the cKPIs and calculate the synthetic performance from the cKPI values to evaluate the result of the collaboration case. To measure different scales of cKPI, we develop a two-folded desirability function based on the logistic sigmoid functions. The proposed methodology provides a quantitative way to measure collaborative performance in order to effectively manage collaboration among partners, continuously improving collaboration performance. Keywords: Manufacturing collaboration, performance measurement, collaborative key performance indicators, twofolded desirability function, sigmoid function. (Received 17 May 2011; Accepted in revised form 18 September 2011)

1. INTRODUCTION One important change in the manufacturing industry is that competition between individual companies has been extended to competition between the manufacturing networks surrounding the companies (NISA, 2001). This is because the competitive advantages of modern manufacturing companies are derived from manufacturing collaboration in virtual enterprise networks such as supply chains (Mun et al., 2009). Most existing performance measures, however, have been developed to evaluate the performance of internal or outsourcing projects from the perspective of a single company (Ghalayini et al., 1997; Khadem et al., 2008; Koc, 2011). Moreover, some performance indicators such as trading costs are oriented to a single company, and cannot be directly applied to measuring the collaboration performance since such indicators conflict between two partners. As a result, new collaborative performance measures are needed so that collaboration partners can make arrangements and compromises with each other, reflecting their common interests. In this paper, we first introduce the concept of collaborative key performance indicators (cKPIs), which are defined to measure the collaboration performance of multiple manufacturing partners. cKPIs are calculated by using several key performance indicators (KPIs) which individual partners can measure. For this research, we referred to the Supply Chain Operations Reference (SCOR) model (SCC, 2006) to define cKPI for manufacturing collaboration. Since the SCOR model provides corresponding performance metrics as well as several levels of supply chain process models, it can be a good reference for defining collaborative performance indicators (Barratt, 2004). In addition, we developed a two-folded desirability function to reflect the characteristics of performance indicators in manufacturing collaboration. The desirability function, which is based on the sigmoid function, can reflect multiple cKPI criteria in service level agreements (SLA). Further, unlike existing desirability functions, the sigmoid based desirability function can transform different scales of cKPIs into values between 0 and 1 without requiring maximum or minimum values (Lee and Yum, 2003). The weighted values of two-folded desirability functions for all cKPIs are summed to determine the synthetic performance of a collaboration, which can be compared with prior performance or partners’ performance. This paper is organized as follows. We first introduce the background of our research in Section 2. The framework of collaborative performance management is presented, along with the concept of cKPI, in Section 3. Subsequently, how to design the collaborative performance indicators and how to measure the performance indicators of manufacturing collaboration are described in Section 4 and Section 5, respectively. Finally, Section 6 concludes this paper.

2. BACKGROUND 2.1 Collaboration in Manufacturing Processes Manufacturing sector is a critical backbone of a nation’s economy while other industries such as information and service sectors are rapidly emerging for economic growth in developed countries. In order for manufacturing ISSN 1943-670X

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International Journal of Industrial Engineering, 19(3), 161-170, 2012.

A FRAMEWORK FOR THE ADOPTION OF RAPID PROTOTYPING FOR SMEs: FROM STRATEGIC TO OPERATIONAL Ayyaz Ahmad*, Muhammad Ilyas Mazhar and Ian Howard Department of Mechanical Engineering, Curtin University of Technology, WA 6102, Australia *Corresponding author: Ayyaz Ahmad, [email protected] Rapidly changing global markets, unprecedented increase in product flexibility requirements and shorter product life cycles require more efficient technologies that can help reduce the time to market, which is considered to be a crucial factor to survive in today’s highly volatile market conditions. Rapid prototyping technology (RPT) has the potential to make remarkable reductions in the product development time. However, its fast development pace combined with increasing complexity and variety has made the task of RPT selection difficult as well as challenging, resulting in low diffusion particularly at SME level. This paper systematically presents (i) Low RP adoption issues and challenges (ii) Importance of SMEs and the challenges they are facing to highlight the magnitude of the problem (iii) Previous work in the area of technology selection and adoption and finally offers an adoption framework which is exclusive for the adoption of RP technology by considering the manufacturing, operational, technology and cost drivers for a perfect technology fit into the business. Significance:

Rapid Prototyping (RP) exhibits unique characteristics and can have potential impact on all business functions, which demands a methodological approach for the evaluation and adoption of the technology. The main focus of this study is to propose a framework that facilitates the RP adoption from strategic to operational level to ensure complete and effective implementation to obtain the desired objectives, with a special emphasis on SMEs.

Keywords:

Rapid prototyping, Technology adoption, SMEs, Technology Selection, Competitiveness (Received 3 June 2011; Accepted in revised form 18 September 2011)

1. INTRODUCTION The changes in the global economic scenario have posed considerable threats to many companies, especially SMEs as they strive to stay competitive in world markets. This change in paradigms demands more flexibility in product designs. These challenges combined with increased variety and very short lead times has a great impact on the business of small to medium companies in securing a significant proportion of markets in which they operate. The conventional approaches and technologies are struggling to meet business needs. Consequently, manufacturers are searching for more efficient technologies, such as rapid prototyping that can help embrace the challenges. A critical activity for small companies is the decision-making on the selection and adoption of these advanced technologies. The SME’s task becomes more difficult because of the absence of any formal procedures (Ordoobadi et al., 2001). An advanced technology can be a great opportunity for a business but it can also be a threat to a company. A wrong alternative or too much investment in the right one can reduce the competitive advantage of a company (Trokkeli and Tuominen, 2002). The changing picture of the competition requires synchronization between business and new trends, which demands unique and effective solutions. These solutions should be designed to support them by keeping in view the specific nature of SMEs and ought to be simple, comprehensive and very practical so that they remain an effective part of the global value chain. To meet these global challenges, the design and manufacturing community is adopting the RP technology to remain efficient as well as competitive. The RP technology has enormous potential to shrink the product design and development timeline. Despite these great advantages, the adoption of RP at SMEs level is significantly low. A survey of 262 UK companies showed that 85% do not use RP. Lack of awareness of what the RP technology offers and how it can be successfully linked into the business functions are the key factors holding back this sector from the RP technology adoption. The majority of the groups who indicate that RP is irrelevant are unaware of what impact it can have on their business (Grenada, 2002). The condition is even worst in developing countries. Laar highlights the sensitivity of the issue by arguing that many engineers and R&D people are still unaware of the future implications of this technology. This is a major concern in view of the fact that technical departments are ignoring the RP/RM when it has already entered into world leading markets and has the potential to completely change the way we do business (Laar, 2007). Kidds argues that RP ISSN 1943-670X

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International Journal of Industrial Engineering, 19(3), 171-180, 2012.

AN INTEGRATED UTILISATION, SCHEDULING AND LOT-SIZING ALGORITHM FOR PULL PRODUCTION Olufemi A.B. Adetunji, Venkata S.S. Yadavalli Department of Industrial and Systems Engineering, University of Pretoria, Hatfield, Pretoria 0002, South Africa We present an algorithm that continuously reduces the batch sizes of products on Non-constraining resource in a production network through the utilization of the idle time on such resource. This leads to reduction in the holding cost and increase in the frequency of batch release of the production system. This would also lead to reduction in customer facing supply lead time. Such technique could be valuable in typical pull production systems like lean manufacturing, theory of constraints or Constant-Work-in-Process CONWIP processes. An example is used to demonstrate a real life application of the algorithm, and it was found to work better for system cost minimization than a previous algorithm that uses the production run length as the criterion for batch reduction. Keywords: Lot-sizing, Utilization, Setup, Pull production, Scheduling algorithm (Received 23 May 2011; Accepted in revised form 28 May 2012)

1. INTRODUCTION Traditionally, a lot size is taken to be the quantity of products contained in a production or purchase batch. This definition is also congruent to the classical batching model of economic order, which basically assumes that decision of what quantity to produce is made independently of job scheduling, but this is assumption is now being relaxed and the concept redefined. Potts and Wassenhove (1992), for instance, defined batching as making decision about whether or not to schedule similar jobs contiguously, and lot sizing as the decision about when and how to split the production of identical items into sub-lots. They noted that these decisions were traditionally taken as if lot sizing is independent of scheduling of jobs. This is obviated by the majority of the body of literature available on both subjects that are separate, with the impression being given that scheduling decisions are taken only after lot sizes of the various products have been decided. This assumption of independence is not usually true in most cases as the decisions are always inter-twined. Paul and Wassenhove also proposed a general model for integrated batching, lot sizing and scheduling. Drexl and Kims (1997) noted that lot-sizing and scheduling are two short term decisions of production planning that must be tied together with the medium term plan, which is the Master Production Scheduling of the system. Many models are since being published addressing integrated batching, lot sizing and scheduling. Potts and Kovalyov (2000) and Webster and Baker (1995) together with Potts and Wassenhove (1992) and Drexl and Kims (1997) are good readings. There is also a close relationship between system utilization and other system parameters like the Work-in-Process Inventory (WIP) and consequently the system holding cost and profitability. Variability in resource processing time and/or input arrival pattern have degrading influence on WIP level, especially as the system gets close to full utilization. This is succinctly summarized in Little’s law. This effect of resource utilization on the production plan and the level of WIP appears not to have been well studied. Among the few known models incorporating resource utilization into production scheduling include Rappold and Yoho (2008), and a model proposed in Hopp (2008). The procedure proposed by Hopp’s is simple and straightforward to use, and that is what has been extended, and hopefully improved, in this paper. Next is a brief review of some work currently being done on integrated lot-sizing. We then proceed to briefly review some necessary principles of the management of constraint system pertinent to our model; especially the emphasis on balancing flow rather than capacities, which creates pockets of spare capacities (labor and machine), and the useful breakdown of the total cycle time of manufacturing resources and jobs, which identifies the various locations and quantities of idle capacities in the system, which can then be used in improved job scheduling due to reduced customer facing lead time and decreased lot sizes. The insight derived, however, is useful in other pull production environments as well since all pull techniques (including lean and CONWIP) always prefer to concentrate on flow and to buffer input and process variability via spare capacities as opposed to excess inventories.

2. INTEGRATED SCHEDULING AND LOT SIZING MODELS Solving integrated batching, lot sizing and scheduling problems has received more research attention recently. This could have also been buoyed by the development of many heuristics and techniques for solving difficult combinatorial problems. Among the recently published work in this area include Toledo et al (2010), which evaluated different parallel algorithms ISSN 1943-670X

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International Journal of Industrial Engineering, 19(4), 181-192, 2012.

THE OPTIMAL ORGANIZATION STRUCTURE DESIGN PROBLEM IN MAKE-TO-ORDER ENTERPRISES Jesús A. Mena Department of Industrial Engineering, Monterrey Institute of Technology Campus, Chihuahua, Mexico This paper addresses the organization structure design problem in a make-to-order (MTO) operation environment. A mathematical model is presented to aid an operations manager in an MTO environment to select a set of potential managerial layers to minimize the operation and supervision cost. With a given Work Breakdown Structure (WBS) for any specific project, solving this model leads an optimal organization structure design. The proposed model considers allocation tasks to workers, considering complexity and compatibility of each task with respect to workers, and the requirement of management for planning, execution, training and control in a hierarchical organization. This model addresses the span of control problem and provides a quantitative approach to the organization design problem and is intended for applications as a design tool in the make-to-order industries.

Keywords Span of control, Organizational Design, Hierarchical Organization, Assignment Problem, Make-to-order (Received 20 Sept 2011; Accepted in revised form 2 Jan 2012)

1. INTRODUCTION The span of management is perhaps the most discussed single concept in classical, neo-classical or modern management theory. Throughout its evolution it has been referred to by various titles such as span of management, span of control, span of supervision, and span of authority (Van Fleet & Benedian, 1977). The existing research work focus on principally qualitative methods to analyze this concept, i.e., heuristic rules based on experiences and/or intuition. This research develops an analytical modeling to determine the number of managerial layers and it is motivated in order to have an evaluation tool for functional based companies and also as a design tool for project-based companies. The challenge of mass customization brings great value to both the customer and the company. For example, building cars to customer order eliminates the need for companies to hold billions of dollars worth of finished stock. Any company able to free this capital would improve their competitive position, and be able to reinvest in future product development. The question for many company executives is how efficient the organizational structure could be. The need for frequent adjustment to an organizational structure can be found in this type of make-to-order or project-based companies, where work contents and its organizational structure could vary dramatically over a short period of time. This paper presents an analytical model for analyzing hierarchical organizations. It considers various factors that affect the requirement for supervision and formulates them into an analytical model which aims at optimizing the organizational design. This decision includes allocation tasks to workers, considering complexity and compatibility of each task with respect to workers, and the requirement of management for planning, execution, training and control in a hierarchical organization. The model is formulated as a 0-1 mixed integer program. The objective of the model is minimum operational cost, which are the sum of supervision costs at each level of the hierarchy and the number of workers assigned with tasks. This model addresses the span of control problem and provides a quantitative approach to the organization design problem and is intended for applications as a design tool in the make-to-order industries. Each project-based company may have to frequently readjust its organizational structure, as its capability and capacity shifts over time. It could also be applied to functionality based companies as an evaluation tool, to assess the optimality of their current organization structure. Meier and Bohte (Meier & Bohte, 2003) have recently reinvigorated the debate on span of control and the optimal manager-subordinate relationship. They offer a theory concerning the impacts and determinants of span of control and test it using data from educational organizations. The findings of Theobald et al. (Theobald & Nicholson-Crotty, S., 2005) suggest that manager-subordinates ratios, along with other structural influences on production, deserve considerably more attention than they have received in modern research on administration.

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International Journal of Industrial Engineering, 19(4), 193-203, 2012.

A NON-TRADITIONAL CAPITAL INVESTMENT CRITERIA-BASED METHOD TO OPTIMIZE A PORTFOLIO OF INVESTMENTS Joana Siqueira de Souza1, Francisco José Kliemann Neto2, Michel José Anzanello3, Tiago Pascoal Filomena4 Assistant Professor, Engineering School - Pontifícia Universidade Catolica of Rio Grande do Sul, Av. Ipiranga, 6681 Partenon - 90619-900, Porto Alegre, RS, Brazil. 2 Associate Professor, Department of Industrial and Transportation Engineering, Federal University of Rio Grande do Sul – PPGEP/UFRGS. Av. Osvaldo Aranha, 99, 90035-190, Porto Alegre, RS, Brazil. 3 Assistant Professor, Department of Industrial and Transportation Engineering, Federal University of Rio Grande do Sul – PPGEP/UFRGS. Av. Osvaldo Aranha, 99, 90035-190, Porto Alegre, RS, Brazil. 4 Assistant Professor, School Business, Federal University of Rio Grande do Sul – Rua Washington Luiz, 855. Centro, 90010-460. Porto Alegre, RS, Brazil. 1

During the capital budgeting, companies need to define a set of projects that bring profitability, perpetuity and also have a direct link with the strategic objectives. This paper presents a practical model for defining a portfolio of industrial investments during capital budgeting by making use of traditional methods of investment analysis, such as Net Present Value (NPV), and by incorporating qualitative attributes on the analysis through the multicriteria analysis method called Non-Traditional Capital Investment Criteria (Boucher and MacStravic, 1991). Optimization techniques are then used to integrate economic and qualitative attributes subjected to budget restrictions. The proposed model was validated in an automotive company. Keywords: project portfolio, capital budgeting, net present value, multicriteria analysis, linear programming, decisionmaking. (Received 31 Aug 2010; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION The definition of a portfolio of projects in capital budgeting appears as an important issue in investment decisions and industrial planning (Chou et al. 2001). Decisions are seldom made for an isolated project; in most situations, the decision maker needs to consider several alternative projects relying on particular variables (Borgonovo and Peccati, 2006) associated not only to financial resources, but also to internal and external factors to the company (Kooros and Mcmanis, 1998; Mortensen et al. 2008). Although a large number of robust approaches related to investment decisions have been suggested in the literature, simplistic methods for evaluating investments are still widely used, and little structured decision making is applied in portfolio definition. Many assessment methods use discounted cash flow techniques such as the Internal Rate of Return (IRR), Net Present Value (NPV) and the Profitability Index (PI) (Cooper et al. 1997). More sophisticated methods can increase the likelihood of solid investments due to a stronger connection to company's strategy, leading to a more consistent analysis of opportunities (Verbeeten, 2006). Although many of these methods are appropriate for investment evaluation, Jansen et al. (2004) state they only enable tactical allocation of capital, and seldom take qualitative aspects into consideration (e.g. strategic aspects). That is corroborated by Arnold and Hatzopoulos (2000) who found that many firms invest their capital in non-economic projects (i.e. projects that do not necessarily bring economic benefits to the company), such as projects driven to workers’ health and safety. One way to incorporate qualitative aspects on decision-making process for capital investment is the adoption of multicriteria techniques, also known as Multiple Criteria Decision Making (MCDM) methods. A widespread method is the MAUT - Multiattribute Utility Theory - which relies on a simple and easy method for ranking the alternatives; see Min (1994). Another popular method is the Analytical Hierarchy Process (AHP), which hierarchically accommodates both quantitative and qualitative attributes of complex decisions (Saaty, 1980; Vaidya and Kumar, 2006). Successful applications of AHP can be found in Fogliatto and Guimarães (2004), Rabbani et al. (2005), Vaidya and Kumar (2006), and Mendoza et al. (2008). A drawback of AHP is that it accommodates economic and qualitative aspects in different matrices, and also requires the comparison of all the alternatives over the same criteria. That is undesired when working with investment projects, since not all projects impact upon the same criteria. For example, a project to renew a truck fleet may have an impact on workers’ ergonomic condition, while a training project might not impact on that criterion. That led Boucher and MacStravic (1991) to develop an AHP-based multicriteria method for investment decision: the Non-Traditional Capital Investment Criteria (NCIC). ISSN 1943-670X

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International Journal of Industrial Engineering, 19(4), 204-212, 2012.

AN ANALYTICAL APPROACH OF SENSITIVITY ANALYSIS FOR EOQ Hui-Ming Teng1,2, Yufang Chiu1, Ping-Hui Hsu1,3, Hui Ming Wee1* 1

Department of Industrial and Systems Engineering, Chung Yuan Christian University, Chungli, Taiwan

2

Department of Business Administration, Chihlee Institute of Technology, Panchiao, Taipei, Taiwan

3

Department of Business Administration, De Lin Institute of Technology, Tu-Cheng, Taipei, Taiwan Corresponding author:*E-mail: [email protected]

This study develops an analytical sensitivity analysis approach for a traditional economic order quantity (EOQ) model. The parameters are treated as variables and a direction for deriving the optimal solution is developed using the gradient approach. The graph of the optimal solution is provided to demonstrate the sensitivity analysis. Numerical example is provided to illustrate the theory.

Keywords: Economic order quantity (EOQ); Sensitivity analysis; Gradient; Sub-gradient.

(Received 28 Apr 2010; Accepted in revised form 27 Feb 2012)

1. INTRODUCTION Researches on inventory problems are usually summarized by sensitivity analysis (Koh et al., 2002; Weng and McClurg, 2003; Sarker and Kindi, 2006; Ji et al., 2008; Savsar and Abdulmalek,2008; Patel et al., 2009; Hsu et al., 2010). The traditional methodology to investigate the impact of parameters sensitivities is done by evaluating the target value based on varying parameters. Although the performance of traditional methodology is good enough, however, its graphs precision is limited. This is mainly caused by its inability to express the discrete property completely. Ray and Sahu (1992) provided the details of sensitivity analysis factors in productivity measurement for multi-product manufacturing firms. Borgonovo and Peccati (2007) applied Sobol’s function and variance decomposition method to determine the most influential parameters on the model output. Borgonovo(2010) introduced a new method to define sensitivity measurement that do not need differential equations for sensitivity analysis. Lee and Olson presented a nonlinear goal programming algorithm based on the gradient method, utilizing an optimal step length for chance constrained goal programming models. Arsham (2007) developed a full gradient method which consists of three phases: initialization, push and final iteration phase. The initialization phase provided initial tableau which may not have a full set of basis. The push phase used a full gradient vector of the objective function to obtain a feasible vertex. The final iteration phase used a series of pivotal steps using sub-gradient, which leads to an optimal solution. For each iteration, the sub-gradient provides the desired direction of motion within the feasible region. In this study, sensitivity analysis based on the traditional economic order quantity (EOQ) model is discussed. A numerical example is provided to illustrate the theory.

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International Journal of Industrial Engineering, 19(5), 213-220, 2012.

PRODUCTION LEAD TIME VARIABILITY SIMULATION – INSIGHTS FROM A CASE STUDY Gandolf R. Finke1, Mahender Singh2, Prof. Dr. Paul Schönsleben1 BWI Center for Industrial Management, ETH Zurich, Kreuzplatz 5, 8032 Zurich, Switzerland 2 Malaysia Institute for Supply Chain Innovation, No. 2A, Persiaran Tebar Layar, Seksyen U8, Bukit Jelutong, Shah Alam, 40150 Selangor, Malaysia 1

We study the impact of disruptions to operations that can cause deviations in the individual processing time of a task, resulting in longer than planned production lead time. Quality, availability of capacity and required material as well as variability in process times are regarded as drivers of disruption. The focus is to study the impact of variability in the lead time on the overall performance of the production system, instead of the average lead time. Structural and numerical application of the approach are provided in a case study. Additionally, the different dimensions of practical implications of this research are accentuated. Accordingly, discrete event simulation is used to study the interactions and draw insights based on a case study. Measures to mitigate lead time variability are discussed and their impact is analyzed quantitatively. Keywords:

Operations management, Production planning, Simulation, Lead time, Variability, Reliability (Received 15 Nov 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION 1.1 Motivation Production lead time is a critical driver of process design in a manufacturing company. The concept of time-based competition stresses the importance of lead times as a competitive advantage and strategic instrument. Shorter lead times are not only advisable in terms of meeting customer demand and the ability to adapt but also to minimize cost by reducing inventories and work in progress. As a result, cycle time reduction efforts have garnered a lot of attention in the literature and industry initiatives. Although a lower lead time is a worthwhile endeavor, how it is reduced is the all-important decision. Traditionally, these decisions involve weighing the benefits of the reduction in the average cycle time with the investment required to achieve the targeted improvement. Little or no attention is paid to the variability in cycle times, however. We will use the terms variability and reliability to address the same issue in this paper. Through this research we intend to highlight the need for a formal consideration of the cycle time reliability when implementing measures for lead time reduction. Although seemingly simple, understanding the system level impact of individual task variability is not straightforward. Whereas the averages are additive and thus simple to study, the variability is not. We take a simple example from the reliability domain to illustrate this point. Consider a system that has 20 components, with each one performing at a high level of 98% reliability individually. Collectively, assuming independence, the reliability of this system is only 65%! This deteriorates further to near 50% if we add 10 more components! The key point here is that we need to assess reliability in a holistic manner as individual task processing time variability tends to amplify as it travels through an interconnected production sequence. In short, a high level of local reliability does not necessarily imply a high level of global reliability. A deeper understanding of the true system level reliability will motivate the need for redundancy at strategic locations throughout the system to improve the overall performance. It may in certain situations be more beneficial to have reliable delivery with longer average lead time, that is minimum or no lead time deviation, than enforcing a shorter average lead time that is less reliable. This type of analysis will enhance the selection criterion when multiple investment options to reduce lead time are possible since reliability has direct and indirect cost consequences. 1.2 Classification of disruptions and scope We classify potential disruptions encountered by a typical manufacturing company into two categories. The first category, which we call systemic disruptions, covers all factors that affect large portions of a company or the supply chain simultaneously, for example earthquakes, floods, wars or strikes. The second category is described as operational disruptions. These include drivers that influence a company’s performance at a micro scale, i.e., individual steps in production sequence for instance, failed quality tests, variability in the completion time of single production steps and production resource breakdown. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(5), 221-231, 2012.  

A COMPUTER SIMULATION MODEL TO REDUCE PATIENT LENGTH OF STAY AND TO IMPROVE RESOURCE UTILIZATION RATE IN AN EMERGENCY DEPARTMENT SERVICE SYSTEM Muhammet Gul1, Ali Fuat Guneri2 1 Industrial Engineering Department Faculty of Engineering Tunceli University 62000, Tunceli 2 Industrial Engineering Department Mechanical Faculty Yıldız Technical University Yıldız, Beşiktaş, İstanbul [email protected] Corresponding author’s e-mail: {Muhammet Gul, [email protected]} This paper presents a case study of a discrete-event simulation (DES) model of an emergency department (ED) unit in a regional university hospital in Turkey. In this paper emergency department operations of the hospital were modeled, analyzed and improved. The goal of the study is to reduce patient average length of stay (LOS) and to improve patient throughput and utilization of locations and human resources (doctors, nurses, receptionists). Some alternative scenarios in an attempt to determine optimal staff level were evaluated. These alternative approaches illustrate that vital improvement in LOS and throughput can be obtained by minor changes in shift hours and number of resources. Considering future changes in patient demand a scenario which reduces LOS and improves throughput is available in the paper. Significance: The Key Performance Indicators (KPIs) to determine and improve system performance in healthcare emergency departments consist of to reduce patient average length of stay (LOS), to improve patient throughput and resource utilization rates. Alternative scenarios and optimal staff levels are enhanced within the scope of this study. Keywords: Emergency departments, healthcare modeling, discrete event simulation, length of stay, Servicemodel (Received 8 Mar 2012; Accepted in revised form 31 Mar 2012)

1. INTRODUCTION Emergency departments (EDs) in which people consult due to many complaints and demand first medical response have vital importance in healthcare systems. Today improvements in healthcare lead to an increase in number of tools and methods. During recent years utilization of emergency department units in Turkey has heavy increased because of fast and cheap treatment opportunities. Statistics about the consultations to healthcare institutions show that number of arrivals at emergency departments have increased recently (Arslanhan, 2010). It is objected decreasing the waiting times that improve performance of the operations in healthcare sector. McGuire (1994) evaluated alternatives to reduce waiting times of ED patients using Medmodel. He managed to reduce LOS from 157 minutes to 107 minutes. Kirtland et al. (1995) provided an improvement of 38 minutes as combination of optimal solutions. Performance measures obtained from simulation applications in EDs are to reduce patient length of stay (LOS), to improve patient throughput, to increase resource utilization rate and to control costs. Evans et al. (1996) described an Arena simulation model for the emergency department of a particular hospital in Kentucky. In the model patient flows of 13 different types of patients were simulated. Also different feasible schedules for doctors, nurses and technicians were evaluated. Main performance measure used in the process was average patient length of stay in emergency department. Model was run 50 replications and patient LOS was found as 142 minutes. Patvivatsiri at al. (2003) evaluated a reducing of %45 in patients’ average waiting times with an affective nurse schedule. Simulation enables how changes system performance based on several factors (Tekkanat, 2007). In EDs, operation times, arrival rates of entities, costs and utilization of resources are given as example to these factors. Discrete Event Simulation (DES) techniques have been used a lot for modeling the operations of an emergency department and for the analysis of patient flows and throughput time (Samaha et al., 2003; Mahapatra et al., 2003; Takakuwa and Shiozaki, 2004). Samaha et al. (2003) evaluated some alternatives to decrease patient length of stay in system with 24 hours and a week data obtained from ED using Arena simulation software. Mahapatra et al. (2003) aimed to develop a reliable decision support system (DSS) using Emergency Severity Index (ESI) triage method which optimizes resource utilization rate. According to three ISSN  1943-­‐670X                                                                                                                                                                                                    ©  INTERNATIONAL  JOURNAL  OF  INDUSTRIAL  ENGINEERING  

International Journal of Industrial Engineering, 19(5), 232-240, 2012.

AN EPQ MODEL WITH VARIABLE HOLDING COST Hesham K. Alfares Systems Engineering Department, King Fahd University of Petroleum & Minerals, Dhahran 31261, Saudi Arabia. Email: [email protected] Instantaneous order replenishment and constant holding cost are two fundamental assumptions of the economic order quantity (EOQ) model. This paper presents modifications to both of these basic assumptions. First, non-instantaneous order replenishment is assumed, i.e. a finite production rate of the economic production quantity (EPQ) model is considered. Second, the holding cost per unit per time period is assumed to vary according to the length of the storage duration. Two types of holding cost variability with longer storage times are considered: retroactive increase and incremental increase. For both cases, models are formulated, solutions algorithms are developed, and examples are solved. Keywords: Economic production quantity (EPQ), Variable holding cost, Production-inventory models. (Received 13 Apr 2011; Accepted in revised form 28 Oct 2011)

1. INTRODUCTION In the classical economic order quantity (EOQ) model, the replenishment of the order is assumed to be instantaneous, i.e. the production rate is implicitly assumed infinite. In practice, many orders are manufactured gradually, at a finite rate of production. Even if the orders are purchased, the procurement and receipt of these orders is seldom instantaneous. Therefore, economic production/manufacturing quantity (EPQ/EMQ) models are more representative of real life. Moreover, the assumption of a constant holding cost for the entire duration of storage may not be always realistic. In many practical situations, such as in the storage of perishable items, longer storage periods require additional specialized equipment and facilities, resulting in higher holding costs. This paper presents an EPQ inventory model with a finite production rate and a variable holding cost. In this model, the holding cost is assumed to be an increasing step function of the storage duration. Two types of time-dependent holding cost functions are considered: retroactive increase, and incremental increase. Retroactive holding cost increase means that the holding cost of the last storage period applies to all previous storage periods. Incremental holding cost increase means that increasingly higher holding costs apply only to later storage periods. For each of these two types, optimal solutions algorithms are developed to minimize the total cost per unit time. Several EOQ and EPQ models with variable holding costs proposed in the literature consider holding cost to be a function of the amount or value of inventory. Only few EOQ-type models assume the holding cost to vary in relation to the inventory level. Muhlemann and Valtis-Spanopoulos (1980) revise the classical EOQ formula, assuming the holding cost to be an increasing function of the average inventory value. Their justification is that the greater the value of inventory, the higher the cost of financing it. Mao and Xiao (2009) construct an EOQ model for deteriorating items with complete backlogging, considering the holding cost as a function of the on-hand inventory. A solution procedure is developed, and the conditions are specified for the existence and uniqueness of the optimal solution when the total holding cost function is convex. Moon et al. (2008) develop mixed integer programming models and genetic algorithm heuristic solutions to minimize the maximum EOQ storage space requirement for both finite and infinite time horizons. Some inventory models have built-in flexibility, allowing the holding to be a function of either the inventory level or storage time. Goh (1994) considers an EOQ-type single-item inventory system with a stock-dependent demand rate and variable holding cost. Giri and Chaudhuri (1998) construct an EOQ-type inventory model for a perishable product with stock-dependent demand and variable holding cost. Considering two types of variation of the holding cost per unit, both Goh (1994) and Giri and Chaudhuri (1998) treat holding cost either as: (i) a non-linear continuous function of the time in storage, or (i) a non-linear continuous function of the amount of inventory. In several EOQ-type models, the holding cost is assumed to be a continuous function of storage time. For a non-linearly deteriorating item, Weiss (1982) considers the holding cost per unit as a non-linear function of the length of storage duration. Optimal order quantities are derived for deterministic and stochastic demands, and for both finite and infinite time horizons. Giri at al. (1996) develop a generalized EOQ model for deteriorating items with shortages, in which both the demand rate and the holding cost are continuous functions of time. The optimal inventory policy is derived assuming a finite planning horizon and constant replenishment cycles. Ferguson et al. (2007) apply Weiss (1982) formulas to approximate optimal order quantities for grocery store perishable goods, using regression to estimate the holding cost curve parameters. Alfares (2007) introduces the notion of holding cost variability as a discontinuous step function of storage time, with two types of holding cost increase. As the storage time extends to the next time period, the new (higher) holding cost can be ISSN 1943-670X

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International Journal of Industrial Engineering, 19(6), 241-251, 2012.

A MULTI-HIERARCHY GREY RELATIONAL ANALYSIS MODEL FOR NATURAL GAS PIPELINE OPERATION SCHEMES COMPREHENSIVE EVALUATION 1

Chang Jun Li1, Wen Long Jia2, En Bin Liu2, Xia Wu2 Oil and Gas Storage and Transportation Engineering Institute of Southwest Petroleum University 2 Southwest Petroleum University

In the condition of satisfying process requirement, determining the optimum operation schemes of natural gas pipeline network is essential to improve the overall efficiency of network operation. According to the operation parameters of natural gas network, the multi-hierarchy comprehensive evaluation index system is illustrated, and the weights of each index are determined with an improved Analytic Hierarchy Process (AHP). This paper presents a multi-hierarchy grey relational analysis (GRA) method which is suitable for evaluating the multi-hierarchy index system with combining the AHP and grey relational analysis. Ultimately, the industrial application shows that multi hierarchy grey relational analysis is effective to evaluate the nature gas pipeline network operation schemes. Significance： This paper presents a multi-hierarchy grey relational analysis model for natural gas operation schemes comprehensive evaluation with the combination of AHP and traditional GRA. The method is applied to the Sebei-Ningxia-Lanzhou gas transmission pipeline successfully. Keywords:

Natural gas pipeline network; Operation schemes; Analytic Hierarchy Process; Grey relational analysis; Comprehensive evaluation (Received 27 Jul 2011; Accepted in revised form 2 Jan 2012)

1. INTRODUCTION     Gas transmission and distribution pipelines play an important role in the development and utilization of natural gas. The network operators can formulate many different schemes in the condition of satisfying process requirement. However, the overall goal of operators is quality, quantity and timely supply of gas and best economic as well as the social benefit. Thus, select the optimum scheme from many reasonable options to improve the economic returns and social benefits of pipeline operation is a problem deserving of study. The operation scheme of natural gas pipeline network is close related to the flow rate, temperature, and pressure at each node in the network. As it involves too many parameters, it is almost impossible to list all the relevant and determine the relationship among them. The traditional probability theory and mathematical methods are used to solve problems with uncertainty characterized by large sample sizes and multi-data. Consequently, it is not suitable for evaluating the network operation schemes. However, grey relational analysis is proposed to solve uncertainty problems with less available data and experiences, small sample sizes and incomplete information. Its main principle is contained in the grey relational analysis model. This analysis method establishes an overall comparative mechanism, overcomes the limitation of pair-wise comparison, and avoids conflicting conditions between serialized and qualitative results (Tong and Wang, 2003, Chi and Hsu, 2005). This method has been widely used in the area of oil and gas pipeline optimum designing and comprehensive evaluation (Liang and Zhen 2004; Zhao 2007) since Professor Wang (Wang, 1993) introduced this method into the optimum designing of natural gas pipeline in 1993. But the index system of objects evaluated is only one layer. This paper builds the multi-hierarchy comprehensive evaluation index system for natural gas network and calculates their weights firstly. Then the multi-hierarchy grey relational analysis method is presented by the combining of the calculating method of AHP and traditional grey relational analysis method. Ultimately, this paper evaluates seven different operation schemes of a natural gas network using the method presented. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(6), 252-263, 2012.

OPTIMAL FLEET SIZE, DELIVERY ROUTES, AND WORKFORCE ASSIGNMENTS FOR THE VEHICLE ROUTING PROBLEM WITH MANUAL MATERIALS HANDLING Prachya Boonprasurt and Suebsak Nanthavanij Engineering Management Program Sirindhorn International Institute of Technology, Thammasat University Pathumthani 12121, Thailand Corresponding author’s e-mail: {Suebsak Nanthavanij, [email protected]} The vehicle routing problem with manual materials handling (VRPMMH) is introduced. At customer locations, delivery workers must manually unload goods from the vehicle and take them to the stockroom. The delivery activities require workers to expend certain amounts of physical energy. In this paper, two models of VRPMMH are developed, namely VRPMMH models with fixed workforce assignments (FXW) and with flexible workforce assignments (FLW). The objective of both VRPMMH models is to determine optimal fleet size and delivery routes such that the total cost is minimized. Additionally, the second model is intended to assign delivery workers to vehicles to minimize the differences in physical workload. Significance:

The results obtained from the vehicle routing problem with manual materials handling (VRPMMH) can help goods suppliers to obtain a delivery solution that not only is economical but also safe for delivery workers. By adding the workload constraint into consideration, the solution will prevent the delivery workers from performing daily physical work beyond the recommended limit.

Keywords:

Vehicle routing problem, workforce assignment, manual materials handling, optimization, ergonomics (Received 9 May 2010; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Danzig and Ramser (1959) firstly introduced the capacitated vehicle routing problem (VRP) several decades ago. Since then, VRP has been studied extensively by researchers. In the classical capacitated VRP, goods are delivered from a depot to a set of customers using a set of identical delivery vehicles. Each customer demands a certain quantity of goods and the delivery vehicles have a limited capacity. Typically, the problem objective is to find delivery routes starting and ending at the depot that minimize a total travel distance without violating the capacity constraint of the delivery vehicles. In some problems, the objective might be to determine the minimum number of delivery vehicles to serve all customers. There are many variants of VRP such as the vehicle routing problem with backhauls (VRPB), the pickup and delivery problem with time windows (VRPTW), the mixed vehicle routing problem with backhauls (MVRPB), the multiple depot mixed vehicle routing problem with backhauls (MDMVRPB), the vehicle routing problem with backhauls and time windows (VRPBTW), the mixed vehicle routing problem with backhauls and time windows (MVRPBTW), and the vehicle routing problem with simultaneous deliveries and pickups (VRPSDP) (Ropke and Pisinger, 2006). The classical VRP including its variants are combinatorial optimization problems. Both exact and heuristic methods have been developed to obtain the problem solution. For example, consider the vehicle routing problem with simultaneous delivery and pickup (VRPSDP) (Min, 1989). Halse (1992) presented exact and heuristic methods for the problem and Dethloff (2001, 2002) considered heuristic algorithms. Additionally, simulation and meta-heuristic approaches have also been employed to investigate the VRP. Park and Hong (2003) evaluated the system performance of the vehicle routing problem under a stochastic environment using four heuristics. They considered the VRP with time window constraints where traveling time and service quantity vary. Ting and Huang (2005) used a genetic algorithm with elitism strategy (GAE) to solve the VRP with time windows. They reported that their GAE are superior to the other three GAs tested in their study in terms of the total traveling distance. Virtually all VRPs do not consider ergonomics in the problem formulation. Consider the situation in which goods must be manually moved from the vehicle to an assigned location at the customer point. This situation is not unusual especially for short-distance deliveries within the city area using small delivery vehicles. An example is the delivery of goods from a distribution center to convenience stores which are scattered around the city. The delivered supplies are manually unloaded from the vehicle and then moved to the stockroom. These convenience stores do not usually keep large inventories. In fact, they rely on receiving supplies from the distribution center on a daily basis. Another example is the delivery of ISSN 1943-670X

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International Journal of Industrial Engineering, 19(6), 264-277, 2012.  

A QUANTITATIVE PERFORMANCE EVALUATION MODEL BASED ON A JOB SATISFACTION-PERFORMANCE MATRIX AND APPLICATION IN A MANUFACTURING COMPANY Adnan Aktepe, Suleyman Ersoz Department of Industrial Engineering, Kirikkale University, Turkey In this study, we propose a performance management model based on employee performance evaluations. Employees are clustered into 4 different groups according to a job satisfaction-performance model and strategic plans are derived for each group for an effective performance management. The sustainability of this business process improvement model is managed with a control mechanism as a Plan-Do-Check-Act (PDCA) cycle as a continuous improvement methodology. The grouping model is developed with a data mining clustering algorithm. Firstly 4 different performance groups are determined with a two-step k-means clustering approach. Then the clustering model developed is testified with an Artificial Neural Network (ANN) model. Necessary data for this study are collected with a questionnaire application composed of 25 questions, first 13 variables measuring job satisfaction level and last 12 variables measuring performance characteristics where evaluators are employees themselves. With the help of model developed, human resources department is able to track employees’ job satisfaction and performance levels and strategies for different performance groups are developed. Application of the model is conducted in a manufacturing company located in Istanbul, Turkey. Keywords: Job Satisfaction-Performance Matrix, K-Means Clustering, Performance Management, Employee Performance Evaluation, Job Satisfaction. (Received 12 Aug 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Fast developing new technologies and changing world had made competitive market conditions harsh. Staying competitive in the market, which is inevitable for organizations to survive, is possible with the efficient use of resources. While traditional organizations directed their efforts only on increasing profitability and being financially strong, now non-traditional organizations analyze the input-output interaction of resources to find reasons of low or high profitability. Today factors affecting financial and non-financial performance of the company are analyzed in detail. Being financially strong for the moment does not guarantee a long-running organization. In order to see the whole picture organizations have started to change their strategies according to performance management systems. Today mostly used performance management systems are Deming Prize Model developed in Japan in 1951, Malcolm Baldridge Quality Award Model developed in the U.S.A. in 1987, American Productivity Centre Model, EFQM Excellence Model, Performance Pyramid developed by Lynch ve Cross (1991), Balanced Scorecard developed by Kaplan and Norton (1992), Quantum Performance Management Model developed by Hronec (1993), Performance Pyramid by Neely and Adams (2001), Neely et al. (2002) and Skandia Navigator model. The very first systematic studies on performance started in the beginning of 20th century. Taylor (1911) in his book “Principles of Scientific Management” discussed productivity, efficiency, optimization and proposed novel techniques on increasing productivity. After that he proposed a performance based salary system for employees but this idea was intensely criticized at that time although today many organizations use this system. Then research on employee performance was triggered. It was found that ergonomic factors affect performance. Besides ergonomic factors Mayo (1933, 1949) and his friends proved that, with experiments conducted at Hawthorne, employee performance is much more affected by behavioral factors. He demonstrated that teamwork, motivation and human affairs much more affect individual performance. There is an abundance of empirical studies on relationship among job performance, job satisfaction and other factors in the literature (Saari and Judge, 2004; Shahu and Gole, 2008; Pugno and Depedri, 2009). The performance model used in this study, of which details given in the next section, groups employees according to both performance and job satisfaction levels. So here we analyze the relationship between them and present a literature review on job satisfaction, performance and other factors’ relationships. Other factors affecting job performance and job satisfaction include stress, organizational commitment, employee attitudes, employee morale, etc. Several authors in the literature studied the effect of job satisfaction and other factors on performance. In Table 1 we give a list of studies carried out on relations among job satisfaction, performance and other factors. However, there exists a controversial debate on the relationship among job satisfaction, performance and other factors. The satisfactory performance model used in this study enables us to look from a different point of view. Without considering the relationships among performance and related factors, in this model employees are grouped according to job satisfaction and performance. This helps us to develop a new approach to individual performance appraisals. If we summarize the performance factors addressed in the literature, we see the relationship diagram given in Figure 1. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(7), 278-288, 2012.

AN INTRODUCTION TO DISTRIBUTION OPERATIONAL EFFICIENCY Bernardo Villareal, Fabiola Garza, Imelda Rosas, David Garcia Department of Engineering, Universidad de Monterrey Department of Business, Universidad de Monterrey

The Lean Manufacturing approach for waste elimination can be applied in all sorts of operations. In this project is applied for the improvement of a supply chain and to achieve high levels of chain efficiency. The identification of warehousing and transportation waste at the chain level is aggregate being difficult its identification within both processes. This work provides an introduction to the concept of distribution operational efficiency and proposes a scheme for eliminating waste in a distribution operation. The Operational Effectiveness Index used in TPM is adapted and used as the main performance measure. Availability, performance and quality wastes are identified using Value Stream Mapping. The scheme is exemplified by applying it on distribution networks of several Mexican companies. Keywords: Lean warehousing, Lean transportation, distribution waste, operational effectiveness index, supply chain efficiency. (Received 8 Sep 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION A key feature of business is the idea that competition is made through supply chains and not between the companies (Christopher, 1992), success or failure of supply chains is ultimately determined in the market-place by the end consumer.   Therefore, is extremely important the deployment of the right strategies to compete successfully. Fisher (1997) suggests that supply chains must acquire capabilities to become efficient or agile accordingly to the type of products marketed (see Figure 1). In particular, an efficient supply chain is suitable for selling functional products. The order winning factor in this market is cost, having quality, lead time and service level as order qualifiers (Hill, 1993). The main supply chain strategy recommended to become efficient is waste elimination (Towill et al., 2002). The origin of waste elimination is associated with the concept of lean manufacturing. This can be traced back to the 1930´s when Henry Ford revolutionised car manufacturing with the introduction of mass production. The most important contribution to the development of lean manufacturing techniques since then came from the Japanese automotive firm Toyota. Its success is based on its renowned Toyota Production System. This system is based on a philosophy of continuous improvement where the elimination of waste is fundamental. The process of elimination is facilitated by the definition of seven forms of waste, activities that add cost but no value: production of goods not yet ordered; waiting; rectification of mistakes; excess processing; excess movement; excess transport; and excess stock. Jones et al., (1997) have shown that these seven types of waste need to be adapted for the supply chain environment. Hines and Taylor (2000) propose a methodology extending the lean approach to enable waste elimination throughout the supply chain and Rother et al., (1999) recommend the use of the value stream map (VSM) and the supply chain mapping toolkit described by Hines et al., (2000) as fundamental aids for identifying waste. As lean expands towards supply chain management, rises the question about its adequate adaptation. Transportation and warehousing represent good opportunities for the application and could give important benefits if applied properly. It is well known that both activities are classified as waste. However, when markets are distant, these are certainly necessary activities to attain competitive customer service levels. Most distribution networks have significant waste and unnecessary costs say McKinnon et al., (2003) and Ackermann (2007). For the identification of waste between facilities and installations in a supply chain Jones et al., (2003) recommend Value Stream Mapping for the extended enterprise. When mapping at the supply chain level, unnecessary inventories and transportation become important wastes. Unnecessary transportation waste is related to location decisions for the improvement of performance at given points of the supply chain. Therefore, the solutions suggested for its elimination are concerned with the relocation and consolidation of facilities, a change of transportation mode or the implementation of milk runs. In addition to transportation, warehousing is another important part of a distribution network. Value stream mapping at the supply chain level emphasizes on the identification of inventory waste. This approach does not consider the elimination of waste in warehousing operations. However, it is important to realize that warehousing could have an important impact on the supply chain cost structure and on the capacity to respond to customer needs. Lean transportation and warehousing are still new areas in full development.

ISSN 1943-670X

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International Journal of Industrial Engineering, 19(7), 289-296, 2012.

ALTERNATIVE CONSTRUCTIVE HEURISTIC ALGORITHM FOR PERMUTATION FLOW-SHOP SCHEDULING PROBLEM WITH MAKESPAN CRITERION Vladimír Modrák, Pavol Semančo and Peter Knuth Faculty of Manufacturing Technologies, TUKE, Bayerova, 1, Presov, Slovakia Corresponding author email: [email protected] In this paper, a constructive heuristic algorithm is presented to solve deterministic flow-shop scheduling problem with make-span criterion. The algorithm is addressed to an m-machine and n-job permutation flow shop scheduling problem. This paper is composed in a way that the different scheduling approaches to solve flow shop scheduling problems are benchmarked. In order to compare the proposed algorithm against the benchmarked, selected heuristic techniques and genetic algorithm have been used. Results of experiments show that proposed algorithm gives better or at least comparable solutions than benchmarked constructive heuristic techniques. Finally, the average computational times (CPU time in ms) are compared for each size of the problem. Keywords: make-span, constructive heuristics, genetic algorithm, CPU time

(Received 13 Mar 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Dispatching rules are one of the most common application areas of heuristic methods used for factory scheduling (Caskey, 2001). Basic types, job shop and flow shop production, cope with a scheduling problem to find a feasible sequence of jobs on given machines with the objective of optimization of some specific function. A selected criterion for purpose of this study - job completion time (make-span) can be defined as the time span from material availability at the first processing operation to the completion at the last operation. Johnson (1954) has shown that, in a 2-machines flow shop, an optimal sequence can be constructed. It was determined that machine flow shop scheduling problem (FSSP) is strongly NP-hard for m ≥3 (Garey et al., 1976). FSSPs can be divided into two main categories: dynamic and static. Hejazi and Saghafian (2005) characterize scheduling problem as an effort „to specify the order and timing of the processing of the jobs on machines, with an objective or objectives respecting above-mentioned assumptions“. This paper is concerned with multi machine FSSP that present a class of Group Shop Scheduling Problems. The criterion of optimality in a flow shop sequencing problem is usually specified as minimization of make-span. If there are no release times for the jobs then the total completion time equals the total flow time. Maximum criteria should be used when interest is focused on the whole system (Mokotoff, 2011). Pan and Chen (2004) studied the re-entrant flow-shop (RFS) with the objective of minimizing the makespan (Cmax) and average flow time of jobs by proposing optimization models based on integer programming technique and heuristic procedure. In addition, they treated new dispatching rules to accommodate the reentry feature. In a RFS, all jobs have the same routing over the machines of the shop and the same sequence is traversed several times to complete the jobs. Chen at al (2009) presented study on hybrid genetic algorithm to solve RFS scheduling problem with the aim to improve the Genetic Algorithm (GA) performance and the heuristic methods proposed by Pan a Chen (2004). In some cases for calculating the completion times specific constraints are assumed. For example, such a situation in the FSSP arises when no idle time is allowed at machines. This constraint creates an important practical situation that arises when expensive machinery is employed (Chakraborty, 2009). The general scheduling problem for a classical shop flow gives rise to (n!)m possible schedules. With aim to reduce the number of possible schedules it is reasonable to make assumption that all machines process jobs in the same order (Gupta 1975). In the classical flow-shop scheduling problem, queues of jobs are allowed at any of m machines in processing sequence based on assumption that jobs may wait on or between the machines (Allahverdi et al., 1999, 2008). Moreover setup times are not considered for calculating make-span parameter. The currently reported approximation algorithms can be categorized into two types: constructive methods or improvement methods. Constructive methods include Slope index based heuristics, CDS heuristics and others. Most of improvement approaches are based on modern meta-heuristics, such as Simulated Annealing, Tabu Search, Genetic Algorithm and others. Modern meta-heuristic algorithms can be easily applied to various FSPs and usually by them are obtained better solution than by constructive methods. However, Kalczynski and Kamburowski (2005) showed that many meta-heuristic ISSN 1943-670X

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International Journal of Industrial Engineering, 19(7), 297-304, 2012.

MEDIA MIX DECISION SUPPORT FOR SCHOOLS BASED ON ANALYTIC NETWORK PROCESS 1*

1

2

3

1

Shu-Hsuan Chang , Tsung-Chih Wu , Hwai-En Tseng , Yu-Jui Su , and Chen-Chen Ko Department of Industrial Education and Technology, National Changhua University of Education No. 2, Shida Rd., Changhua City 500, Taiwan, ROC 2 Department of Industrial Engineering and Management, National Chin-Yi University of Technology, 35, Lane215, Section 1, Chung-Shan Road, Taiping City, Taichung County 411, Taiwan, ROC 3 Asia-Pacific Institute of Creativity, No.110.Syuefu Rd. Toufen Township.Miaoli County 351.Taiwan, ROC *Corresponding author: Shu-Hsuan Chang, [email protected] 1

Media Selection is a multi criteria decision making (MCDM) problem. Decision makers with budget constraints should select media vehicles with the greatest effects on audiences by simultaneously considering multiple and interdependent evaluation criteria. This work develops a systematic decision support algorithm for media selection. Analytic Network Process (ANP) is adopted to determine the relative weights of criteria. An Integer Programming (IP) is then applied to (identify the optimum combination of media below a fixed budget. An empirical example demonstrates the computational process and effectiveness of the proposed model. Significance:

The decision model aims to develop a systematic decision support hybrid algorithm to solve the best media mix for student recruiting advertisement with budget constraints by simultaneously considering multiple and interdependent evaluation criteria. An empirical example of media selection for school C is demonstrates the computational process and effectiveness of the proposed model.

Keywords: MCDM, Media Selection, Analytic Network Process (ANP), Integer Programming (IP) (Received 9 Sep 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Consumers have benefited from the revolutionary growth in the number of TV and radio channels, magazines, newspapers and outdoor media in recent decades. However, the time devoted to a single medium constantly shrinks, and the complexity of the media landscape undermines the stability of media habits. As the attention of consumers is spread over more media categories than ever before, only one conclusion is possible: an effective media strategy must take a multimedia selection approach (Franz, 2000).The media mix decisions, a unique case of a resource allocation problem, is a complex multi-faceted decision (Dyer, Forman, and Mustafa, 1992). Selecting the best media requires considering not only cost and the number of readers, but also the efficiency with which the medium reaches the target audience. These developments have influenced the media usage habits of target audiences as well as the fit between the product and the characteristics of the medium. The media selection approach is defined as the process whereby the decision maker selects the media vehicles that affect the audience effectively by simultaneously considering multiple and interdependent evaluation criteria, which is a multi criteria decision making (MCDM) problem (Lgnizio, 1976; Dyer, Forman, and Mustafa, 1992). Many factors have increased the complexity of the media selection decision. The criteria are usually interdependent (Gensch, 1973). Moreover, since some criteria are uncertainty, qualitative, and subjective, consistent expert opinions are rare (Dyer, Forman and Mustafa, 1992; Calantone, 1981). So far, the literature on media selection problems suggests that the criteria for evaluating media are independent and ignore the interactions between the criteria (Lgnizio, 1976; Lee, 1972; Dyer, Forman and Mustafa, 1992). Since the process for media selection is so complicated, an effective tool for assessing interdependent criteria is needed. However, AHP models a decision-making framework that assumes a unidirectional hierarchical relationship among decision levels (Triantaphyllou and Mann, 1995; Meade and Presley, 2002; Shen et al., 2010). Analytic Network Process (ANP) is an effective tool when elements of the system are interdependent (Saaty, 2001). The ANP is more accurate in complex situation due to its capability of modeling complexity and the way in which comparisons are performed (Yang et al., 2010). The ANP has been applied to many areas, including (1) evaluating and selecting alternatives; e.g., ANP has been utilized to construct a model for selecting an appropriate project (Lee and Kim 2001; Shang et al., 2004; Chang, Yang, and Shen, 2007), a company partner (Chen et al., 2004), and an appropriate product design (Karsak et al., 2002); (2) optimizing a product mix (Chung et al., 2005) and price allocation (Momoh and Zhu, 2003); (3) constructing models for assessing ISSN 1943-670X

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International Journal of Industrial Engineering, 19(8), 305-319, 2012.  

SOLVING CAPACITATED P-MEDIAN PROBLEM BY A NEW STRUCTURE OF NEURAL NETWORK Hengameh Shamsipoor, Mohammad Ali Sandidzadeh, Masoud Yaghini School of Railway Engineering, Iran University of Science & Technology, Kermanshah University of Technology, Iran Corresponding author email: Email: [email protected] One of the most popular and renowned location-allocation problems is Capacitated P-Median Problem (CPMP). In CPMP locations of p capacitated medians are selected to serve a set of n customers, so that the total distance between customers and medians is minimized. In this paper primarily we present a new dynamic assignment method based on urgency function. After that a new formulation for CPMP, based on two types of decision variables with 2( n + p ) linear constraints, is proposed. Later on, based on the newly presented formulation, we propose a novel neural network structure that comprises five layers. This neural network is a combination of two-layered Hopfield neural network with location and allocation layers and three other layers that control the Hopfield neural network. The advantage of the proposed network is that it always provides feasible solutions, and since the constraints are united in this neural structure instead of the energy function, the need for tuning parameters is avoided. According to the computational dynamic of the new neural network, the amount of energy function always decreases or remains constant. The effectiveness and efficiency of this algorithm, for standard and simulated problems with different sizes, are analyzed. Our results show that the proposed neural network generates excellent quality and acceptable solutions. Keywords: Location-allocation, Capacitated p-Median Problem (CPMP), Neural Network, Hopfield Network. (Received 2 Feb 2010; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Location allocation problem has several applications in the areas of telecommunication, transportation and distribution and has received a great deal of attention from many researchers recently. One of the most well-known location-allocation problems is the capacitated p-median problem. Its aim is to locate p facilities within the given space to serve n demand(s) with the minimum total cost possible. We illustrate a typical p-median model in Fig. 1. The total cost of the solution presented is the sum of the distance between demand points and selected location which is presented by the black lines [1].

  Figure 1. Typical output for the p-median problem

The p-median problem is an improved NP-hard problem in which an increase in the input increases the computation time of the result logarithmically. Consequently, many heuristic methods have been developed to solve this problem. In this article we try to use neural network techniques to solve the p-median problem in which each facility can serve only a limited number of demands. ISSN  1943-­‐670X                                                                                                                                                                                                                                                                                ©  INTERNATIONAL  JOURNAL  OF  INDUSTRIAL  ENGINEERING  

International Journal of Industrial Engineering, 19(8), 320-329, 2012.

ADOPTING THE HEALTHCARE FAILURE MODE AND EFFECT ANALYSIS TO IMPROVE THE BLOOD TRANSFUSION PROCESSES 1

Chao-Ton Su1,*, Chia-Jen Chou1, Sheng-Hui Hung2, Pa-Chun Wang2,3,4 Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu 30013, Taiwan, R.O.C. 2 Quality Management Center, Cathay General Hospital, Taipei 10630, Taiwan, R.O.C. 3 Fu Jen Catholic University School of Medicine, Taipei County 24205, Taiwan, R.O.C. 4 Department of Public Health, China Medical University, Taichung 40402, Taiwan, R.O.C. *Corresponding author. Email: [email protected]

The aim of this study is to conduct the healthcare failure mode and effects analysis (HFMEA) to evaluate the risky and vulnerable blood transfusion process. By implementing HFMEA, the research hospital plans to develop a safer blood transfusion system that is capable of detecting potentially hazardous events in advance. In this case, eight possible failure modes were identified in total. Regarding the severity and frequency, seven failure modes were identified to have hazard scores higher which are than 8. Five actions were undertaken to eliminate the potential risk processes. After the completion of HFMEA improvement, from the end of July, 2008 to December 2009, two adverse events occurred during the blood transfusion processes and the error rate is 0.012%. The HFMEA proves to be feasible and effective to predict and prevent potentially risky transfusion processes. We have successfully introduced information technology to improve the whole blood transfusion process. Keywords: healthcare failure mode and effect analysis (HFMEA), blood transfusion, hazard score. (Received 30 Mar 2011; Accepted in revised form 1 Feb 2012)

1.

INTRODUCTION

Reducing medical errors for a given healthcare process is critical to patient safety. Traditionally, risk assessment methods in healthcare have analyzed adverse events individually. However, risk-evaluated approaches should reflect healthcare operations, which are usually composed of sequential procedures. In other words, a systematic and process-driven programming of risk prevention is necessary for every healthcare provider. Many studies have illustrated the necessities to introduce risk analysis method in preventing the medical error ((Bonnabry et al., 2006); (Bonan et al., 2009)). Healthcare Failure Mode and Effect Analysis (HFMEA) is a novel technology used to evaluate healthcare processes proactively. HFMEA was first introduced by the Department of Veterans Affairs (VA) System and developed by the National Center for Patient Safety (NCPS) in the United States. HFMEA is a hybrid risk evaluation system that combines the ideas behind Failure Mode and Effect Analysis (FMEA), Hazard Analysis and Critical Control Point (HACCP), and the VA’s root cause analysis (RCA) program. An interdisciplinary team, process and subprocess flow drawing, identification of failure mode and its cause, a hazard scoring matrix, and a decision tree to determine system weakness are usually included in HFMEA. Currently, the HFMEA method is encouraged by the American Society for Healthcare Risk Management for hospitals in the United States (Gilcheist et al., 2008). Clinical researches have identified blood transfusion as a significant risky process (Klein, 2001; Rawn, 2008). Errors in blood transfusion result in immediate and long-term negative outcomes including the increase chance of death rates, stroke, renal failure, myocardial infraction, and infection, among others. Therefore, reducing the risks of blood transfusion is a major patient safety issue for all hospitals. The blood transfusion process is setting on top of the list for process analysis, since the process affects a large number of patients and the procedure is complex in nature (Burgmeier, 2002). Linden et al. (2002) indicated that the blood transfusion is a complicated system involving the hospital blood bank, patient floor, emergency department, operating room, transfusionist, and transporter. A more comprehensive and risk proactive analysis of the blood transfusion process is necessary to improve patient safety. A series of transfusion-related adverse events take place in the research hospital have urged the Patient Safety Committee to take decisive actions to prevent harmful medical errors resulted from transfusion-related processes. An efficient risk prevention method was anticipated to reduce the number of adverse blood transfusion events at the research hospital. The aim of this study is to conduct the HFMEA to evaluate the risky and vulnerable blood transfusion process. By ISSN 1943-670X

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International Journal of Industrial Engineering, 19(8), 330-340, 2012.  

ECODESIGN CASE STUDIES FOR FURNITURE COMPANIES USING THE ANALYTIC HIERARCHY PROCESS Miriam Borchardt, Miguel A. Sellitto, Giancarlo M. Pereira, Luciana P. Gomes Vale do Rio dos Sinos University (UNISINOS) Address: Av. Unisinos, 950 – São Leopoldo – CEP 93200-000 – RS - Brazil Corresponding author e-mail: [email protected] The purpose of this paper is to propose a method to assess the degree of the implementation of ecodesign in manufacturing companies. This method was developed based on a multi-criteria decision support method known as analytic hierarchy process (AHP). It was applied in three furniture companies. Ecodesign constructs were extracted from the literature related to environmental practices and weighted according to the AHP method, allowing for a determination of the relative importance of the constructs for each company. Finally, the team answered a questionnaire for each company to check each item’s degree of application of these processes. One year later, the method was applied again to the same three companies. By comparing the assessed relative importance of each ecodesign construct and the degree of its application, it was possible for us to observe the relation of the priorities of the companies to their eco-conception. Keywords: ecodesign, design for environment, sustainability, furniture industry, Analytic Hierarchy Process, ecoconception. (Received 11 Sep 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION One of the key contributing causes to the environmental degradation that threatens the planet is the increasing production and consumption of goods and services. Some of the factors that contribute to environmental degradation are (a) the lifestyle of some societies, (b) the development of emerging countries, (c) the aging of populations in developed countries, (d) inequalities between the planet’s regions and (e) the increasingly short life cycles of products (Manzini and Vezzolli, 2005). Environmental considerations, such as ecodesign (or design for (the) environment, DfE), cleaner production, recycling projects and the development of sustainable products, promote a redesign of techniques for the conceptualization, design and manufacturing of goods (Byggeth et al., 2007). A balance between the environmental “cost” and the functional “income” of a production method is essential for achieving sustainable development, a requirement that has resulted in a situation in which environmental issues must now be merged into “classical” product development processes (Luttropp and Lagerstedt, 2006; Plouffe et al., 2011). Out of this context, we can define ecodesign as a technique for establishing a product project in which the usual project goals, manufacturing costs and product reliability are considered, along with environmental goals such as the reduction of environmental risks, reduction in the use of natural resources, increase in recycling and the efficiency in the use of energy (Fiksel, 1996). Such a technique makes it possible to relate the functions of a product or service to issues in environmental sustainability, reducing environmental impact and increasing the presence of eco-efficient products, as well as encouraging technological innovation (Manzini and Vezzoli, 2005; Santolaria et al., 2011). The environmental practices observed in the literature on ecodesign are chiefly related to the materials, components, processes and characteristics of products, including the use of energy, storage, distribution, packing and material residuals (Wimmer et al., 2005; Luttropp and Lagersted, 2006; Fiksel, 1996). However, even though these techniques have been explored in the literature, the environmental practices related to ecodesign have a generic shape and are difficult to fit to specific product projects and industrial processes (Borchardt et al., 2009). Authors such as De Mendonça and Baxter (2004) and Goldstein et al. (2011) have worked to develop performance indicators associated with ecodesign and have related ecodesign principles with environmental management, showing a positive correlation between the two. However, notably, there is no consensus regarding this topic. Despite the fact that environmental assessments are commonly found in the literature, no objective method can generate an ecodesign measurement instrument to evaluate the degree of implementation. Such an instrument would help organizations to prioritize their efforts in terms of achieving the most significant environmental gains. There is a need for a structural approach in ecodesign that can address environmental concerns in a coherent way. However, the limits in capabilities and resources available to many companies frequently hamper the development of an ISSN  1943-­‐670X                                                                                                                                                                                                                                                                                ©  INTERNATIONAL  JOURNAL  OF  INDUSTRIAL  ENGINEERING  

International Journal of Industrial Engineering, 19(9), 341-349, 2012.

APPLYING GENETIC LOCAL SEARCH ALGORITHM TO SOLVE THE JOB-SHOP SCHEDULING PROBLEM Chuanjun Zhu1, Jing Cao1, Yu Hang2, Chaoyong Zhang 2 School of Mechanical Engineering, Hubei University of Technology, Wuhan, 430068, P.R. China 2 State Key Laboratory of Digital Manufacturing Equipment & Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, P.R. China 1

This paper presents a genetic local search algorithm for the Job-Shop Scheduling problem, and the chromosome representation of the problem is based on the operation-based representation. In order to reduce the search space, schedules are constructed using a procedure that generates active schedules. After a schedule is obtained, a local search heuristic based on N6 neighborhood structure is applied to improve the solution. In order to avoid premature convergence of the conventional genetic algorithms (GA), the improved precedence operation crossover (IPOX) and approach of the generation alteration schema are proposed. The approach is tested on a set of standard instances taken from the literature. The computation results validate the effectiveness of the proposed algorithm. Keywords: Genetic Algorithms; Local Search Algorithms; Job-Shop Scheduling Problem (Received 1 Oct 2010; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Generally the Job-Shop scheduling problem can be described as follows: a set of n jobs is to be processed on a set of m machines that are continuously available from time zero onwards, and each job has special processing technology. Each job consists of a sequence of operations, and each of the operations uses one of the machines for a fixed duration. The scheduling problem is to find a schedule which optimizes some index by determining machining sequence of job in every machine. The hypothesis is as follows: (1) The processes of different jobs have no machining sequence constraint; (2) Any process can not be interrupted once be begun, and every machine can only machining one job a certain time; (3) Machines can not break down. The objective of the problem is to find a schedule which minimizes the makespan (Cmax) or optimizes other indices by determining start time and machining sequence of every job. The Job-Shop Scheduling problem can be simplified as n/m/G/Cmax. Job-Shop scheduling problem is a well-known NP-hard problem, which have wide applications in the industrial fields. In order to solve the hard problem, Job-Shop scheduling has been studied by a significant number of researchers for several decades, and many theoretical research results have been proposed. The research achievements mainly include heuristic dispatch rules(Panwalkar S, et al, 1977), mathematical programming(Blazewicz J, et al,1991), simulation-based methods(Kim M, et al, 1994), and Artificial Intelligence (AI)-based methods(Foo S Y, et al, 1994) and so on. Heuristic dispatch rules is straightforward and easy to implement, but it can only obtain local optimization and moderate effect. When using mathematical programming methods, computing burden may increase exponentially with the increasing of Job-Shop scheduling scale. Simulation methods can lead to higher computational cost and not find optimal solution. With the development of computer technology, a number of complicated optimization methods by simulating some feature of the biology evolution system, physical systems and human being’s behavior are getting rapid development recently. Therefore, the meta-heuristic methods, such as genetic algorithms (GA) (Croce et al.,1995, Ibrahim et al.,2008), neural network method, simulated annealing (SA) (Van Laarhoven et al.,1992), tabu search (TS) (Taillard, 1994, Nowicki et al, 1996), have become research hotspot of Job-Shop scheduling problem. GA were originally developed by Professor J. Holland of Michigan University. Professor Holland published a monograph which systematic exposition the basic theory and method of GA in 1975(Holland J H, 1975). GA main reference the evolutionary criterion of the survival of the fittest in natural selection from Darwin’s evolutionism, imitate biology reproduction, mating and gene mutation by selection, crossover and mutation operation, and find best chromosome to solve problem by gene attached on it. GA are universal optimization algorithm, their coding technology and genetic operation are comparatively simple, and the optimization process is no constraint condition and have the characteristics of implicit parallelism and global solution space searching etc, so GA become the widely used in resolving Job Shop scheduling problem. However, GA have global searching ability due to their population parallel searching so has poor local searching ability and is prone to premature convergence. Local Search (LS) algorithm is used to local searching, but it is ISSN 1943-670X

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International Journal of Industrial Engineering, 19(9), 350-358, 2012.  

BIOBJECTIVE MODEL FOR REDESIGNING SALES TERRITORIES Juan Gabriel Correa Medina1, Loecelia Guadalupe Ruvalcaba Sánchez1, Elias Olivares-Benitez2, Vittorio Zanella Palacios3 1 Department of Information Systems, Autonomous University of Aguascalientes 2 Metallurgical Engineer, National Polytechnic Institute 3 Department of Computer Engineering, Autonomous University of Puebla State

Designing and updating of sales territories are strategic activities that have several causes like mergers and changes in the markets among others. The new territories must satisfy the planning characteristics defined by each company. In this paper we propose a biobjective mixed integer programming model for redesigning sales territories. The study was motivated by the case of a company that distributes its products along Mexico. The model looks for minimizing the total sum of the distances and the variation of the sales volumes for each salesman with respect to the current situation. The model is solved using the ε-constraint method to obtain the true efficient set, and a heuristic method to obtain the approximate efficient set. Both efficient sets are compared to determine the quality of solutions obtained by the heuristic method. Keywords: biobjective model, sales territory, integer programming, business strategies (Received 23 Feb 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION The design and constant updating of the sales territories are important strategic activities that have as intention to improve the service level to customers through an efficient and effective covering of the markets. The updating of the sales territories is required mainly because of mergers of firms and changes in the markets (expansion, contraction). Sometimes just small sales territory realignment can have a big impact on the sales force productivity. Therefore it is a critical and ongoing process to help maximize sales productivity and revenue. Some of the benefits of sales territory design include: 1) a better coverage and customer service leading to increased productivity and sales revenue; 2) Increased sales by prioritizing accounts with the greatest potential; 3) Reduced costs of sales through shorter and cheaper travel times; 4) improved morale, performance and permanence of sales people due to equitable distribution of accounts and an impartial system for achieving rewards; 5) competitive advantage through the ability to reach new opportunities faster than the competitors. The territories design or redesign groups geographical small areas, defined as sales coverage units (SCUs), in larger geographical units known as territories. These territories must satisfy certain planning characteristics determined by the firm’s management considering the assignment of customers, types of products, geographical areas, workload, sales volume and territories dimensions for every salesman, among others. The sales territory design problem is classified as a districting problem. Typical districting problems include the drawing of political constituencies, school board boundaries, sales or delivery regions (Bozcaya et al., 2003). Although multiple exact and heuristic methods have been applied to solve this problem, its generalization is difficult because the goals of every firm are different. In addition, Pereira-Tavares et al. (2007) mention that when there are multiple criteria, the problem is considered NP-hard. Puppe and Tasnadi (2008) showed that in discrete districting problems with geographical limitations, the determination of an impartial redistricting turns out to be a problem computationally intractable (NPcomplete). In this paper a biobjective mixed integer programming model is proposed for redesigning sales territories. The work is structured as follows. In section 2 the problem is described showing its characteristics. Section 3 presents the mixed integer programming model, the exact method and the heuristic algorithm used to solve it and the comparison metrics. In section 4 the experiments are explained and the results obtained are shown. Section 5 shows the conclusions and future work for this research.

2. PROBLEM DEFINITION The problem analyzed in this paper is motivated by a firm which sells its products along Mexico. This problem was analyzed originally by Olivares-Benítez et al. (2009). To control its sales force, the firm has divided the Mexican Republic into regions. In every region, the salesmen have inherited and enlarged their customers portfolio to improve their income without intervention from the firm’s management. This absence of control has produced unbalanced territories with regard ISSN  1943-­‐670X                                                                                                                                                                                                                                                                                ©  INTERNATIONAL  JOURNAL  OF  INDUSTRIAL  ENGINEERING  

International Journal of Industrial Engineering, 19(10), 369-388, 2012.

REVERSE LOGISTICS: PERSPECTIVES, EMPIRICAL STUDIES AND RESEARCH DIRECTIONS *Arvind Jayant1, P.Gupta2, S.K.Garg3 Department of Mechanical Engineering, Sant Longowal Institute of Engineering & Technology, Longowal, Punjab, India (Deemed to be University) 3 Department of Mechanical Engineering, Delhi Technological University, Delhi-110042 *Corresponding Author E-mail address: [email protected] 1,2

Environmental and economic issues have significant impacts on reverse logistics practices in supply chain management and are thought to form one of the developmental cornerstones of sustainable supply chains. Perusal of the literature shows that a broad frame of reference for reverse logistics is not adequately developed. Recent, although limited, research has begun to identify that these sustainable supply chain practices, which include the reverse logistics factors, lead to more integrated supply chains, which ultimately can lead to improved economic performance. The objectives of this paper are to: report and review various perspectives on design and development of reverse SC, planning and control issues, coordination issues, product remanufacturing and recovery strategies, understand and appreciate various mechanisms available for efficient management of reverse supply chains and identify the gaps existing in the literature. Ample opportunities exist for the growth of this field due to its multi-functional and interdisciplinary focus. It also is critical for organizations to consider from both an economic and environmental perspective. The characteristics of reverse logistics provided here can help the researchers/practitioners to advance their work in the future. Significance: The objective of this study is to encourage and provide researchers with future research directions in the field of reverse logistics for which only empirical research methods are not appropriate. In addition, the research directions suggested in the paper address several opportunities and challenges that currently face business managers & academicians operating in closed loop supply chain management. Keywords: Reverse supply chain management, Remanufacturing, Recycling, Reverse logistics. (Received 11 May 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Reverse logistics, which is the management or return flow due to product recovery, goods return, or overstock, form a closed-loop supply chain. The success of the closed-loop supply chain depends on actions of both manufacturers and customers. Now, manufacturers require producing products which are easy for disassembly, reuse and remanufacturing owing to the law of environmental protection. On the other hand, the number of customers supporting environmental protection by delivering their used products to collection points is increasing (Lee and Chan, 2009). According to the findings, the total cost spent in reverse logistics is huge. In order to minimize the total reverse logistics cost and high utilization rate of collection points, selecting appropriate locations for collection points is critical issues in RSC/reverse logistics. Reverse logistics receive increasing attention from both the academic world and industries in recent years. There are a number of reasons for its attention. According to the findings of Rogers and Tibben-Lembke (1998), the total logistics cost amounted to $862 billion in 1997 and the total cost spent in reverse logistics is enormous that amounted to approximately $35 billion which is around 4% of the total logistics cost in the same year. The concerns about energy saving, green legislation and the rise of electronic retaining are increasing. Also, the emergence of e-bay advocates product reuse. Online shoppers typically return items such as papers, aluminum cans, and plastic bottles whose consumption and return rates are high. Although most companies realize that the total processing cost of returned products is higher than the total manufacturing cost, it is found that strategic collections of returned products can lead to repetitive purchases and reduce the risk of fluctuating the material demand and cost. Research on reverse supply chain has been growing since the Sixties (see, for example, Zikmund and Stanton, 1971; Gilson, 1973; Schary, 1977; Fuller, 1978). Research on strategies and models on RL can be seen in the publications in and after the Eighties. However, efforts to synthesize the research in an integrated broad-based body of knowledge have been limited (Pokharel and Mutha, 2009). Most research focuses only on a small area of RL systems, such as network design, production planning or environmental issues. Fleischmann et al. (1997) studied RL from the perspectives of distribution planning, inventory control and production planning. Carter and Ellram (1998) focused on the transportation and ISSN 1943-670X

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International Journal of Industrial Engineering, 19(10), 389-400, 2012.

CONTINUOUS-REVIEW INVENTORY MODELS USING DIFFUSION APPROXIMATION FOR BULK QUEUES Singha Chiamsiri1, Hui Ming Wee2 and Hsiao Ching Chen3 School of Management, Asian Institute of Technology, Klong Luang, Pathumthani 12120, Thailand 2 Industrial & Systems Engineering Department, Chung Yuan Christian University, Chungli,32023, Taiwan, ROC 3 Department of Business Management, Chungyu Institute of Technology , Keelung 20103, Taiwan ROC H.M.Wee, e-mail: [email protected] 1

In this paper, two continuous-review inventory control models are developed using steady-state diffusion approximation method. Accuracy evaluations of the approximate optimal solutions for the inventory control models are reported for selected “Markovian-like” queues to approximate the steady-state queue size behavior of single-server queues with bulkarrival and batch-service. The diffusion approximation method gives a remarkably good performance in approximating the base stock level one-to-one ordering policy inventory model. The approximation for the order-up to inventory model with replenishment lot size greater than one is also exceptionally good at selected values of heavy traffic intensity and when the service time replenishment process distributional characteristic does not differ greatly from the exponential inter-arrival time of the demands. Keywords: Inventory; Queueing; Continuous-review policy; Diffusion approximation (Received 1 Apr 2010; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION There are many applications of diffusion approximations in population genetics modeling (Bahrucha-Reid 1960, Cox and Miller 1968, and Feller 1966), the optimal control of a stochastic advertising model (Tapiero 1975), storage systems model and inventory control model (Bather 1966, Harrison and Taylor 1976, and Puterman 1975), and in queuing models (Kingman 1965, Chiamsiri and Leonard 1981, and Whitt 2004) and queuing networks/systems in computer applications (Kleinrock 1976). Diffusion models have been developed in order to mitigate the analytical and the computational complexity of performance measures and optimal solutions. For example, Chiamsiri and Leonard (1981) developed a diffusion process to approximate the steady-state queue size behavior of single-server queues with bulk-arrival and batch-service, referred to as bulk queues. Diffusion approximation solutions for various queue size statistics are developed and evaluated for a number of special “Markovian-like” bulk queues. The diffusion approximation method provides a robust solution for the queue size distribution under heavy traffic conditions. Rubio and Wein (1996) identified specific formula for the base stock levels under a multi-product production-inventory system by exploiting the make-to-stock system and an open queuing network. Perry et al, (2001) studied the problem of a broker in a dealership market whose buffer content (cash flow) is governed by stochastic price-dependent demand and supply. Three model variants are considered. In the first model, buyers and sellers (borrowers and depositors) arrive independently in accordance with price-dependent compound Poisson streams. The second and the third models are two variants of diffusion approximations. They developed an approach to analyze and compute the cost function based on the optional sampling theorem. Wein (1992) noted that diffusion models require a heavy traffic condition to be valid and used the diffusion process to model a multi-product, single-server Make-to-Stock system. Diffusion approximation method provides an approximate solution for a general class of queuing models, and is particularly valuable when compared with simulation since both methods provide approximate numerical results. However, the diffusion approximation method requires far less computation time to generate numerical results, especially for queues under heavy traffic conditions. Bather (1966) was the first author to develop a diffusion process model for an inventory control problem. The inventory control problem considered was assumed to have instantaneous replenishments with continuous-review (s, S) operating policy type. Demands were assumed to be a Weiner (Gaussian) process and statistical decision theory was used to obtain the optimal solution. A more general diffusion process model for storage system was considered by Puterman (1975). The diffusion process model was found to be suitable for a storage system with an infinitely divisible commodity such as liquids, e.g., oil, blood, or whisky. Puterman (1975) also indicated that: “The model might also be used to approximate more lumpy quantities such as tires, whistles, or people, especially if the numbers are large”. This is because the sequences of stochastic input-output system processes such as queues, dams, and inventory system often converge to limiting stochastic processes which are else ISSN 1943-670X

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International Journal of Industrial Engineering, 19(9), 359-368, 2012.

A NURSE SCHEDULING APPROACH BASED ON SET PAIR ANALYSIS 1

Jianfeng Zhou1, Yuyun Fan2, Huazhi Zeng3 Department of Industrial Engineering, School of Mechatronics Engineering, Guangdong University of Technology, Guangzhou, China 2 Responsibility Nurse, Guangzhou Chest Hospital of China 3 Nursing Director, Guangzhou Chest Hospital of China

In practice, multiple sources of uncertainties needed to be treated in nurse scheduling. The problem involves multiple conflicting objectives such as satisfying demand coverage requirements and maximizing nurses’ preferences subject to a variety of constraints imposed by legal regulations, personnel policies and many other hospital-specific requirements. The aim of this research is twofold: Firstly, to apply SPA (set pair analysis) theory to the nurse scheduling problem (NSP) to treat uncertainties and to model and solve the nurse schedule assessment problem. Secondly, to integrate the nurse schedule assessment model with GA (genetic algorithm) to establish a nurse scheduling approach. A case study of nurse scheduling in a surgical unit of Guangzhou Chest Hospital in China is presented to validate the approach. Keywords: nurse scheduling problem; set pair analysis; genetic algorithm (Received 27 Feb 2011; Accepted in revised form 1 Feb 2012)

1. INTRODUCTION Nurse scheduling problem (NSP) is a highly constrained scheduling problem which involves generating individual schedules for nurses over a planning period. Usually, the period is a week or a number of weeks. At the end of a period, the time table of the next period is to be determined. The nurses need to be assigned to possible shifts in order to meet the constraints, and to maximize the schedule quality by meeting the nurses’ requests and wishes as much as possible. Nurse scheduling is a NP complete problem. It is hard to obtain a high quality schedule via automatic approach due to various constraints including legal regulations, management objectives, and requests of nurses need to be considered. Thus, the nurse scheduling is often solved manually in many hospitals in practice. In the past, a considerable number of relevant studies on nurse scheduling problem have been found. The proposed approaches can be divided into three types, the first is mathematical programming approach, the second is heuristic approach, and the third is AI (Artificial Intelligence) approach (Cheang et al., 2003; Burke et al., 2004). The mathematical programming approaches adopt traditional operational research methods, such as linear programming, integer programming, and goal programming, to solve the objective optimization problem in nurse scheduling. The objectives of nurse scheduling involve minimum nurses, maximum satisfaction of nurses’ requests, and minimum costs. Warner (1976) proposed a nurse scheduling system, which poses the scheduling decision as a large multiple-choice programming problem whose objective function quantifies preferences of individual nursing personnel concerning length of work stretch, rotation patterns, and requests for days off. Bartholdi et al. (1980) presented an integer linear programming model with cyclically structured 0-1 constraint matrix for cyclic scheduling. Bailey et al. (1985) utilized linear programming for personnel scheduling when alternative work hours are permitted. Heuristic approaches, especially meta-heuristic approaches, have shown their advantages in solving non-linear and complex problems. They are generally better suited for generating an acceptable solution in cases where the constraint load is extremely high and indeed in cases where even feasible solutions are very difficult to find. In recent years, the meta-heuristic approaches, such as genetic algorithm, simulated annealing algorithm, and ant colony optimization algorithm, have been adopted to solve nurse scheduling problem. Aickelin et al. (2003) presented a genetic algorithms approach to a nurse scheduling problem arising at a major UK hospital. The approach used an indirect coding based on permutations of the nurses, and a heuristic decoder that builds schedules from these permutations. Kawanaka et al. (2001) proposed a genetic algorithm based method of coding and genetic operations with their constraints for NSP. The exchange of shifts is done to satisfy the constraints in the coding and after the genetic operations. Thompson (1996) developed a simulated-annealing heuristic for shift scheduling using employees having limited availability and, by comparing its performance to that of an efficient optimal integer programming model, demonstrated its effectiveness. Gutjahr et al. (2007) described the first ant colony optimization (ACO) approach applied to nurse scheduling, analyzing a dynamic regional problem. Many results of artificial intelligence research were also used to solve NSP. Petrovic et al. (2003) proposed a new scheduling technique for capturing rostering experience using case-based reasoning methodology. Examples of previously ISSN 1943-670X

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International Journal of Industrial Engineering, 19(10), 401-411, 2012.

A FRAMEWORK OF INTEGRATED RECYCLABILITY TOOLS FOR AUTOMOBILE DESIGN Novita Sakundarini 1, Zahari Taha2, Raja Ariffin Raja Ghazilla1, Salwa Hanim Abdul Rashid1, Julirose Gonzales1 1 Department of Engineering Design and Manufacture Center for Product Design and Manufacturing University of Malaya, 50603 Kuala Lumpur, MALAYSIA 2 Faculty of Mechanical Engineering University Malaysia Pahang, 26600 Pekan, Pahang, MALAYSIA N. Sakundarini, email : [email protected] Automobiles are major transportation choice for society around the world. Automotive industries in many countries mostly are one of the drivers of economic growth, job creation and technology advancement. Although automotive industry gives promising return, problem of managing disposal at the end of automotive’s life is quite challenging. Automobile is a very complex product that comprise of thousand components made from various materials that need to be separately treated. In addition, short supply of natural resources has provided opportunities to either reuse, remanufacture or recycle automotive’s components. End of Life Vehicle (ELV) Directive launched by European Union mandated that recyclability rate of automobile must reach 85% by 2015. The aim of this legislation is to minimize the impact of end of life vehicle, contributing to prevention, preservation and improvement of environment quality and energy conservation. Vehicle manufacturers and suppliers requested to include these aspects at earlier stages of the development of new vehicles, in order to facilitate the treatment of vehicles at the time when they reach the end of their life. Therefore, the automobile industry has to establish its voluntary action plan for ELVs, and has numerical target to improve ELV recycling rate, reduce automotive shredder residue (ASR) landfill volume, and reduce lead content. Many innovative approaches in improving recyclability have been implemented, but still called out for more intelligent solutions which integrate recyclability evaluation in product development stage. This paper attempts to review some of current innovative approach that used to improve recyclability and introduce a framework for integrated recyclability tool to improve product recyclability throughout its development phase. Keywords: End of Life Vehicle, disposal, product life cycle, ELV Directive, recyclability. (Received 2 June 2009; Accepted in revised form 1 Feb 2012)

1.

INTRODUCTION

Automobile industries provide essential need for society to support easiness of mobility. According to OECD, the total number of vehicle are expected to increase by 32% from 1997-2020 (Kanari et al., 2003). In Europe, approximately 23 million units of automotive have been produce in 2007, while in Asia there were 30 million units and the number will be increase every year (Pomykala et al., 2007). Automobile products comprise of thousand parts which 74-75% of them compose from ferrous and non-ferrous material and 8-10% are from plastics, and typically only less than 75% of weights to be recycled and the rest are not. This condition leads to the increasing number of landfill space. Unfortunately, there is no more space available to threat this disposal. According to Kumar and Putnam (2008), the automotive recycling infrastructure successfully recovers 75% of the material weight in end-of-life vehicles mainly through ferrous metal separation. However, this industry faces significant challenges as automotive manufacturers increase the use of nonferrous and non metallic materials. Vehicle composition has been shifting toward light material such as aluminium and polymer that consequence on higher impact to the environment. Vehicle affect the environment through their entire life cycle in energy consumption, waste generation, green house gases, hazardous substances emissions and disposal at the end of their life (Kanari et al., 2003) . To overcome this problem, European Union has established EU Direction for end of life vehicle and underlined that in 2015, recyclability rate of automobile must reach 85%. According to EU Directive, recyclability means the potential for recycling of component parts or materials diverted from an end of life vehicle. Vehicle manufacturers and their supplier are requested to include this aspect at the earlier stage of the development of new vehicle, in order to facilitate the treatment of vehicle at the time when they reach their end of life. Many countries are now refer to the EU legislation and try to demonstrate a strategy in fulfilling this requirement by using less of non-recyclable material in their products, calculating for energy usage, limit waste stream, etc. Additionally, as consumption increases, raw ISSN 1943-670X

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International Journal of Industrial Engineering, 19(11), 412-427, 2012.

THE OPERATION OF VENDING MACHINE SYSTEMS WITH STOCK-OUT-BASED, ONE-STAGE ITEM SUBSTITUTION Yang-Byung Park, Sung-Joon Yoon Department of Industrial and Management Systems Engineering, College of Engineering, Kyung Hee University, 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do 446-701, Republic of Korea Corresponding author’s e-mail: {Yang-Byung Park, [email protected]} The operation of vending machine systems presents a decision-making problem consisting of item allocation to storage compartments, inventory replenishment, and vehicle routing, all of which have critical effects on system profit. In this paper, we propose a two-phase solution with an iterative improvement procedure for the operation problem with stock-outbased, one-stage item substitution in vending machine systems. In the first phase, the item allocation to storage compartments and the replenishment intervals of vending machines are determined by solving a non-linear integer mathematical model for each machine. In the second phase, vehicle routes for replenishing vending machine inventories are determined by applying the savings-based algorithm, which minimizes the sum of transportation and shortage costs. The accuracy of the solution is improved by iteratively executing the two phases. The optimality of the proposed solution is evaluated on small test problems. We present an application of the proposed solution to an industry problem and carry out computational experiments on test problems to evaluate the effectiveness of the stock-out allowance policy with one-stage item substitution compared to the no-stock-out allowance policy with respect to system profit. The results show the substantial economic advantage of the stock-out allowance policy. Sensitivity analysis indicates that some input variables significantly impact the effectiveness of this policy. Significance: A no-stock-out policy at vending machines may cause excess transportation and inventory costs. Allowing stock-outs and substitutions for stock-out items might increase the profit of the vending machine system. A proposed two-phase heuristic generates high quality solutions to the operation problem with stock-out-based, one-stage item substitution in vending machine systems. The results of the computational experiments with the proposed heuristic guarantee a substantial economic advantage of the stock-out allowance policy over the no-stock-out allowance policy and present favorable environments to the stock-out allowance policy. The proposed two-phase solution can be modified easily for application to various retail vending settings under a vendor-managed inventory scheme. Keywords: Vending machine system, inventory management, operation problem, item substitution (Received 1 Jan 2012; Accepted in revised form 7 Oct 2012)

1. INTRODUCTION Vending machines have become an essential part of daily life in many countries. Their spread is especially important from an environmental perspective because they enable consumers in remote locations to make purchases without having to drive long distances. The USA is estimated to have over four million vending machines, with retail sales over $30 billion annually. Japan's vending machine density is the highest in the world. The number of vending machines in South Korea has increased over 10% every year in recent years (Korea Vending Machine Manufacturers Association, 2009). Most vending machines sell beverages, food, snacks, or cigarettes. Recently, they have expanded to include tickets, books, flower pots, and medical supplies like sterile syringes. Vending machine management companies manage a network of vending machines in dispersed locations. A company assigns between 100~200 vending machines to different business offices based on location, and each business office manages its machines using 10~20 vehicles. An example of a vending machine system is depicted in Figure 1. Under a vendor-managed inventory scheme, the business office is responsible for coordinating item allocation to vending machine storage compartments, inventory replenishment, and vehicle routing, with the objective of maximizing system profit. These decisions and management practices are referred to as the operation problem for vending machine systems (OPVMS).

ISSN 1943-670X

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International Journal of Industrial Engineering, 19(11), 428-443, 2012.

INDUSTRY ENERGY EFFICIENCY ANALYSIS IN NORTHEAST BRAZIL: PROPOSAL OF METHODOLOGY AND CASE STUDIES Miguel Otávio B C. Melo1, Luiz Bueno da Silva2, Sergio Campello3 1,2 Universidade Federal da Paraíba Cidade Universitária, [email protected], [email protected] Tel.: +55 83 32167685 ; fax: +55 83 32167549. João Pessoa – PB, Brazil 58051-970 3 Portal Tecnologia Rua Joao Tude de Melo 77 Recife-PE, Brazil52060-010 [email protected] Energy gains vital importance once it accounts for up to one-third of the product cost. One can also consider energy as a strategic input for the establishment of any economic and social development policy. Electricity is the basis for industrial production, agriculture, as well as in providing services chain; hence, the need to reduce the cost for that input is vital. This produces great benefits to the production chain by making companies more competitive, and people benefit because the products’ final price becomes cheaper. The aim of this paper is to present a new methodology for assessing industrial efficiency energy and identify points of energy losses and the most influenced sectors within the production process, and propose mitigation measures. Keywords: Energy Efficiency; Clean Energy; Industrial Energy Management (Received 8 Mar 2011; Accepted in revised form 3 Oct 2012)

1. INTRODUCTION Energy management in industry or commerce should not be limited to concerns about assistance in demand and taking energy-efficiency measures; it should also sustain the idea of knowing policies and rules of energy compound, quality certificates, as well as environmental and CO2 certificates (Cullen et al. 2010, Siitonen et al. 2010). Currently, there are several industrial sectors that have already obtained opportunities to improve energy efficiency in thermal systems, efficient motors, buildings with thermal insulation, efficient automated cooling, expert systems, and more efficient compressed air and chilled water and boilers (Laurijssen et al. 2010, Hasanbeigi et al. 2010, Kirschen et al. 2009, Hammond, 2007). In domestic industries, it is common to apply conventional techniques in the operation of motor system. The interpretation of this reality drives us to undertake studies in this sector, proposing improvements in the production system. The following are noteworthy: Replacement of induction motors with a conventional high-yield motor, methods of motor drives with direct starters or star-delta starting device for smooth, soft-starter, and frequency inverter mainly used in processes that enable operation to change motor shaft speed (Panesi, 2006). Energy gains vital importance once it accounts for up to one-third of the product cost. One can also consider energy as a strategic input for the establishment of any economic and social development policy. Electricity is the basis for industrial production, agriculture, as well as in providing services chain; hence, the need to reduce the cost for that input is vital. This produces great benefits to the production chain by making companies more competitive, and people benefit because the products’ final price becomes cheaper. The aim of this paper is to present a new methodology for assessing industrial efficiency energy and identify points of energy losses and the most influenced sectors within the production process, and propose mitigation measures.

2. GENERAL CONSIDERATIONS From the scope of production chains, energy efficiency is concerned with productivity, which in turn is linked to economic results and management. The management aspects are those that relate to project deployment and implementation, hiring, training and retraining of personnel, as well as system evaluation in general (Jochen et al. 2007). The most important energy-efficiency evaluation factors in economic terms are data consistency, behavior of the consumers, and incentive for participation as well as implementation of energy-efficiency programs (Vine et al. 2010). ISSN 1943-670X

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International Journal of Industrial Engineering, 19(11), 444-455, 2012.

PRODUCT PLATFORM SCREENING AT LEGO Niels Henrik Mortensen1, Thomas Steen Jensen1 and Ole Fiil Nielsen2 Department of Mechanical Engineering1 Technical University of Denmark Niels Koppels Allé, DTU Bygn. 404 DK-2800 Kgs. Lyngby, Denmark Email: Niels Henrik Mortensen, [email protected], Ole Fiil Nielsen, [email protected] Product and Marketing Development2 LEGO Group A/S Hans Jensensvej/Systemvej DK-7190 Billund, Denmark Email: Thomas Steen Jensen, [email protected] Product platforms offer great benefits to companies developing new products in highly competitive markets. Literature describes how a single platform can be designed from a technical point of view, but rarely mentions how the process begins. How do companies identify possible platform candidates, and how do they assess if these candidates have enough potential to be worth implementing? Danish toy manufacturer LEGO has systematically gone through this process twice. The first time the results were poor; almost all platform candidates failed. The second time, though, has been largely successful after a few changes had been applied to the initial process layout. This case study shows how companies must focus on a limited selection of simultaneous projects in order to keep focus. Primary stakeholders must be involved from the very beginning, and short presentations of the platform concepts should be given to them throughout the whole process to ensure commitment. Significance: Product platforms offer great benefits to companies developing new products in highly competitive markets. Literature describes how a single platform can be designed from a technical point of view, but rarely mentions how the process begins. This paper describes how platform candidates are identified and synchronized with product development. Keywords: Product platform, Product family, Multi-product development, Product architecture, Platform assessment (Received 8 Jul 2011; Accepted in revised form 3 Oct 2012)

1. INTRODUCTION Numerous publications show the benefits of product platforms. Companies use platforms to develop not a single, but multiple products (i.e. a product family) simultaneously. This may lead to increased sales due to more customized products as well as decreased costs due to reuse, making product platforms very profitable for product developing companies. Designing product platforms is not straightforward, though. How do companies start designing a product platform? Often they start by looking for a suitable platform candidate. Many good examples of product platforms exist in literature, and companies will often look for similar candidates within their own company. But what if no apparent low-hanging fruits are available? How does the company then start designing a product platform? Or what if the low-hanging fruits are too plentiful? How does the company then choose among these candidates, or can they all be undertaken simultaneously? In the literature cases, the case company always starts by having a generic product, which can then be analyzed and modularized. The problem for most companies, however, is that they have no generic product. Instead, they have a range of different products with different structures and different functions, and various restrictions like backwards-compatibility, license-agreements, and existing production equipment prevent the company from changing this fact. Secondly, how do companies know if their platforms will be beneficial? Can they simply assume that all candidates will evolve into profitable platforms? Although cases where platforms fail are very rare in literature, they are not unheard of in industry. It is only natural that most companies would not want to share their unsuccessful platform experiences with the rest of the world. Still many companies, who have finally achieved some degree of success, often describe the process of getting to this level as a struggle, where several important platform initiatives have failed on the way. ISSN 1943-670X

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International Journal of Industrial Engineering, 19(12), 456-463, 2012.

MULTI-ASPIRATION GOAL PROGRAMMING FORMULATION Hossein Karimi, Mehdi Attarpour Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran, Postal Address: Iran, Tehran, 470 Mirdamad Ave. West, 19697, Postal Code: 1969764499. Corresponding author email: mailto:[email protected] A significant analytical approach contrived to solve many real-world problems is Goal Programming (GP). In many marketing or decision management problems, the phenomenon of multi-segment aspiration levels and multi-choice goal levels may exist for decision makers. This problem cannot be solved by current GP techniques such as multichoice goal programming and multi-segment goal programming. This paper provides a new idea to integrate the multi-segment goal programming and multi-choice goal programming in order to solve multi-aspiration problems. Moreover, it develops the concepts of these models significantly for real application; in addition, a real problem is provided to demonstrate usefulness of the proposed model. The results of the problem are analyzed and finally, the conclusion is remarked. Keywords: Multi-aspiration levels; Multi-segment goal programming; Multi-choice goal programming; Decision making; Marketing. (Received 14 Mar 2011; Accepted in revised form 1 Nov 2012)

1. INTRODUCTION Goal programming is a form of linear programming that considers multiple goals that are often in conflict with each other. With multiple goals, all goals usually cannot be achieved properly. For example, an organization may want to: (1) maximize profits and increase after-sales services; (2) increase product quality and reduce product cost and (3) decrease credit sales and increase total sales. GP was originally introduced by Charnes and Cooper (1961). Then, it was extended by Lee (1972), Ignizio (1985), Li (1996), Tamiz et al. (1998), Romero (2001), Chang (2004, 2007) and Liao (2009). Goal programming seeks to minimize the deviations among the desired goals and the actual results according to the assigned priorities. The objective function of a goal programming model is provided in terms of the deviations from the target goals. The general GP model can be described as follows: n ... Minimize ∑ f i ( x) − g i (1) i =1

Where

f i (x ) and g i are the linear function and goal of the i th objective, respectively, and n is the number of

goals. The GP model mentioned above can be solved with many techniques such as Lexicographic GP (LGP), Weighted GP (WGP), and so on. First, some of the GP model formulations are briefly explained. In WGP model, the achievement function consists of the unpleasant deviation variables; the weight of each one represents its importance. Ignizio (1976) provided the mathematical formulations of a WGP model. This model is as following: n ... min ∑ α i d i+ + β i d i− (2) i =1

(

)

subject to

fi (x) − di+ + di− = gi , di+ , di− ≥ 0,

i = 1,2,..., n

i = 1,2,..., n

... ...

(3) (4)

x∈F

... (5) Where d i+ and d i− are orderly the positive and negative deviation between the i th objective and goal. α i and β i are the positive weights for the deviations. In LGP model, an ordered vector makes the structure of achievement function. The dimension of this vector matches Q , the number of priority levels, which is presented in the model. And its components are related to unpleasant deviation variables of goal placed in the corresponding priority level. The mathematical formulation of a LGP model

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International Journal of Industrial Engineering, 19(12), 464-474, 2012.

COMPATIBLE COMPONENT SELECTION UNDER UNCERTAINTY VIA EXTENDED CONSTRAINT SATISFACTION APPROACH 1

Duck Young Kim1, Paul Xirouchakis2, Young Jun Son3 Ulsan National Institute of Science and Technology, Republic of Korea 2 École Polytechnique Fédérale de Lausanne, Switzerland 3 University of Arizona, United States Corresponding author email: [email protected]

This paper deals with compatible component selection problems, where the goal is to find combinations of components satisfying design constraints given a product structure, component alternatives available in design catalogue for each subsystem of the product, and a preliminary design constraint. An extended Constraint Satisfaction Problem (CSP) is introduced to solve component selection problems considering uncertainty in the values of design variables. To handle a large number of all possible combinations of components, the paper proposes a systematic filtering procedure and an efficient method to estimate a complex feasible design space to facilitate selection of component combinations having more feasible solutions. The proposed approach is illustrated and demonstrated with a robotic vacuum cleaner design example. Keywords: Component Selection, Configuration, Design Constraint, Constraint Satisfaction Problem, Filtering (Received 24 Apr 2012; Accepted in revised form 1 Nov 2012)

1. INTRODUCTION AND BACKGROUND The product design process involves four main phases: (1) product specification, (2) conceptual design, (3) embodiment design, and (4) detailed design. At each phase, design teams first generate or search for several design alternatives, and select the best one considering design criteria and constraints. In conceptual design, for instance, this generation and selection process consists of four main steps (Pahl and Beitz, 1988) (see Figure 1): (1) decomposition-establish a function structure of a product, (2) definition-search for components to fulfil the subfunctions and define a preliminary design constraint, (3) filtering-combine components to fulfil the overall function, select suitable combinations, and firm up into concept variants, and (4) selection-evaluate concept variants against technical and economic design criteria and select the best one. This divergence and convergence of the search space in design is intended to allow design teams to have unrestrained creativity by producing many initial component alternatives for subsystems, as well as to support the filtering and selection processes to find best design alternatives for a product. The focus of this paper is on “filterning” in Figure 1. In particular, we consdider a constraint based compatible component selection problem under uncertainty in the values of design variables, especially in redesign and variant design environments. This problem is a combinatorial selection problem, where a component satisfying design constraints is chosen for each subsystem from a pre-defined set (i.e. design catalogue). It is compounded by multiple values or continuous space of design variables and discrete choices of components. In this work, it is assumed that a design catalogue (containing component alternatives for subsystems comprising a product) and a preliminary design constraint are given as input information (see Table 3). By generalizing the problem characteristics found, we formulate the constraint based component selection problem with an extended Constraint Satisfaction Problem (CSP). Finally, a systematic filtering procedure and an efficient method to estimate a complex feasible design space are proposed to select component combinations having more feasible solutions. A product usually consists of a number of subsystems (see Table 1), where each of them has its own design alternatives, namely component alternatives. Table 2 lists a major list of variables used in this paper. Any combination of components of all subsystems can be a potential design alternative for a product. The selected components must be mutually compatible to achieve the overall functionality, where compatibility means that when components are designed to work others without adjustment (Patel et al., 2003). Therefore, design teams need to find the compatible combinations of components satisfying design constraints from all possible combinations.

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International Journal of Industrial Engineering, 19(12), 476-487, 2012.

MONITORING TURNAROUND TIME USING AN AVERAGE CONTROL CHART IN THE LABORATORY Shih-Chou Kao Graduate School of Operation and Management, Kao Yuan University, Taiwan Corresponding author email: [email protected] The long turnaround time (TAT) will prolong the waiting time of patient, increase hospital costs and decrease service satisfaction. None of the studies on control charts and medical care have applied control charts to monitor TAT and proposed a probability function for the distribution of the mean. This study proposed a general formula for the probability function of the distribution of the mean. The control limits of the average chart were determined according to the type I risks (α) and the standardized Weibull, lognormal and Burr distributions. Furthermore, compared to control charts that use α=0.0027, weighted variance (WV), skewed correction (SC) and traditional Shewhart control charts, the proposed control chart is superior to other control chart, in terms of the αs for a skewed process. An example of the TAT of laboratory for the medical center presented to illustrate these findings. Significance: This study proposes a control chart to TAT of complete blood count (CBC) test of laboratory for a medical center. Constants of average control chart are calculated in accordance with fixing type I risks( α, 0.0027) with three distributions (Weibull, lognormal and Burr) by using the proposed a general model for the probability density function of the distribution of the mean. Average control chart using the proposed method is superior to other control chart, in terms of the type I risks for a skewed process. Keywords: Average control chart, distribution of the mean, skewed distribution, type I risk, turnaround time. (Received 23 Nov 2011; Accepted in revised form 3 Oct 2012)

1. INTRODUCTION Timeliness is one of the most important characteristics of a laboratory test, but its importance has often been overlooked. The timeliness with which laboratory staffs deliver test results is a manifest parameter of laboratory service and a general standard by which clinicians and organizations judge laboratory performance (Valenstein, 1996). The College of American Pathologists’ Q-Probes study in 1990 identified that the turnaround time (TAT) from phlebotomy to reporting of results is the most important characteristic for laboratory testing and provided TATs for various laboratory tests (Howanitz et al., 1992). Many studies also reported that poor laboratory performance in terms of long TAT had a major impact on patient care (Vacek, 2002; Montalescot et al., 2004; Singer et al., 2005). Until now, essentially all TAT studies have focused on inpatient testing (especially of an emergency nature), outpatient testing and outfits (Howanitz and Howanitz, 2001; Novis et al. 2002; Steindel and Jones, 2002; Novis, 2004; Howanitz, 2005; Chien et al. 2007; Guss et al, 2008; Singer et al. 2008; Qureshi et al, 2010). Most of these studies discussed the main factors that significantly affect the TAT, such as day of the week, drawing location, ordering method and delivery method. Rare research proposed a statistical process control method to monitor the TAT. Valenstein and Emancipator (1989) noted that the distribution of TAT data is non-normal. The skewed nature of TAT data distribution may result in specimens with excessively long TATs (Steindel and Novis, 1999). Hence, if the traditional control charts based on the normality assumption are used to monitor a non–normal process, the probabilities of a type I error (α) in the control charts increases as the skewness of the process increases (Bai and Choi, 1995; Chang and Bai, 2001). Most studies on statistical process control issue used a simulation method to estimate the α and related constant values of an average control chart. No previous research has derived a probability function of the distribution of the mean for a skewed distribution. The study will derive a general formula of the probability density function (pdf) of the distribution of the mean and propose an average control chart that is both simple to use and more effective for monitoring an out–of–control signal for TAT process. In the area of the statistical process control, the α = 0.0027 is a well-known criterion for the design of a control chart or the comparison among control charts. To monitoring a non-normal process, many studies designed some new control charts by splitting the α-risks equally into the two tails (Castagliola, 2000; Chan and Cui, 2003; Khoo ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 2–11, 2013.

A FRAMEWORK FOR SYSTEMATIC DESIGN AND OPERATION OF CONDITION-BASED MAINTENANCE SYSTEMS: APPLICATION AT A GERMAN SEA PORT M. Lewandowski1, B. Scholz-Reiter1 1

BIBA - Bremer Institut für Produktion und Logistik GmbH Germany Corresponding author’s email: Marco Lewandowski, [email protected] Abstract: Ongoing improvement of logistics and intermodal transport leads to high requirements regarding availability of machine resources like straddle carriers or gantry cranes. Accordingly, efficient maintenance strategies for port equipment have to be established. The change to condition-based maintenance strategies promises to save resources while enhancing availability and reliability. This paper introduces a framework of methods and tools that enable the systematic design of condition-based maintenance systems on the one hand and offers integrated support for operating such systems on the other hand. The findings are evaluated based on a case-study of a German seaport and illustrate the usage of the system based on managing the equipping process of machines with sensors for condition monitoring as well as bringing the system into the operation phase. Keywords: Maintenance, Maintenance Management, Condition Monitoring, Condition-based Maintenance, Sensor Application (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION Global distributed production structures and according supply networks have to work efficiently. Sea ports and transhipment terminals, the backbone of Europe’s economy, have to possess lean structures and ensure seamless integration in the supply chain. The ongoing improvement of logistics and intermodal transport with respect to through-put time and cost reductions shall satisfy future demands for scalable structures in times of economic growth and recession. Accordingly, this leads to high requirements regarding efficient maintenance strategies for port equipment like straddle carriers or gantry cranes. While cyclic and reactive maintenance actions are still the representative method in practice, the change to conditionbased monitoring of equipment is ongoing. The current research focuses on condition-based concepts for different applications, including monitoring of tools, pumps, gearboxes, electrical equipment etc. (e.g. Al-Habaibeh et al., 2000; Garcia et al., 2006; García-Escudero et al., 2011). Condition-based maintenance itself promises to make maintenance processes more efficient (Al-Najjar, 2007; Sandborn et al., 2007), among others due to decentralized decision units in terms of cognitive sensor applications at certain crucial components for instance so that the machine itself will be able to trigger a maintenance action in terms of automated control and cooperation (e.g. Scholz-Reiter et al., 2007). Hence, this paper presents the exploration of a fleet management case in a German seaport in which the specific requirements of the design and operating phase were examined and transferred to an adopted systematic procedure model and a methodology framework. The paper is organized as follows: The first chapter introduces the maintenance topic with the specific requirements regarding port equipment. A state of the art review refers to topical work on condition-based maintenance in general and according endeavours to build a comprehensive framework for such systems. Chapter two presents the methodologies that are part of a framework that enables and supports the design and operation of condition-based maintenance systems on top of existing assets. Its application based, on a case study at a German seaport, verifies the applicability in chapter three. The last chapter presents a conclusion on the work done and gives an outlook for necessary further research and work to be done to put such systems into practice. 1.1 Maintenance in General The term maintenance describes the combination of all technical and administrative actions that have to be fulfilled to retain the functioning condition of a technical system or to restore it to a state in which it can perform in the required manner. To this end, the main aim of maintenance is to secure the preferably continuous availability of machines. Based on this definition, the holistic view on the maintenance topic is clear. The several processes based on the typical maintenance tasks according to DIN EN 13306 as presented in the following table 1 consequently require task-specific know-how. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 12–23, 2013.  

A HYBRID SA ALGORITHM FOR INLAND CONTAINER TRANSPORTATION Won-Young Yun1, Wen-Fei Wang2, Byung-Hyun Ha1* 1

Department of Industrial Engineering Pusan National University 30 Jangjeon-Dong, Geumjeong-Gu,Busan 609-735, South Korea *Corresponding author’s e-mail: [email protected] 2 Department of Logistics Information Technology Pusan National University 30 Jangjeon-Dong, Geumjeong-Gu Busan 609-735, South Korea

Abstract: Inland container transportation refers to container movements among customer locations, container terminals, and inland container depots in a local area. In this paper, we consider the inland transportation problem where containers are classified into four types according to the destination (inbound or outbound) and the container state (full or empty). In addition, containers can be delivered not only by truck but also by train when time windows are satisfied. We propose a graph model to represent and analyze the problem, and develop a mixed-integer programming model based on the graph model. A hybrid simulated annealing algorithm is proposed to obtain the near-optimal transportation schedule of containers. The performance of the proposed algorithm is investigated by numerical experiments. Keywords: Inland container transportation; time windows; intermodal transportation; hybrid simulated annealing (SA) (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION By inland transportation, containers are transported from their shippers to a terminal and delivered from another terminal to their receivers. This study deals with the inland container transportation problem by taking the total transportation cost into account. We consider four types of containers: inbound full, outbound full, inbound empty, and outbound empty ones. The transportation process depends on the type of a container. For example, outbound freight transportation by a container is briefly described as follows. First, a truck is assigned to carry an empty container to a customer and the empty container is unloaded at the customer location. Then, freight is packed into the container and the container becomes a full one. The full container is loaded onto the truck again and delivered to a terminal directly or a railway station where the container is transported to a terminal by train subsequently. Finally, the container is transferred to another terminal by vessel, where the container gets into another inland container transportation system. In addition, we consider multimodal transportation by truck and train, and further impose the constraint of time windows when a container can be picked up and unloaded at its origin and destination, respectively. Hence, containers can be delivered either by truck or by truck and train together, as long as time windows are satisfied. There are many papers in which various methods are proposed to find the optimal or good solutions for the inland container transportation problem. Wen and Zhou (2007) developed a GA (genetic algorithm) to solve a container vehicle routing problem in a local area. Jula et al. (2005) formulated truck container transportation problems with time constraints as an asymmetric multi-traveling salesman problem with time windows (m-TSPTW). They applied a DP/GA (dynamic programming and genetic algorithm) hybrid algorithm for solving large size problems. Zhang et al. (2009) addressed a similar problem, a graph model was built up, and a cluster method and a reactive tabu search were proposed and compared their performance with each other. Liu and He (2007) decomposed a vehicle routing problem into several sub-problems according to vehicle-customer assignment structure and a tabu search algorithm was applied to each sub-problem, respectively. Intermodal transportation problems with time windows are more difficult to deal with, especially when a container is related to more than one time window. Some researchers tried to transform and/or to relax the constraints related to time windows. Lau et al. (2003) considered the vehicle routing problem with time windows under a limited number of vehicles, and they provided a mathematical model to obtain the upper bound by selecting one of the latest-possible times to return to ISSN  1943-­‐670X  

 

 

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International Journal of Industrial Engineering, 20(1-2), 24–35, 2013.

A METHOD for SIMULATION DESIGN of REFRIGERATED WAREHOUSES USING AN ASPECT-ORIENTED MODELING APPROACH G.S. Cho1, H.G. Kim2 1

Department of Port Logistics System, Tongmyong University, Busan, 608-711, Korea 2 Department of Industrial & Management Engineering, Dongeui University, Busan, 614-714, Korea Corresponding author’s e-mail: GS Cho, [email protected] Refrigerated warehouses play a buffer function in a logistics system to meet the various demands of consumers. Over 50% of Korean refrigerated warehouses are located in Busan, and Busan has become a strategic region for cold chain industries. This paper suggests an Aspect-Oriented Modeling Approach (AOMA) for refrigerated warehouses which can design and analyze system models using a simulation method considering the design conditions. Significance: The AOMA is an analytic approach that combines the Aspect-Oriented Modeling considering cross cutting concerns to the existing Object-Oriented Modeling. The purpose of this paper is to suggest a simulation model using the AOMA for refrigerated warehouses. The suggested model can be utilized for redesigning refrigerated warehouses for the easy control of reuse, extension and modification. Keywords: Simulation, Refrigerated Warehouse, System Operation, Aspect-Oriented Modeling Approach. (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION 1.1 Background and Purpose of this Research The refrigerated warehouse industry has grown as the consumption of fresh foods has increased. The Busan area in Korea has become a strategic region for the refrigerated warehouse industry. Many refrigerated warehouses have been built since 2000s to meet the demands but the refrigerated warehouse industry has been in trouble due to the excessive facilities, shared stevedoring and lower storage fees etc. (Kim et al., 2010). So, it is needed that the refrigerated warehouse should support the high value-added service to customers but so far the function of a refrigerated warehouse is only focused on storing the items. Although the minimum necessity is to consider the design factors such as layouts, facilities and items etc., there are needed operating alternatives as a system, to enhance the operations and performance of refrigerated warehouses supporting the services. Until now the main function of refrigerated warehouses is restricted to storing and there has not been any systematic approach method to solve the above mentioned problems. For the complex system, Object-Oriented Modeling (OOM) has been utilized in other industrial system (Venketeswaran and Son, 2004). The OOM along with applications in the computer science area has long been the essential reference to object-oriented technology, which, in turn, has evolved to join the mainstream of industrial-strength software development. The OOM is a modeling paradigm mainly used in computer programming. The OOM emphasizes the use of discreet reusable code blocks that can stand on their own, take variables, perform a function, and return values. AspectOriented Modeling (AOM) that is an extension of the OOM may also contain interfaces to each model because they also involve method interactions (Lemos et al., 2009). Such modeling techniques help separate out the different concerns implemented in a software system and especially some that cannot be clearly mapped to isolated units of implementation. The main idea of the AOM is suggested to improve the performance of the OOM for realizing the modularization of these types of concerns. The terms of the AOM can be used to demonstrate the space of programmatic mechanisms for expressing crosscutting concerns (Kiczales et al., 1997). The AOM should be built upon a conceptual framework and is able to denote the space of modeling elements for specifying crosscutting concerns at a higher level of abstraction (Chavez and Lucena, 2002). Recently an Aspect-Oriented Modeling Approach (AOMA) has been suggested and applied to enhance the performance of the simulation models based on the AOM (France et al., 2004, Wu et al., 2010). In this paper, we suggest and develop a prototype system which implements the class model composition behavior specified in the composition metamodel to design the refrigerated warehouse system using the AOMA. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 36–46, 2013.

A MULTI-PRODUCT DYNAMIC INBOUND ORDERING AND SHIPMENT SCHEDULING PROBLEM AT A THIRD-PARTY WAREHOUSE B. S. Kim1, W. S. Lee2 1

Graduate School of Management of Technology Pukyong National University Busan 608-737, Korea 2 Department of Systems Management & Engineering Pukyong National University Busan 608-737, Korea Corresponding Author’s Email: [email protected]

Abstract: This paper considers a dynamic inbound ordering and shipment scheduling problem for multiple products that are transported from a supplier to a warehouse by common freight containers. The following assumptions are made: (i) each ordering in a period is immediately shipped in the same period, (ii) the total freight cost is proportional to the number of containers used, and (iii) demand is dynamic and backlogging is not allowed. The objective of this study is to identify effective algorithms that simultaneously determine inbound ordering lot-sizes and a shipment schedule that minimize the total cost consisting of ordering cost, inventory holding cost, and freight cost. This problem can be shown in NP-hard, and this paper presents a heuristic algorithm that exploits the properties of an optimal solution. Also, a shortest path reformulation model is proposed to obtain a good lower bound. Simulation experiments are presented to evaluate the performance of proposed procedures. (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION For the couple of decades, the reduction of transportation cost and warehousing cost have been two important issues to enhance logistic efficiency and demand visibility in a supply chain. The logistic alliances and specialized Third-PartyLogistic (TPL) providers have been growing to reduce the costs in industry. In a dynamic planning period, the issue of transportation scheduling for inbound ordering and shipping of products to TPL warehouse by proper transportation modes at scheduled time and the issue of lot size dispatching control including inventory control to the customers have become significantly important for production and distribution management. Each warehouse purchases multiple products and uses a freight container as a transportation unit to ship its purchased (or manufactured) products to retailers, which may lead to the managerial decision problems including lot-sizes for each product, container types used, loading policy in containers, and the number of containers used. Thus, this provides us with a motivation to investigate the optimal lot-sizing and shipment scheduling problem. Also, the managerial decision problems have arisen in TPL. Several articles have attempted to extend the classical Dynamic Lot-Sizing Model (DLSM) incorporating production-inventory and transportation functions together. Hwang and Sohn (1985) investigated how to simultaneously determine the transportation mode and order size for a deteriorating product without considering capacity restrictions on the transportation modes. Lee (1989) considered a DLSM allowing multiple set-up costs consisting of a fixed charge cost and a freight cost, in which a fixed single container type with limited carrying capacity is considered and the freight cost is proportional to the number of containers used. Fumero and Vercellis (1999) proposed an integrated optimization model for production and distribution planning considering such operational decisions as capacity management, inventory allocation, and vehicle routing. The solution of the integrated optimization model was obtained using the Lagrangean relaxation technique. Lee et al. (2003) extended the works of Lee (1989) by considering multiple heterogeneous vehicle types to immediately transport the finished product in the same period it is produced. It is also assumed that each vehicle has a type-dependent carrying capacity and the unit freight cost for each vehicle type is dependent on the carrying capacity. Lee et al. (2003) considered a dynamic model for inventory lot-sizing and outbound shipment scheduling in the third-party warehousing domain. They presented a polynomial time algorithm for computing the optimal solution. Jaruphongsa et al. (2005) analyzed a dynamic lot-sizing model in which replenishment orders may be delivered by multiple shipment modes with different lead times and cost functions. They proposed a polynomial time algorithm based on the dynamic programming approach. However, the aforementioned works have not considered a multiple product problem. Emily and Tzur (2005) considered a dynamic model of shipping multiple items by capacitated vehicles. They presented an algorithm based on a dynamic programming approach. Norden and Velde (2005) dealt with a multiple product problem of determining transportation lot-sizes in which the transportation cost function has piece-wise linear ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 47–59, 2013.  

A STRUCTURAL AND SEMANTIC APPROACH TO SIMILARITY MEASUREMENT OF LOGISTICS PROCESSES Bernardo Nugroho Yahya1,3, Hyerim Bae1*, Joonsoo Bae2 1

Department of Industrial Engineering Pusan National University 30-san Jangjeon-dong, Geumjong-gu, Busan 609-735, South Korea *Coressponding author’s email: {bernardo;hrbae}@pusan.ac.kr 2 Department of Industrial and Information Systems Engineering Chonbuk National University 664-14 Deokjin-dong, Jeonju, Jeonbuk 561-756, South Korea. [email protected] 3 School of Technology Management Ulsan National Institute of Science and Technology UNIST-gil 50, Eonyang-eup, Ulju-gun, Ulsan 689-798, South Korea [email protected]

Abstract: The increased individuation and variety of logistics processes has spurred a strong demand for a new process customization strategy. Indeed, to satisfy the increasingly specific requirements and demands of customers, organizations have been developing more competitive and flexible logistics processes. This trend not only has greatly increased the number of logistics processes in process repositories but also has resulted processes for business decision making hard. Organizations, therefore, have turned to process reusability as a solution. One such strategy employs similarity measurement as a precautionary measure limiting the occurrence of redundant processes. This paper proposes a structureand semantics-based approach to similarity measurement of logistics processes. Semantic information and semantic similarity on logistics processes are defined based on logistics ontology, available in the supply chain operation reference (SCOR) model. By combining similarity measurement based on both structural and semantic information of logistics processes we show that our approach improves the previous approaches in terms of accuracy and quality. Keywords: Logistics process, SCOR, similarity measurement, business process, logistics ontology (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION To adapt to dynamic business conditions and achieve a competitive advantage, a logistics organization must implement customized processes that meet customer requirements and that also further its business objectives. Thus, it could be said that process customizability is integral to an organization’s competitive advantage. We define customizability as the ability of the logistics party to apply logistics process objectives to many different business conditions (Lee and Leu (2010)). Customization of reference processes or templates to reduce the time and effort required to design and deploy processes on all levels is common practice (Lazovik and Ludwig (2007)). Customization of reference processes usually involves adding, removing or modifying process elements such as activities, control flow and data flow connectors. However, the existence of a large number of customized processes can incur process redundancy. For example, many similar processes with only slight differences in terminology, structure and semantics can exist in maritime supply chains involving the handling of containers. In such environments, the establishment of joint procedures among several global communities such as the International Association of Ports and Harbors (IAPH), the International Network of Affiliated Ports (INAP) and the North American Inland Port Network (NAIPN) can increase the process redundancy in some way. For example, the three ports of the country of origin, hub and destination belong to the same global communities (Fig. 1). The conceptual processes of container flows at the hub and the destination are the same; however, their operational processes might differ slightly according to the respective performers, which is to say, the country’s relevant laws, port’s processing capacities, and other factors. When the ports are in the same communities, they are supposed to have either similar or standardized processes to handle container flows. The existence of similar or standard processes inspires port community members to reuse existing processes instead of creating new ones. In this sense, process redundancy encourages organizations to prioritize process reusability. Process reusability is the ability to develop a process model once and use it ISSN  1943-­‐670X  

 

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International Journal of Industrial Engineering, 20(1-2), 60–71, 2013.

FUZZY ONTOLOGICAL KNOWLEDGE SYSTEM FOR IMPROVING RFID RECOGNITION H. K. Lee1, C. S. Ko2, T. Kim3*, T. Hwang4 1

Research associate [email protected], 2Professor [email protected], 3Professor [email protected], 4Professor [email protected] 1-3 Department of Industrial & Management Engineering, Kyungsung University 314-79 Daeyeon-3 dong, Nam-gu, Busan, Korea 4 Department of Civil Engineering, Dongeui University 176 Eumkwang-ro, Jin-gu, Busan, Korea

To remain competitive in business and to be quick responsive in the warehouse and supply chain, the use of RFID has been increasing in many industry areas. RFID can identify multiple objects simultaneously as well as identifying individual objects respectively. Some limitations of RFID still remain in the low recognition rate and the sensitive response according to the material type and its ambient environment. Much effort has been made to enhance the recognition rate and to be more robust. Examples include tag design change, antenna angle, search angle, and signal intensity to name a few. The paper proposes fuzzy logic based ontological knowledge system for improving the recognition rate of RFID and the variance of recognition. In order to improve a performance and reduce a variance, the following sub-goals are pursued. First, ontology is constructed for the environmental factors to be used as a knowledge base. Second, fuzzy membership function is defined using the Forward Link Budget in RFID. Finally, a conceptual knowledge system is proposed and tested to verify the model in the experimental environment. Keyword: RFID, Performance, Identification, Ontology, SWRL, Fuzzy (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION The radio frequency identification (RFID) technology allows remote identification of objects using radio signal, thus without the need for line-of-sight or manual positioning of each item. With the rapid development of RFID technology and its application, we expect a brighter future in the object identification and control. The major advantage of RFID technology over the barcode is that the RFID system allows detection of multiple items simultaneously as they pass through a reader field. Additionally, each physical object has its unique ID (even two products of the same type have two different IDs) enabling to precisely track and monitor the position of each individually labeled product piece. There is no doubt that the RFID technology has paid off in some areas. But, the effect is not so big in the industry wide as it has been expected earlier. One of the limitations is the recognition rate of RFID. There are many environmental factors affecting the performance of RFID. They are material type, packaging type, tag type, reader type and tag location to name a few. As the variables affecting the RFID performance are unpredictable in advance and changes according to the domain, a high demand exists in a reusable and robust knowledge system. An ontology is a formal representation of the knowledge by a set of concepts within a domain and the relationships between those concepts. It is used to reason about the properties of that domain, and may be used to describe the domain. An ontology provides a shared vocabulary, which can be used to model a domain — that is, the type of objects and/or concepts that exist, and their properties and relations. The focus of the ontology lies on the representation of the RFID domain. The ontology can act as a model for exploring various aspects of the domain. Since part of the ontology deals with the classification of RFID applications and requirements, it can also be used for supporting decisions on the suitability of particular RFID tags for different applications. Previous researches of RFID include RFID device, middleware, agent, ontology and industrial applications. Pitzek (2010) focused ontologies as the representation of the domain for informational purposes, i.e., as a conceptual domain model, and putting it into context with other domains, such as communication capable devices and automatic identification ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 72–83, 2013.

COLLABORATION BASED RECONFIGURATION OF PACKAGE SERVICE NETWORK WITH MULTIPLE CONSOLIDATION TERMINALS C. S. Ko1, K. H. Chung2, F. N. Ferdinand3, H. J. Ko4 1

Department of Industrial & Management Engineering Kyungsung University 309, Suyeong-ro, Nam-gu Busan, 608-736, Korea e-mail: [email protected] 2 Department of Management Information Systems Kyungsung University 309, Suyeong-ro, Nam-gu Busan, 608-736, Korea e-mail: [email protected] 3 Department of Industrial Engineering Pusan National University Busandaehak-ro, Geumjeong-gu Busan, 609-935, Korea e-mail: [email protected] 4 Department of Logistics Kunsan National University 558 Daehangno, Gunan Jeonbuk, 573-701, Korea Corresponding author’s e-mail: [email protected]

Abstract: The market competition of package deliveries in Korea is severe because a large number of companies have entered into the Korean market. A package delivery company in Korea generally owns and operates a number of service centers and consolidation terminals for high level customer service. However, some service centers cannot create profits due to low volume acting as the facilities raising the costs. This challenge can be overcome by collaboration strategy in order to improve its competitiveness. In this regard, this study suggests an approach to the reconfiguration of package service networks with respect to collaboration strategy. Thus, we propose a multi-objective nonlinear integer programming model and a genetic algorithm-based solution procedure for participated companies to maximize their profit. An illustrative numerical example in Korea is presented to demonstrate the practicality and efficiency of the proposed model. Keyword: network reconfiguration, express package delivery, cutoff time, strategic partnership (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION The market of express package deliveries in Korea has been rapidly expanded according to the progress of TV home shopping and internet buying and selling. Accordingly, various sized domestic express companies have been established, and various foreign companies also have entered into the Korean express market. As a result of the surplus of express companies, they are struggling with remaining competitive at a reasonable price with appropriate level of customer satisfaction. In this regard, collaboration or partnership strategy can be a possible option in order to overcome such difficulties. The collaboration or partnership is becoming a popular competitive strategy to be adopted in all business sectors. Some of well-known examples can be seen in the air transportation system such as Sky Team, Star Alliance, and Oneworld as well as in sea transportation such as CKYH-The Green Alliance, Grand Alliance, and so on. In addition, the supply chain management regards the concept of collaboration as a critical factor for its successful implementation. In Korea, an express company generally operates its own service network which consists of customer zones, service centers, and consolidation terminals. Customer zones refer to geographical districts in which customers either ship or receive packages and are typically covered by a service center. And a service center receives customer shipment requests and picks up parcels from customer zones and then the packages are waited until its cutoff time for transshipment in bulk to a consolidation terminal. In this way, the service center acts as a temporary storage facility connecting customers to a ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 84–98, 2013.

COMPARISON OF ALTERNATIVE SHIP-TO-YARD VEHICLES WITH THE CONSIDERATION OF THE BATCH PROCESS OF QUAY CRANES S. H. Choi1, S. H. Won2, C. Lee3 1

Port Management/Operation & Technology Department, Korea Maritime Institute 1652, Sangam-dong, Mapo-gu, Seoul, South Korea 2 Department of Logistics, Kunsan National University 558 Daehangno, Gunsan, Jeonbuk, South Korea 3 School of Industrial Management Engineering, Korea University Anam-dong, Seongbuk-gu, Seoul, South Korea Corresponding author’s email: Seung Hwan Won, [email protected]

Container terminals around the world fiercely compete to increase their throughput and to accommodate new mega vessels. In order to increase the port throughput drastically, new quay cranes capable of batch processing are being introduced. The tandem-lift spreader equipped with a quay crane, which can handle one to four containers simultaneously, has recently been developed. Such increase in the handling capacity of quay cranes requires significant increase in the transportation capacity of ship-to-yard vehicles as well. The objective of this study is to compare the performances of three alternative configurations of ship-to-yard vehicles in a conventional container terminal environment. We assume that the yard storage for containers is horizontally configured and the quay cranes equip with tandem-lift spreaders. A discrete event simulation model for a container terminal is developed and validated. We compare the performances of the three alternatives under different cargo workloads and profiles, represented by different annual container handling volumes and different ratios of tandem mode operations, respectively. The results show that the performances of the alternative vehicle types are largely dependent on workload requirement and profile. Keywords: ship-to-yard vehicle; simulation; container terminal; quay crane; tandem-lift spreader (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION As the size of trade between countries increased, there are rapid changes in the logistics environment concerning ports. The world container traffic in 2008 is 540 million TEUs, which grew by 2.3 times compared to 230 million TEUs in 2000. It is forecasted to achieve growth rate of around the annual average of 9% by 2013. Due to this, the marine transportation industry has made Mega-Carrier appear through mergers and acquisitions between shipping lines to expand market dominance, and they are continuing to make enormous investments for securing mega ships over 10,000 TEUs in order to strengthen the competitiveness in shipping cost. According to such changes in the shipping environment, large ports in the world are engaging in fierce competition for hub ports by continents to attract mega fleet, and this is leading to the trend of strengthening port competitiveness through the securing and operation of efficient port facilities. In other words, the world’s leading ports such as Singapore, Shanghai, Hong Kong, Shenzhen, Busan, Rotterdam, and Hamburg are not only developing large-sized terminals but also investing highly productive handling equipment for the efficiency of port operation. The handling equipment in a port generally consists of quay cranes (QCs), ship-to-yard vehicles (terminal trucks or automated guided vehicles), and yard cranes (YCs). Out of these, QCs and ship-to-yard vehicles are most closely related to ships. These are the most important factors that determine the ship turnaround time in a port. Berthing a mega ship over 10,000 TEUs in a port requires water depth, the workable specification of QCs, and the high productivity of a terminal. Despite increasing the size of ships, shipping lines tend to require the service time in the past. Therefore, ports unable to meet the trend of such customer requirements may bring about the desertion of customers. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 99–113, 2013.

A HIERARCHICAL APPROACH TO VEHICLE ROUTING AND SCHEDULING WITH SEQUENTIAL SERVICES USING THE GENETIC ALGORITHM K. C. Kim1, J. U. Sun2, S. W. Lee3 1

School of Mechanical, Industrial & Manufacturing Engineering, Oregon State University, USA 2 School of Industrial & Management Engineering, Hankuk University of Foreign Studies, Korea 3 Department of Industrial Engineering, Pusan National University Korea Corresponding author’s email: [email protected]

Abstract To survive in today’s competitive market, material handling activities need to be planned carefully to satisfy business’ and customers' demand. The vehicle routing and scheduling problems have been studied extensively for various industries with special needs. In this paper, a vehicle routing problem considering unique characteristics of the electronics industry is considered. A mixed-integer nonlinear programming (MINP) model has been presented to minimize the traveling time of delivery and installation vehicles. A hierarchical approach using the genetic algorithm has been proposed and implemented to solve problems of various sizes. The computational results show the effectiveness and the efficiency of the proposed hierarchical approach. A performance comparison between the MINP approach and the hierarchical approach is also presented. Keywords: Vehicle Routing Problem, Delivery and Installation, Synchronization of Vehicles, Genetic Algorithm, Electronics Industry (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION To survive in this competitive business environment, a company must have ways to handle various materials of concern cost-effectively. In manufacturing industries, material handling activities for raw materials and works-in-process are as important as the ones for final products. So that material handling activities satisfy business’ and customers' demand effectively, the vehicle routing and scheduling problems have been studied and implemented extensively for various industries with special needs (Golden and Wasil, 1987; List and Mirchandani, 1991; Chien and Spasovic, 2002; Zografos and Androutsopoulos, 2004; Ripplinger, 2005; Prive et al, 2006; Claassen and Hendricks, 2007; Ji, 2007). In this paper, a variant of the vehicle routing problems (VRP), which has been characterized in the electronics industry to satisfy its unique material handling needs as the paradigm of distribution has been shifted from the past, has been presented. In recent days, the electronics industry experiences rapidly-emerging changes in their post-sales service, i.e., delivery and installation. In the past, local stores individually are responsible for the services of the delivery and the installation. However, due to the growing demand of direct orders from customers and the increasing complexity of advanced electronics products, electronics manufacturers are acceleratingly required to directly deliver their goods to customers and to provide on-site professional installation. The sales of electronics via e-commerce, large discount stores, general merchandise stores, department stores, and etc. are very rapidly increasing. In addition, electronics manufacturers put intensive efforts to increase sales through professional electronics franchises like Staples, OfficeMax, and etc., which do not provide such delivery and installation. These trends tend to add the responsibilities of the delivery and the installation onto electronics manufacturers, and the number of direct deliveries from electronics manufacturers to customers increases at an explosive pace. Another unique characteristic of the electronics industry can be identified in installation service. Some products like airconditioners have required the professional installation service even in the past. Many newly-emerging products require not ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 114–125, 2013.

THE PROBLEM OF COLLABORATION IN MANUFACTURED GOODS EXPORTATION THROUGH AUTONOMOUS AGENTS AND SYSTEM DYNAMIC THEORIES V. M. D. Silva1, A. G. Novaes2, B. Scholz-Reiter3, J. Piotrowski3 1

Department of Production Engineering Federal Technological University of Paraná, Ponta Grossa, PR, 84016-210, Brazil Corresponding author’s e-mail: [email protected] 2 Federal University of Santa Catarina Florianopolis, SC, 88040-900 Brazil e-mail: [email protected] 3 Bremen Institut for Production und Logistic BIBA- University of Bremen, Hochschulring 20, 28359, Bremen, Germany e-mail: [email protected] e-mail: [email protected]

Abstract: Along export chains transportation has an important cost impacting directly on the efficiency of the whole chain. Experiments show satisfactory results in terms of reduced delivery time, increased productivity of transportation resources as well as economies of scale by the implementation of the Collaborative Transportation Management (CTM). In this context, this incipient study intends to present a real Brazilian problem about exports of manufactured products using maritime transportation, as well as introducing the concept of CTM as a tool for helping companies on their decision making. It identifies the major parameters that could support the maritime logistics of manufactured products and, the Autonomous Agents and System Dynamics theories are described as possible methods to model and analyze this logistic problem. As a result for this preliminary study, is intended to awake the readers interest about these emergent concepts applied to such important problem to contribute with the costs reduction of the exports chain. Key-Words: Collaborative transportation management, Manufactured exporters, Maritime shippers, Autonomous agents, Decision-making, System Dynamics (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION In Brazil, the foreign trade has been not used as pro-active factor in development strategy because, historically, the negotiations between the different participants of the export chain have presented conflicts. It is observed that each link intend to minimize its individual costs, which normally does not converge to the global optimum of the supply chain. Therefore, companies are being obliged to re-analyze its procedures, to use reengineering techniques and redefine the relations and models of its supply chains to reduce costs, increase efficiencies and gain competitive advantage. To reduce such problems it has recently emerged the concept of CTM, in the new concept of collaborative logistics. It has been spread out from the year 2000 through Collaborative Planning, Forecasting and Replenishment (CPFR) approach, and CTM has been defined by experts as a helpful tool to provide reductions in the costs of transactions and risks, enhance the performance of service and capacity, as well as the achievement of a more dynamic supply chain (Silva et al., 2009). As the exporter Brazilian companies are looking for higher competitiveness, they shall not act in an individual manner and start acting in a collaborative manner. Therefore, it is required a detailed sharing of data and information by the agents of the logistics chain to compose a solid partnership. It is understood as agent each integrant of this chain, as in the maritime logistics chain: the producer company, road transportation, shipowners and maritime shippers. After bibliographic studies and contacting entrepreneurs of this area, it is verified that there is restrict scientific work exploring this subject comprising manufactory industries, freight contractors and maritime shippers, in order to contribute with exportation. Therefore, this study, which is part of a Ph.D. thesis in development, intends to summarily present an overview of the Brazilian exportation and its operation of manufactured exportation chain using maritime shippers, the ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 126–140, 2013.  

EVOLUTION OF INTER-FIRM RELATIONSHIPS: A STUDY OF SUPPLIER-LOGISTICAL SERVICES PROVIDER-CUSTOMER TRIADS P. Childerhouse1, W. Luo1, C. Basnet1, H. J. Ahn2, H. Lee3, G. Vossen4 1

Department of Management Systems, Waikato Management School, University of Waikato, Hamilton 3216, New Zealand 2 College of Business Administration, Hongik University, Seoul, Korea 3 Brunel Business School, Brunel University, Uxbridge, Middlesex, UK 4 School of Business Administration and Economics, University of Muenster, 48149 Muenster, Germany Corresponding author’s email: Paul Childerhouse, [email protected] The concept of supply chain management has evolved from focussing initially on functional co-ordination within an organisation, then to external dyadic integration with suppliers and customers and more recently towards a holistic network perspective. The focus of the research described in this paper is to explore how and why relationships within supply chain networks change over time. Since a triad is the simplest meaningful sub-set of a network, we use triads as the unit of analysis in our research. In particular, we consider triads consisting of a supplier, their customer, and the associated logistics services provider. An evolutionary triadic model with eight relational states is proposed and the evolutionary paths between the states hypothesised, based on balance theory. The fundamental role of logistical service providers is examined within these alternative triadic states with a specific focus on the relationships between the actors in the triad. Empirical evidence is collected from three very different triads and cross-referenced with our proposed model. How the interactions and relationships change over time is the central focus of the case studies and the conceptual model. Our findings indicate that some networks are more stable than others and depending on their position in a triad some actors can gain power over their business partners. Further, those organisations that act as information conduits seem to have greater capacity to influence their standing in a supply chain network. Significance: We make conceptual contribution to supply network theory, as well as reporting empirical investigation of the theory. Keywords:

Supply networks, Inter-firm relationships, Triads, Balance theory, Logistical service providers. (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION This paper investigates inter-firm relationships from a social network perspective. In particular, we examine the relationship dynamics of a network of inter-connected firms with shared end consumers. The social network perspective has gained significant momentum in the management literature (Wang and Wei, 2007). In this paper, we use the psychological concept of balance theory (Simmel, 1950; Heider, 1958) to make sense of the dynamic interrelationships in a supply chain network. The most important dimensions of change in business networks that will be focussed upon concern the development of activity links, resources ties, and actor relationship bonds (Gadde and Hakansson, 2001). A triad is the smallest meaningful sub-set of a network (Madhavan, Gnyawali and He, 2004) and as such will be used as the unit of analysis throughout this paper. Figure 1 is a simplistic representation of the multi-layered complex business interactions that make up supply chain networks. The actors are represented by nodes (circles) and the connections between them as links. A triadic sub-set of the entire network is illustrated as the grey shaded area in Figure 1. Three actors, ‘A,’ ‘B,’ and ‘C’ are highlighted and their three links, ‘A’ with ‘B,’ ‘A’ with ‘C’ and ‘B’ with ‘C.’ Each actor also has a potential mediating role in the relationship between the other two as indicated by the dashed arrow from actor ‘A’ to the link between ‘B’ and ‘C.’ Thus, we contend that a representative sub-set of a network can be investigated via triads. This cannot be said for dyads, which overly simplify the social complexities of real world business interactions. ISSN  1943-­‐670X  

 

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International Journal of Industrial Engineering, 20(1-2), 141–152, 2013.  

OPERATION PLANNING FOR MARITIME EMPTY CONTAINER REPOSITIONING Y. Long1, L. H. Lee2, E. P. Chew3, Y. Luo4, J. Shao5, A. Senguta6, S. M. L. Chua7 1,2,3,4,5

Department of Industrial and Systems Engineering, National University of Singapore, Singapore,119260 1 Corresponding author’s email: [email protected] 2 [email protected] 3 [email protected] 4 [email protected] 5 [email protected] 6,7 Neptune Orient Lines Ltd., Singapore,119962 6 [email protected] 7 [email protected]

Abstract One of the challenges that liner operators face today is to effectively operate empty containers to meet demands and to reduce inefficiency. In this study, we develop a decision support tool to help the liner operator in managing the maritime empty container repositioning efficiently. This tool considers the actual operations and constraints of the problems faced by the liner operator and uses mathematical programming approaches to solve it. We present a case study, which considers 49 ports and 44services.We also compare our proposed model with a simple rule, which attempts to mimic the actual operation of a shipping liner. The numerical results show that the proposed model is promising. Moreover, our model is able to identify potential transshipment hubs for intra-Asia empty container transportation. Keywords Empty Container Repositioning Optimization Network Transshipment Hub Decision Support Tool (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION Since 1970s, containerization has become increasingly popular in global freight transportation activities, especially in international trade routes. Containerization helps to improve port handling efficiency, reduce handling costs, and increase trade flows. To increase the utilization of containers, containers should be reloaded with new cargoes as soon as possible after reaching its destination. However, this is not always possible due to the trade imbalance between different regions in the world and this has resulted in holding large inventory of empty containers by ocean liners and thereby increasing the operating cost. Generally export-dominated ports need a large number of empty containers, while import-dominated ports hold a large number of surplus empty containers. Under this imbalanced situation, a profitable movement of a laden container usually generates an unprofitable empty container movement. The main challenge is when and how many empty containers we should move from the import-dominated ports to export-dominated ports to meet the customer demands while reducing the operational cost. There are a large number of studies on the empty container repositioning problem. One area is to use inventory-based control mechanisms for empty container management (e.g., Li et al., 2004; Song, 2007; Song and Earl, 2008). Another area is to apply dynamic network programming methods to container management problem (e.g., Lai et al., 1995; Shen and Khoong, 1995; Shitani et al., 2007; Liu et al., 2007; Erera et al., 2009). Some studies of this area focus on inland container flow (e.g., Crainic et al., 1993; Jula et al., 2006), while some studies are on maritime transportation (e.g., Francesco et al., 2009). Besides, there are studies developing intermodal models, which consider both inland and maritime transportation (e.g., Choong et al., 2002; Erera et al., 2005; Olive et al., 2005).The general maritime network model for empty container repositioning was proposed by Cheung and Chen (1998).They develop a time space network model and their study paves the way for maritime empty container repositioning network modeling. To apply the general networking techniques to the shipping industry, researchers tend to consider the actual services and the real scale network in the latest decade. Actual service schedule is considered in Lam et al. (2007). They develop an approximate dynamic programming approach in deriving operational strategies for the relocation of empty containers. Although actual services schedule is considered in their study, the proposed dynamic approximation programming is limited to a small scale problem. One paper that ISSN  1943-­‐670X  

 

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International Journal of Industrial Engineering, 20(1-2), 153–162, 2013.

OPTIMAL PRICING AND GUARANTEED LEAD TIME WITH LATENESS PENALTIES K. S. Hong1, C. Lee2 1,2

Division of Industrial Management Engineering Korea University Anamdong 5-ga, Seongbuk-gu, 136-713 Seoul, Republic of Korea 1 [email protected] 2 Corresponding author’s e-mail: [email protected]

This paper studies the price and guaranteed lead time decision of a supplier that offers a fixed guaranteed lead time for a product. If the supplier is not able to meet the guaranteed lead time, the supplier must pay a lateness penalty to customers. Thus, the expected demand is a function of the price, guaranteed lead time and lateness penalty. We first develop a mathematical model for a given supply capacity to determine the optimal price, guaranteed lead time and lateness penalty to maximize the total profit. We then consider the case where it is also possible for the supplier to increase capacity and compute the optimal capacity. Keyword: Time-based competition, Guaranteed lead time, Pricing, Lateness penalty decision, Price and time sensitive market (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION Increased competition has forced service providers and manufacturers to introduce new products into the market and time has evolved as a competitive paradigm (Blackburn 1991, Hum and Sim 1996). As time has become a key to business success, lead time reduction has emerged as a key competitive edge in service and manufacturing (Van Beek and Van Putten 1987, Suri 1998, Hopp and Spearman 2000, White et al. 2009). This new competitive paradigm is termed as timebased competition. Suppliers exploit customers’ sensitivity to time to increase prices in return for shorter lead time. For instance, amazon.com charges more than double the standard shipping costs to guarantee delivery in two days, while its normal delivery time may be as long as a week (Ray and Jewkes, 2004). Likewise, suppliers differentiate their products based on lead time in order to maximize the supplier’s revenue (Boyaci and Ray, 2003). In this case, the lead time reduction provides suppliers with new opportunities. Additionally, in today’s global economy, suppliers are increasingly dependent on fast response time as an important source of sustainable competitive advantage. As a result, one needs to consider the influence of lead time on demand. This paper considers a supplier that is using guaranteed lead time to attract customers and supply a product in a price and time sensitive market. Time-based competition was first studied by Stalk and Hout (1990) who addressed the effect of time as strategic competitiveness. Hill and Khosla (1992) developed an optimization model to calculate the optimal lead time reduction, and compares the costs and benefits of lead time reduction. Palaka et al. (1998), So and Song (1998) and Ray and Jewkes (2004) assumed that demands are sensitive to both the price and the guaranteed lead time, and investigated the optimal pricing and guaranteed lead time decisions. Palaka et al. (1998) employed an M/M/1 queueing model, and developed a mathematical model to determine the optimal guaranteed lead time, the capacity utilization and the price with a linear demand function. So and Song (1998) extended the Palaka et al’s. (1998) results to consider a log-linear (CobbDouglas) demand function, and analyzed the impact of using delivery time guarantees as a competitive strategy in service industries. Ray and Jewkes (2004) assumed that the mean demand rate is a function of price and guaranteed lead time, and the price is determined by the length of the lead time, and developed the optimization model to determine the optimal guaranteed lead time. They also extended their results by incorporating economies of scale where the unit operating cost is a decreasing function of the mean demand rate. So (2000), Tsay and Agarwal (2000), Pekgun et al. (2006) and Allon and Federgruen (2008) also developed a mathematical model to determine the optimal price and the optimal guaranteed lead time in a competitive setting where suppliers selling a product compete on price and lead time. However, their models do not consider the lateness penalty decision. When suppliers employ a guaranteed lead time strategy, they may have to pay the lateness penalty to customers ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 163–175, 2013.

OPTIMAL CONFIGURATION OF STORAGE SYSTEMS FOR MIXED PYRAMID STACKING D. W. Jang1, K. H. Kim2 1

Port Research Division Port Management/Operation & Technology Department Korea Maritime Institute Seoul, Korea Email: [email protected] 2 Department of Industrial Engineering Pusan National University Busan, Korea Corresponding author’s email: [email protected]

Abstract: Pyramid stacking is a type of block stacking method for cylindrical unit loads such as drums, coils, paper rolls, and so on. This study addresses how to determine the optimum configuration of a storage system for mixed pyramid stacking of multi-group unit loads. It is assumed that multiple groups of unit loads, with different retrieval rates and duration of stays from each other, are stored in the same storage system. The configuration of a storage system is specified by the number of bays, the assignment of groups to each bay, and the height and width of each bay. A cost model considering the handling cost and the space cost is proposed. Numerical experiments are provided to illustrate the procedures for the optimization in this study. (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION Pyramid stacking is a storage method in which cylindrical unit loads are stacked on the floor as shown in Figure 1. Pyramid stacking is one of the storage methods with a high re-handling cost and space utilization. The bay of pyramid stack in Figure 1 consists of 3 tiers by 4 rows at the bottom resulting in 9 unit loads in total. There are 4, 3 and 2 unit loads at each tier, respectively, from the bottom. When a retrieval order is issued for a unit load at a low tier, one or more than one relocation must be performed before the target unit load is retrieved. Such relocations are a major source of inefficiency in handling activities in pyramid stacking systems. Figure 2 shows the total number of handling each unit load for retrieval in the pyramid stacking system of Figure 1. The k is the index of the tier from the top and l is the index of the position in each tier from the left hand side. The s represents the total number of handlings for retrieving a target unit load from each corresponding position. In case of a unit load at (3,2), it requires 4 relocations of unit loads at (1,1), (1,2), (2,1) and (2,2) and thus the total number of handlings becomes 5. For a given number of unit loads in a bay, when the number of unit loads at the lowest tier decreases, the number of tiers in pyramid stacking system must increase, which results in an increase in the expected number of relocations per retrieval. However, the height of a pyramid stacking bay cannot exceed the number of unit loads at the lowest tier because the number of unit loads per tier decreases one by one as the tier goes up. When the number of unit loads at the lowest tier increases, the space required for the bay increases. Park and Kim (2010) attempted to estimate the number of re-handles for a given number of unit loads at the lowest tier and the number of tiers in a bay when all the unit loads are heterogeneous, which means that all the unit loads in the bay are different from each other and a retrieval order is issued for a specific unit load in the bay. However, this study extends Park and Kim (2010) to the case where multiple unit loads in the bay are the same type and thus a retrieval order is issued for the unit loads in the same type. Figure 3-(a) illustrates the case where all the unit loads in a bay are different types, while Figure 3-(b) illustrates the case where there are three unit loads in each of three types. Many researchers have analyzed the re-handling operation. Watanabe (1991) analyzed the handling activities in container yards and proposed a simple index, termed as the “index of accessibility” to express the accessibility of a stack considering the number of relocations required to lift a container. Castilho and Daganzo (1993) analyzed the handling activities in inbound container yards. Based on a simulation study, they proposed a formula for estimating the number of relocations for the random retrieval of a container. Kim (1997) proposed a formula for estimating the number of relocations for a random retrieval of an inbound container from a bay. Kim and Kim (1999) analyzed the handling activities for relocations in inbound container yards and used the result for determining the number of devices and the amount of space ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 176–187, 2013.

PLANNING FOR SELECTIVE REMARSHALING IN AN AUTOMATED CONTAINER TERMINAL USING COEVOLUTIONARY ALGORITHMS K. Park1, T. Park1, K. R. Ryu1 1

Department of Computer Engineering Pusan National University Busan, Korea Corresponding author’s email: [email protected]

Abstract: Remarshaling in a container terminal refers to the task of rearranging containers stored in the stacking yard to improve the efficiency of subsequent loading onto a vessel. When the time allowed for such preparatory work is limited, only a selected subset of containers can be rearranged. This paper proposes a cooperative co-evolutionary algorithm (CCEA) that decomposes the planning problem into three subproblems of selecting containers, determining target locations, and finding a moving order, and conducts a cooperative parallel search to find a good solution for each subproblem. To cope with the uncertainty of crane operation in real terminals, the proposed method iteratively replans at regular intervals to minimize the gap between the plan and the execution. For an efficient search under real-time constraint of iterative replanning, our CCEA reuses the final populations of the previous iteration instead of restarting from scratch. Significance:

Keywords:

This paper deals with an optimization problem having three constituent subproblems that are not independent of each other. Instead of solving the subproblems in turn and/or heuristically, which sacrifices solution quality for efficiency, we employ a CCEA to conduct a cooperative parallel search to find a good solution efficiently. For applications to real world, issues like real-time constraint and uncertainty are also addressed. Automated container terminal, remarshaling, container selection, iterative replanning, cooperative coevolutionary algorithm (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION The productivity of a container terminal is critically dependent on the vessel dwell time that is mainly determined by how efficiently the export containers are loaded onto the vessels. The efficiency of loading operation is dependent on how the containers are stacked in the stacking yard where the containers are temporarily stored. The export containers should be loaded in a predetermined sequence taking account of the weight balance of vessel and the convenience of operations at the intermediate and the final destination ports. If a container to be fetched next is stored under some other containers, additional operations are required for the yard crane to relocate the containers above it. This rehandling is the major source of inefficiency of loading, causing delays at the quayside. Loading operation is also delayed if a yard crane needs to travel a long distance to fetch a container for loading. The delay of loading caused by rehandling or long travelling can be avoided if the export containers are arranged in an ideal configuration respecting the loading sequence. There have been many studies on deciding ideal stacking positions of export containers coming into the yard (Kim et al., 2000, Duinkerken et al., 2001, Dekker et al., 2006, Yang et al., 2006, Park et al., 2010a, and Park et al., 2010c). However, appropriate stacking of incoming containers is difficult because most of the containers are carried into the terminal before the loading plan is made available. Remarshaling refers to the preparatory task of rearranging the containers during the idle times of yard cranes to avoid rehandling and long travelling at the time of loading. In real container terminals, however, not all the export containers can usually be remarshaled because the crane idle time is not long enough and the loading plan is fixed only a few hours before the loading operation starts. In this paper, we propose a cooperative coevolutionary algorithm (CCEA) that can derive a remarshaling plan for a selected subset of the export containers under time constraint. The idea of CCEA is to efficiently search for a solution in a reduced search space by decomposing a given problem into subproblems (Potter et al., 2000). In CCEAs, there is a population of candidate solutions for each subproblem, and these populations evolve cooperatively via mutual information exchanges. Park et al. (2009) developed a planning method for remarshaling all the export containers using a CCEA assuming no time constraint. In their CCEA, the problem of remarshaling is decomposed into two subproblems: one for determining the target slots to which the containers are relocated and the other for determining the order of moving the containers. Another work by Park et al. (2010b) paid attention to the problem of selective remarshaling and proposed a genetic algorithm ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 188–210, 2013.

SEASONAL SUPPLY CHAIN AND THE BULLWHIP EFFECT D. W. Cho1, Y. H. Lee2 1

Department of Industrial and Management Engineering Hanyang University, Ansan, Gyeonggi-Do, 426-791, South Korea, e-mail: [email protected] 2* Department of Industrial and Management Engineering Hanyang University, Ansan, Gyeonggi-Do, 426-791, South Korea, Corresponding author’s e-mail: [email protected]

Abstract In this study, we quantify the bullwhip effect in a seasonal two echelon supply chain with stochastic lead time. The bullwhip effect is the phenomenon of demand variability amplification when one moves away from the customer to the supplier in a supply chain. The amplification effect poses very severe problems for a supply chain. The retailer faces external demand for a single product from end customers where the underlying demand process is a seasonal autoregressive moving average, SARMA (1,0)X(0,1)s demand process. And the retailer employs a base stock periodic review policy to replenish its inventory from the upstream party every period using the minimum mean-square error forecasting technique. We investigate what parameters influence the bullwhip effect and how large each parameter affects it. In addition, we investigate the respective relationship between the seasonal period and the lead time, the seasonal moving average coefficient, and the autoregressive coefficient on the bullwhip effect in a seasonal supply chain. Keywords: Supply chain management, Bullwhip effect, Seasonal autoregressive moving average process, Stochastic lead time (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION Seasonal supply chains are affected by seasonal behavior that impact material and information flows both in and between facilities including vendors, manufacturing and assembly plants, and distribution centers. The seasonal patterns of demand, which exist when time series data fluctuates according to some seasonal factor, are a common occurrence in many supply chains. This may intensify the bullwhip effect, which causes severe problems in supply chains. Seasonal peaks of demand may increase demand variability amplification across the supply chain. In the long run, this result may lead to a reduction in supply chain profitability, the difference between the revenue generated from the final customer and the total cost across the supply chain. A basic approach to maintain supply chain profitability is for each independent entity of a supply chain to maintain stable inventory levels to fulfill customer requests at a minimum cost. However, the main one among barriers both internal and external to achieving this objective is recognized as the bullwhip effect. This effect is the phenomenon of the increasing amplification of variability in orders occurring within a supply chain the more one moves upstream. This amplification effect includes demand distortion described as a phenomenon where order to the suppliers tends to have larger variance than the sales to the buyer. The occurrence of the bullwhip effect in a supply chain poses severe problems such as lost revenues, inaccurate demand forecasts, low capacity utilization, missed production schedules, ineffective transportation, excessive inventory investments, and poor customer service (Lee et al., 1997a, b). Forrester (1969) proves evidence of the bullwhip effect. Sterman (1989) exhibites the same phenomenon through an experiment known as the beer game. In addition, Lee et al. (1997a, b) discoveres five main sources that may lead to the bullwhip effect, including demand signal processing, non-zero lead-time, order batching, rationing game under shortage, and price fluctuations and promotions. They argue that eliminating its main causes may significantly reduce the bullwhip effect. In the concrete, the demand process, lead times, inventory policies, supply shortage and the forecasting techniques have a significant influence on the bullwhip effect. Among these, forecasting techniques, inventory policies and to some extent replenishment lead time are controllable by supply chain members and hence can be decided upon to mitigate the bullwhip effect. However, demand process whether seasonal or not is uncontrollable because of external parameter occurring at the customer. It is reasonable for supply chain members to suitably respond to demand process they face. Changing demand trends has a significant influence on supply chain performance measures (Byrne and Heavey, 2006). Therefore, it is important to understand the impact of the seasonal demand process on the bullwhip effect in a seasonal supply chain. There have been many studies in the bullwhip effect including demand process, forecasting techniques, lead times and an ordering policy. Alwan et al. (2003) studied the bullwhip effect under an order-up-to policy by applying the mean squared error optimal forecasting method to an AR(1) and investigated the stochastic nature of the ordering process for an incoming ARMA(1,1) using the same inventory policy and forecasting technique. Chen et al. (2000a, 2000b), Luong (2007), and Luong and Phien (2007) studied the bullwhip effect resulting from an order-up-to policy ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 211–224, 2013.

SCHEDULING ALGORITHMS FOR MOBILE HARBOR: AN EXTENDED M-PARALLEL MACHINE PROBLEM I. Sung1, H. Nam1, T. Lee1 1

Korea Advanced Institute of Science and Technology Korea, Republic Of Corresponding author’s email: [email protected]

Abstract: Mobile Harbor is a movable floating structure with container loading/unloading equipment on board. Mobile Harbor is equivalent to a berth with a quay crane in a conventional port, except that it works with a container ship anchoring on the open sea. A Mobile Harbor-based system typically deploys a fleet of Mobile Harbor units to handle a large number of containers, and operations scheduling for the fleet is essential to the productivity of the system. In this paper, a method to compute scheduling solutions for a Mobile Harbor fleet is proposed. Jobs are assigned to Mobile Harbor units, and their operations sequence is determined, with an objective of minimizing the sum of completion times of all container ships. This problem is formulated as a mixed integer programming (MIP) problem, which is modified from an mparallel machine problem. A heuristic approach using Genetic Algorithm is developed to obtain a near optimal solution with reduced computation time. (Received November 30, 2010; Accepted March 15, 2012)

1. INTRODUCTION In today’s global economy environment, demand for maritime container transportation has been steadily increasing. This, in turn, has stimulated the adoption of very large container ships of over 8,000TEU1 capacity, in an effort to reduce the transportation costs. With the introduction of such large container ships, container terminals are now facing challenges to dramatically improve their service capability to efficiently serve container ships. The challenges include providing sufficient water depth at their berths and in their sea routes, and improving container handling productivity to reduce port staying time for container ships. Resolving these problems by conventional approaches – expanding existing ports or building new ones – requires massive investment and causes environmental concerns. Mobile Harbor is a new concept developed by a group of researchers at Korea Advanced Institute of Science and Technology (KAIST) as an alternative solution to this problem. Mobile Harbor is a container transportation system that can load/unload containers from a container ship anchoring on the open sea. It can transfer containers from a container ship to a container terminal, and vice versa. A concept design and dimensional specifications of Mobile Harbor are shown in Figure 1 and Table 1, respectively.

Figure 1. A concept design of Mobile Harbor

An illustrative operational scenario of Mobile Harbor is as follows: Ÿ A container ship calls at a port, and instead of berthing at a terminal, it anchors at an anchorage, remotely located from the terminal, 1

TEU stands for twenty-foot equivalent unit.

ISSN 1943-670X

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International Journal of Industrial Engineering, 20(1-2), 225–240, 2013.

SHORT SEA SHIPPING AND RIVER-SEA SHIPPING IN THE MULTI-MODAL TRANSPORT OF CONTAINERS J. R. Daduna Berlin School of Economics and Law Badensche Str. 52 D - 10825 Berlin, Germany e-mail: [email protected]

Abstract: The constantly increasing quantitative and qualitative requirements for the terrestrial container and Ro/Ro transport can not only be dealt with in road and rail freight transport and from transportation on inland waterways in the upcoming years. Also suitable solutions have to be found, which include other modes of transport, where both economic and ecological factors as well as macroeconomic considerations are of importance. One possible approach is to increase the use of Short Sea Shipping and River-Sea Shipping that is less applied so far. In this contribution, the underlying structures are presented and reviewed for their advantages and disadvantages. Potential demand structures are identified and illustrated by various examples. The paper concludes with analysis and evaluation of these concepts and the summary of necessary measures for their implementation. (Received November 30, 2010; Accepted March 15, 2012)

1. POLITICAL FRAMEWORK FOR FREIGHT TRANSPORT The realization of cargo traffic, both as inland and port hinterland transport, largely occurs in road freight transport at the moment. This situation is very contradictory to the (worldwide increasingly coming to the fore) transport policy objectives, which provide a sustainable change of modal split for the benefit of rail freight transport and freight transport on inland waterways. Considerations regarding the efficient use of resources and the reduction of mobility-based pollution receive priority here. However, the results of a realization of these goals should not be overestimated. The critical question is to which extend a modal shift can actually be achieved under the existing technical and organizational framework and the requirements for operational processes in logistics (see e.g. Daduna 2009). In general, this concept does not exclude undertaking measures to shift road transport to other modes of transport, but more importantly the existing potentials should be exhausted, especially in long-distance haulage. Targeted governmental measures in various countries, for example in the Federal Republic of Germany with the introduction of the road toll (for heavy trucks over 12 tones admissible gross vehicle weight on highways), which has caused an (administratively enforced) increase in cost of road transport, do not show the aspired effect (see e.g. Bulheller 2006; Bühler / Jochem 2008). Only the economical behavior of suppliers of services in the road transport has led to noticeable ecological effects, for example by increasing use of vehicles with lower pollutant category (see e.g. BAG 2009: 19p). The (often existing and desired) political prioritization of multi-modal freight transport for road / rail has not yet led to the expected results regarding a significant change in modal split, as from user perspective in many cases process efficiency and adequate quality of services is not provided. In addition, in rail transport there are the often existing capacity restrictions regarding the available network infrastructure, as well as (for example within the European Communities (EC)) the sometimes significant interoperabilities in cross-border traffic. This especially occurs concerning the monitoring and control technology and the energy supply as well as the legal framework (see e.g. Pachl 2004: 16pp). Another possibility is the inclusion of inland waterway and maritime navigation in the structures of multi-modal transport, regardless of (process-related) limits. The inland waterway navigation can offer only limited shift potentials because of capacity restrictions (referring to the authorized breadth and draught of inland waterway vessels) and the geographical structures of the available network. Also in maritime navigation accordant restrictions occur regarding (possible) access to the (often close to the customer located but smaller) ports and therewith to the hinterland, for example with a (further) increase in ocean-going vessel sizes (s. e.g. Imai et al. 2008). An increasingly discussed and also worldwide in various areas implemented solution is given by the concept of Short Sea Shipping (SSS) (also in the context of feeder traffic), whereupon a larger number of smaller ports (with local and / or regional importance) is involved in the configuration of transport processes. In the focus of attention are multi-modal transport chains, in which primarily the (coastal) shipping is efficiently linked with the (classical) terrestrial modes of transport. A specific extension of these considerations results from the integration of River-Sea Shipping (RSS), because not only coastal transport routes are used here, but with a suitably designed inland network of waterways also access to the ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 241-251, 2013.

A PREMLIMINARY MATHEMATICAL ANALYSIS FOR UNDERSTANDING TRANSMISSION DYNAMICS OF NOSOCOMIAL INFECTIONS IN A NICU 1

Taesu Cheong1, and Jennifer L. Grant2 Department of Industrial and Systems Engineering, National University of Singapore Singapore 117576, Singapore 2 Rollins School of Public Health, Department of Health Policy and Management, Emory University, Atlanta, GA 30322, USA

Nosocomial infections (NIs) have been a major concern in hospitals, especially in high-risk populations. Neonates hospitalized in the intensive care unit (ICU) have a higher risk of acquiring infections during hospitalization than other ICU populations, which often result in prolonged and more severe illness and possibly death. The corresponding economic burden is immense, not only for parents and insurance companies, but also for hospitals faced with increased patient load and resource utilization. In this paper, we attempt to systemically understand the transmission dynamics of NIs in a neonatal intensive care unit (NICU). For this purpose, we present a mathematical model, perform sensitivity analysis to evaluate effective intervention strategies, and discuss numerical findings from the analysis. Keywords: Nosocomial infections, Hospital-acquired infections, Infection control, Mathematical model, Pathogen spread

1. INTRODUCTION Nosocomial infection (NI; also known as hospital-acquired infection or HAI) is defined as an infection during hospitalization that was not present or incubating at the time of admission, according to the US Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) (Lopez Sastre et al.,2002). Data from CDC suggests that 1 in 10 hospitalized patients in the United States acquire an infection each year (Buus-Frank,2004). This calculates to approximately two million hospitalized patients with NIs and approximately 90,000 deaths that result from these infections. The associated economic burden is also immense, and in fact, approximately USD 6.7 billion are spent annually, primarily on costs associated with increased length of stay. HAIs often lead to morbidity and mortality for neonates in intensive care. A 2007 study by Gastmeier et al. (2007) compared reports of HAI outbreaks in the NICU to those in other intensive care units (ICUs). They found that, out of 729 outbreaks in all ICUs, 276 were in NICUs, totaling 37.9% of all ICU outbreaks. NICU outbreaks included 5718 patients making it the most frequent subgroup in ICU outbreaks. Critically ill infants cared for in the intensive care environment are among the most vulnerable patient groups for HAIs. Since these babies are underdeveloped and have weak skin, they have a higher risk of acquiring these infections. The immunologic immaturity of this patient population, the need for prolonged stay, and the large use of invasive diagnostic and therapeutic procedures also contribute to higher rates of infection in the NICU than in pediatric and adult ICUs (Mammina et al.,2007). Rates of infections have varied from 6% to 40% of neonatal patients, with the highest rates occurring most often in facilities having larger proportions of very low-birth-weight infants or neonates requiring surgery (Brady, 2005). This group of infants also experiences more severe illness as a result of these infections, mainly because of their profound physiologic instability and the diminished functional capacity of their immune system. Efforts to protect NICU infants from infections must therefore be concomitant. Children's Healthcare of Atlanta (CHOA) 1 has three ICUs, of which their NICU has the highest rate of infection. This is a concern for the management since these rates are also higher than the national average. A systemic approach and mathematical modeling have been increasingly used to understand the transmission dynamics of infectious diseases in hospitals - particularly, to “test hypotheses of transmission” and “explore transmission dynamics of pathogens” (Grundmann et al., 2006). In this study, we perform a preliminary mathematical analysis of the spread of NIs in the CHOA NICU. We then evaluate the effectiveness of different intervention strategies, including increased hand hygiene, patient screening at admission, and NICU-wide explicit contact precautions against colonized or infected patients, numerically through sensitivity analysis. We remark that, in the field of industrial engineering, the application of quality control charts to detect the outbreak of infections has been mainly discussed in literature (e.g., Benneyan,2008). We also consider facility surface disinfection including medical equipment and devices as an intervention strategy. 1

A non-profit pediatric hospital (http://www.choa.org/) ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 252-261, 2013.

AUTOMATED METHODOLOGY FOR SCENARIO GENERATION AND ITS FEASIBILITY TESTING Sang Chul Park1, Euikoog Ahn1, Yongjin Kwon1, 1 Department of Industrial Engineering Ajou University, Suwon, 443-749 South Korea Email: [email protected] The main purpose of this study is to devise a novel methodology for automated scenario generation, which simultaneously checks the feasibility and the correctness of scenarios in terms of event sequence, logical propagation, and violation of constraints. Modern day warfare is highly fluidic, fast moving, and unpredictable. Such situation stipulates the fast decision making and rapid deployment of fighting forces. Management of combat assets and utilization of battlefield information, therefore, become the key factors that deice the outcome of engagement. In this context, the Korean Armed Forces are building a framework, in which commanders can rapidly and efficiently evaluate every conceivable engagement scenario before committing real assets. The methodology is derived from the Conflict Table, event transition probabilities, DEVS formalism, and DFS algorithm. The presented example illustrates an oneon-one combat engagement scenario with two submarines, of which results validate the effectiveness of the proposed methodology.

Keywords: Defense M&S; DEVS; DFS; Automated scenario generation; Conflict Tables; Event transition probabilities.

1.

INTRODUCTION

Defense modeling and simulation (M&S) technology enables a countless number of testing and engagement scenarios evaluated without having to commit real assets (Lee et al. 2008). In defense M&S, real objects (e.g., soldiers, trucks, tanks, and defense systems) are modeled as combat entities and embedded into a computer generated synthetic battlefield. The interaction between the combat entities and the synthetic battlefield is dictated by the rules within the sequence of events, which is basically an engagement scenario. Defense M&S manifests two broad categories: (1) a testing of weapon’s effectiveness; and (2) a virtual engagement. The first category is highly favored due to many benefits, including cost savings, less environmental damages, and reduced safety hazards. The second category represents virtual war games or engagements, depending on the size of forces and theaters involved. By examining the engagement scenarios, war strategists can formulate the factors important to the conduct of battles and visualize the tactical merits and flaws that are otherwise difficult to identify. One problem is, however, the scenarios must be manually composed, incurring much time and effort (Yoon, 2004). Due to complex and unpredictable nature of modern warfare, every possible scenario needs to be evaluated to increase the chance of operational success. A manual composition of engagement scenario, therefore, has been a great hindrance to the defense M&S. To cope with the problem, a new method is needed, which is automatic and self-checking. In other words, it automatically composes scenarios for every possible eventuality, while automatically ascertaining the correctness of the scenarios. Such notion is well aligned with the concept of concurrent engineering (CE) that intends to improve operational efficiencies by simultaneously considering and coordinating disparate activities spanning the entire development process (Evanczuk, 1990; Priest et al. 2001; Prasad, 1995; Prasad, 1996; Prasad, 1997; Prasad, 1998; Prasad, 1999). CE is known to successfully reduce the product development cycle time and the same can be true for the defense M&S development process. In this context, the automated scenario generation is based on the atomic model of DEVS (Discrete Event System specification) formalism and the DFS (depth first search) algorithm. DEVS provides a formal framework for specifying discrete event models in hierarchical and modular manner (DEVS, 2010). It is represented by the state transition tables. Many defense related studies capitalize on the DEVS formalism (Kim et al. 1997), such as a small scale engagement (Park, 2010), a simulation model for war tactics managers (Son, 2010), and defense-related spatial models using the Cell-DEVS (Wainer et al. 2005). Correctness is checked out by the Conflict Table, representing the possible or impossible pathways for the events. For this study, any discernible activities are referred to as events, and each event should propagate into the next event on a continuous time scale. The Conflict Table controls the transition of any events from one state to the next. By doing so, an event can unfold along any feasible path. While the Conflict Table only manifests the tractable ways for the event transition, the probabilities of one event becoming the next are very different when there exist many subsequent events to propagate into. Therefore, the event transition probabilities (ETP) can be prescribed by the simulation planners (Figure 1). For war tacticians and military commanders, the result of this study brings about an immediate enhancement in their ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 262-272, 2013.

A NEW APPROXIMATION FOR INVENTORY CONTROL SYSTEM WITH DECISION VARIABLE LEAD-TIME AND STOCHASTIC DEMAND Serap AKCAN1, Ali KOKANGUL2 Department of Industrial Engineering1 University of Aksaray 68100, Aksaray, Turkey E-mail: [email protected] Department of Industrial Engineering2 University of Çukurova 01330, Adana, Turkey E-mail: [email protected] Demand for any material in a hospital depends on a random arrival rate and random length of stay in units. Therefore, the demand for any material shows stochastic characteristics that make determining the optimum level of r and Q problem more difficult. Thus, in this study, a single item inventory system for healthcare was developed using a continuous review (r, Q) policy. A simulation meta-model was constructed to obtain equations for the average on-hand inventory and average number of orders per year. Then, the equations were used to determine the optimal levels of r and Q while minimizing the total cost in an integer non-linear model. The same problem investigated in this study was also solved using OptQuest optimization software.

Significance: In this study, an applicable new approximation for inventory control system is constructed and this approximation is examined by presenting a healthcare case study. Keywords: Healthcare systems; Inventory control; (r, Q) policy; Integer non-linear programming; Simulation meta-

modeling

1. INTRODUCTION There are a growing number of studies on continuous review inventory systems. The majority of these studies relate to production applications, and backordering and shortages are allowed. However, there are very few studies concerning the area of healthcare (Sees, 1999). Thus, this study aimed to determine the optimal reorder point (r) and the order quantity (Q) required to minimize the expected annual total cost considering a single-item continuous review (r, Q) policy for a hospital. Many models have been developed for continuous review (r, Q) policies. Çakanyıldırım et al. (2000) modeled (Q, r) policy where the lead-time depends on lot size. Salameh et al. (2003) considered a continuous inventory model under permissible delays in payments. In this model, it was assumed that expected demand was constant over time and the order lead-time was random. Durán et al. (2004) developed a continuous review inventory model to find the optimal inventory algorithm when there was an expediting option. In their inventory policy, decision variables were integers. They also discussed the case when the decision variables were real values. Mitra and Chatterjee (2004) modified a continuous review model for two-stage serial systems first developed by De Both and Graves. The model was examined for fast-moving items. Park (2006) used analytic models in the design of inventory management systems. Chen and Levi (2006) examined a continuous review model with infinite horizon and single product; pricing and inventory decisions were made simultaneously and ordering cost included a fixed cost. Mohebbi and Hao (2006) investigated a problem of random supply interruptions in a continuous review inventory system with compound Poisson demand, Erlangdistributed lead-times and lost sales. Axsäter (2006) developed a single-echelon inventory model controlled by continuous review (r, Q) policy in which it was assumed that the lead-time demand was normally distributed and in which the aim was to minimize holding and ordering cost under fill rate constraint. Lee and Schwarz (2007) considered a continuous review (Q, r) inventory system with single-item from an agency perspective, in which the agent’s effort influences the item’s replenishment lead-time. Their findings revealed that the possible influence of the agent on the replenishment lead-time could be large, but that a simple linear contract was capable of recapturing most of the cost penalty of ignoring agency. Hill (2007) investigated continuous review lost-sales inventory models with no fixed order cost and a Poisson demand process. In addition, Hill et al. (2007) modeled a single-item, two-echelon, continuous review inventory model. In their model, demands made on the retailers follow a Poisson process and warehouse leadtime cannot exceed retailer transportation time. Darwish (2008) examined a continuous review model to determine the ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 273-281, 2013.

MANPOWER MODELING AND SENSITIVITY ANALYSIS FOR AFGHAN EDUCATION POLICY 1

Benjamin Marlin 1, 2 and Han-Suk Sohn 2 * United States Army TRADOC Analysis Center, TRAC-WSMR, White Sands MR, NM 88002, USA 2 Dept. of Industrial Engineering, New Mexico State University, Las Cruces, NM 88003, USA E-mail address: [email protected] (B. Marlin) and [email protected] (H. Sohn)

This paper provides a demand based balance of flow manpower model premised in mathematical programming to provide insight into the potential futures of the Afghan Education System. Over the previous three decades, torn from multiple wars and an intolerant governing regime, the education system in Afghanistan has been decimated. Over the past 10 years Afghanistan and the international community have dedicated a substantial amount of resources to educate the youth of Afghanistan. By forecasting student demand we are able to determine points of friction in the teacher production policy regarding grade level, gender, and province across a medium-term time horizon. We modify the model to provide sensitivity analysis to inform policies. Examples of such policies are accounting for the length of teacher training programs and encouragement of inter-provincial teacher moves. By later applying a stochastic optimization model potential outcomes regarding changes in teacher retention attributed to policy decisions, incentives to teach, or security concerns are highlighted. This model was developed in support of the validation of a large scale simulation regarding the same subject.

Keywords: Manpower model, sensitivity analysis, Afghanistan, education policy, mixed integer linear program.

1. BACKGROUND Over the previous three decades, torn from multiple wars and an intolerant governing regime the education system in Afghanistan has been decimated. Only in the recent decade has there been a unified effort toward the improvement of education. This emphasis regarding education has provided benefit, but has also brought unexpected problems. There has been a seven fold increase in the demand for primary and secondary education with nearly seven million children enrolled in school today (Ministry of Education, 2011). Unfortunately, in a country with 27% adult literacy, an ongoing war upon its soil, an opium trade as a primary gross domestic product, and an inefficient use of international aid, meeting the increasing demand for education is difficult at best (Sigsgaard, 2009). The Afghanistan Ministry of Education (MOE) has stated the future of Afghanistan depends on the capacity of its people to improve their own lives, the well being of their communities, and the development of the nation. Concurrently, the United Nations (UN) has supported a tremendous amount of research stating that primary and secondary education is directly linked to the ability of a people to better their lives and their community (Dickson, 2010). This has resulted in the UN charter for universal primary education and improved secondary education by 2015. As of 2012, there are 56 primary donors who have donated approximately $57 billion U.S. to Afghanistan (Margesson, 2009). The UN Coalition is dedicated to the security and infrastructure improvement of Afghanistan in order to ensure Afghan Government success. In 2014, with the anticipated withdrawal of coalition forces and a newly autonomous Afghan state, the future is uncertain. The purpose of this research is to use mathematical modeling to demonstrate potential outcomes and points of friction regarding the demand for teachers in Afghanistan given the substantial forthcoming changes in the country.

2. INTRODUCTION Teacher management is a critical governance issue in fragile state contexts, and especially those in which the education system has been destroyed by years of conflict and instability (Kirk, 2008). For this reason, this research focuses on the capacity for teacher training in Afghanistan as it pertains to the growing demand for education. Although the current pool of teachers has a mixed training background (73% of teachers have not met the grade 14 graduate requirement (Ayobi, 2010), the Afghanistan Ministry of Education requires a two year teacher training college (TTC) after a potential teacher has passed the equivalent of 12th grade (Ministry of Education, 2011). Therefore, it is rather important to determine the number of future teachers required to enter the training base each year to support the increasing education demand. Of equal importance is discovering potential weaknesses in training capacity, and where these potential friction points exist. The issues cannot be remedied in the short run; therefore, it is beneficial to use insights gained through modeling to inform policy decision. The technique presented in this paper is based on a network flow integer program which has been successfully applied ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 282-289, 2013.

QUICK RELIABILITY ASSESSMENT OF TWO-COMMODITY TRANSMISSION THROUGH A CAPACITATED-FLOW NETWORK Yi-Kuei Lin Department of Industrial Management National Taiwan University of Science and Technology Taipei 106, Taiwan, R.O.C. Tel: +886-2-27303277, Fax: +886-2-27376344 [email protected] Each arc in a capacitated-flow network has discrete and multiple-valued random capacities. Many studies evaluated the probability named system reliability herein that the maximum flow from source to sink is no less than a demand d for a capacitated-flow network. Such studies only considered commodities of a same type transmitted throughout the network. Many real-world systems allow commodities of multiple types to be transmitted simultaneously, especially in the case that different type of commodity consumes the arc’s capacity differently. For simplicity, this article assesses the system reliability for a two-commodity case as follows. Given the demand (d1,d2), where d1 and d2 are the demands of commodity 1 and 2 at the sink, respectively, an algorithm is proposed to find out all lower boundary points for (d1,d2). The system reliability can be computed quickly in terms of such points. The computational complexity of the proposed algorithm is also analyzed. Keywords: Reliability; two-commodity; capacitated-flow networks; minimal paths

1. INTRODUCTION A minimal path (MP) is a path whose proper subsets are no paths and a minimal cut (MC) is a cut whose proper subsets are no cuts. When the system is binary-state and composed of binary-state components (Endrenyi, 1978; Henley, 1981), the typical method uses MPs or MCs to compute the system reliability, the probability that the source node s connects the sink node t. When the system is multistate (Aven, 1985; Griffith, 1980; Hudson and Kapur, 1985; Xue, 1985), the system reliability, the probability that the system state is not less than a state d, can be evaluated in terms of d-MPs or dMCs. Note that a d-MP (not a MP) and a d-MC (not a MC) are both vectors denoting the state of each arc. In the case that the considered multistate system is a single-commodity capacitated-flow network (i.e., flow is considered), the system reliability is the probability that the maximum flow (from s to t) is not less than a demand d. The typical approach to assesse such a reliability is to first search for the set of d-MPs (Lin et al., 1995; Lin, 2001, 2003, 2010a-d; Yeh, 1998) or d-MCs (Jane et al., 1993; Lin, 2007, 2010e). However, in real world many capacitated-flow networks allow commodities of multiple types to be transmitted from s to t simultaneously, especially in the case that different type of commodity consumes the capacity on an arc differently. A broadband telecommunication network is one of such flow networks as several types of services (audio, video, etc.) share the bandwidth (capacity of an arc) simultaneously. The purpose of this article is to extend the reliability assessment from single-commodity case to a two-commodity case. The source node s supplies commodities unlimitedly. The demands of commodity 1 and 2 at the sink t are d1 and d2, respectively. An algorithm is first proposed to generate all lower boundary points for (d1,d2), called (d1,d2)-MPs, in terms of MPs. Then the system reliability, the probability that the system satisfies the demand (d1,d2), can be computed in terms of (d1,d2)-MPs. The remainder of this paper is organized as follows. The two-commodity capacitated-flow model is presented in section 2. Theory and algorithm are proposed in section 3 & 4, respectively. In section 5, a numerical example is presented to illustrate such an approach and also how the system reliability be calculated. The analysis of computational time complexity is shown in section 6.

2. TWO-COMMODITY CAPACITATED-FLOW NETWORK Notation and Nomenclature G A N C s, t  ik

(A, N, C): a capacitated-flow network {ai|1  i  n}: the set of arcs the set of nodes (C1, C2, …, Cn): Ci is the maximal capacity of ai the unique source node, the unique sink node (real number) the weight of commodity k (k = 1, 2) on ai. It measures the consumed amount of capacity on ai

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International Journal of Industrial Engineering, 20(3-4), 290-299, 2013.

APPLICATIONS OF QUALITY IMPROVEMENT AND ROBUST DESIGN METHODS TO A PHARMACEUTICAL RESEARCH AND DEVELOPMENT Byung Rae CHO1, Yongsun CHOI2and Sangmun SHIN2* 1 Department of Industrial Engineering, Clemson University Clemson, South Carolina 29634, USA 2 Department of Systems Management & Engineering, Inje University Gimhae, GyeongNam 621-749, South Korea Researchers often identify robust design, based on the concept of building quality into products or processes, as one of the most important systems engineering design concepts for quality improvement and process optimization. Traditional robust design principles have often been applied to situations in which the quality characteristics of interest are typically time-insensitive. In pharmaceutical manufacturing processes, time-oriented quality characteristics, such as the degradation of a drug, are often of interest. As a result, current robust design models for quality improvement which have been studied in the literature may not be effective in finding robust design solutions. In this paper, we show how the robust design concepts can be applied to the pharmaceutical production research and development by proposing experimental and optimization models which should be able to handle the time-oriented characteristics. This is perhaps the first attempt in the robust design field. An example is given and comparative studies are discussed for model verification. Keywords: Robust design; mixture experiments, pharmaceutical formulations, censored data, Weibull distribution, maximum likelihood estimation.

1. INTRODUCTION Continuous quality improvement has become widely recognized by many industries as a critical concept in maintaining a competitive advantage in the marketplace. It is also recognized that quality improvement activities are efficient and cost-effective when implemented during the design stage. Based on this awareness, Taguchi (1986) introduced a systematic method for applying experimental design, which has become known as robust design which is often referred to as robust parameter design. The primary goal of this method is to determine the best design factor settings by minimizing performance variability and product bias, i.e., the deviation from the target value of a product. Because of the practicability in reducing the inherent uncertainty associated with system performance, the widespread application of robust design techniques has resulted in significant improvements in product quality, manufacturability, and reliability at low cost. Although the main robust design principles have been implemented in a number of different industrial settings, our literature study indicates that robust design has been rarely addressed in the pharmaceutical design process. In the pharmaceutical industry, the development of a new drug is a lengthy process involving laboratory experiments. When a new drug is discovered, it is important to design an appropriate pharmaceutical dosage or formulation for the drug so that it can be delivered efficiently to the site of action in the body for the optimal therapeutic effect on the intended patient population. The Food and Drug Administration (FDA) requires that an appropriate assay methodology for the active ingredients of the designed formulation be developed and validated before it can be applied to animal or human subjects. Given this fact, one of the main challenges faced by many researchers during the past decades is the optimal design of pharmaceutical formulations to identify better approaches to various unmet clinical needs. Consequently, the pharmaceutical industry’s large investment in the research and development (R&D) of new drugs provides a great opportunity for research in the areas of experimentation and design of pharmaceutical formulations. By definition, pharmaceutical formulation studies are mixture problems. These types of problems take into account the proportions within the mixture, not the amount of the ingredient; thus, the ingredients in such formulations are inherently dependent upon one another and consequently experimental design methodologies commonly used in many manufacturing settings may not be effective. Instead, for mixture problems, a special kind of experimental design, referred to as a mixture experiment, is needed. In mixture experiments, typical factors in question are the ingredients of a mixture, and the quality characteristic of interest is often based on the proportionality of each of those ingredients. Hence, the quality of the pharmaceutical product is influenced by such designs when they are applied in the early stages of drug development. In this paper, we propose a new robust design model in the context of pharmaceutical production R&D. The main contribution of this paper is two-fold. First, traditional experimental design methods have often applied to situations in ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 300-310, 2013.

USING A CLASSIFICATION SCHEMA TO COMPARE BUSINESS-IT ALIGNMENT APPROACHES Marne de Vries University of Pretoria South Africa Department of Industrial and Systems Engineering Enterprise engineering (EE) is a new discipline that emerged from existing disciplines, such as industrial engineering, systems engineering, information science and organisation science. EE has the objective to design, align and govern the development of an enterprise in a coherent and consistent way. Within the EE discipline, knowledge about the alignment of business components with IT components is embedded in numerous business-IT alignment frameworks and approaches, contributing to a fragmented business-IT alignment knowledge base. This paper presents the BusinessIT Alignment Model (BIAM) as a conceptual solution to the fragmented knowledge base. The BIAM provides a common frame of reference to compare existing business-IT alignment approaches. The main contribution of this article is a demonstration of BIAM to compare two business-IT alignment approaches: the foundation for execution approach and the essence of operation approach. Significance: To provide enterprise designers/architects with a qualitative analysis tool for understanding and comparing the intent, scope and implementation means of existing/already-implemented business-IT alignment approaches. Keywords: enterprise engineering, enterprise architecture, enterprise ontology, enterprise design, business-IT alignment

1. INTRODUCTION Enterprise systems of the 21st century are exceedingly complex, and in addition, these systems need to be dynamic to stay ahead of competition. Information technology opened up new opportunities for enterprises to extend enterprise boundaries in offering complementary services, entering new business domains and creating networks of collaborating enterprises. The extended enterprise however still needs to comply with corporate governance rules and legislation and need to be flexible and adaptable to seize new opportunities (Hoogervorst, 2009). Supporting an overall view of a complex enterprise, enterprise engineering (EE) emerged as a new discipline for designing, aligning and governing the development of an enterprise. EE consists of three subfields: enterprise ontology, enterprise governance, and enterprise architecture (Barjis, 2011). One of the potential business benefits of EE, is to design and align the entire enterprise (Kappelman et al., 2010). However, a strong theme within enterprise alignment, is alignment between business components and IT components, called business-IT alignment. Although various theoretical approaches and frameworks emerged in literature (Schekkerman, 2004) to facilitate business-IT alignment, a study performed by OVUM (Blowers, 2012) indicates that 66% of enterprises had developed their own customised framework, with one third of the participants making use of two or more theoretical frameworks. The expanding number of alignment approaches and frameworks create difficulties in comparing or extending a current alignment approach with knowledge from the existing business-IT alignment knowledge base. Previous studies circumvented this problem by providing a common reference model, the Business-IT Alignment Model (BIAM) (De Vries, 2010, 2012)for understanding and comparing alignment approaches. This article applies the BIAM in contextualising two business-IT alignment approaches, the foundation for execution approach (Ross et al., 2006) and the essence of operation approach (Dietz, 2006). The aim is to enhance the foundation for execution approach, due to certain method deficiencies of its associated operating model (OM), with another approach, the essence of operation approach. The main contribution of the article is to demonstrate how the classification categories of the BIAM are used to compare two alignment approaches in confirming their compatibility. As demonstrated by the comparison example, BIAM is useful to enterprise engineering practitioners for contextualising current alignment approaches implemented at their enterprise, to identify similarities and differences between current approaches and opportunities for extension. The paper is structured as follows: Section 2 provides background on the topic of business-IT alignment, the Business-IT Alignment Model (BIAM) and two alignment approaches, the foundation or execution approach and essence of operation approach. Section 3 defines the problem of assessing the feasibility of combining current alignment approaches. Section 4 suggests the use of the BIAM components as comparison categories in contextualising two alignment approaches, presenting the results of the a comparison demonstration in section 5. Section 6 concludes with opportunities for follow-up research. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(3-4), 311-318, 2013.

VARIABLE SAMPLE SIZE AND SAMPLING INTERVALS WITH FIXED TIMES HOTELLING’S T2 CHART M. H. Lee School of Engineering, Computing and Science, Swinburne University of Technology (Sarawak Campus), 93350 Kuching, Sarawak, Malaysia. Email: [email protected] The idea of variable sample size and variable sampling interval with sampling at fixed times is extended to the Hotellling’s T2 chart in this study. This chart is called variable sample size and sampling intervals with fixed times (VSSIFT) Hotellling’s T2 chart, in which samples with sample size n always be taken at some specified fixed equally spaced time points but additional samples larger than n are allowed between these time points whenever there is some indication of a process mean shift. The numerical comparison shows that the VSSIFT Hotellling’s T2 chart and the variable sampling interval and variable sample size (VSSI) Hotellling’s T2 chart give almost the same effectiveness in detecting shifts in the process mean. However, from the administration viewpoint, the VSSIFT chart is considered to be more convenient than the VSSI chart. Keywords: sampling at fixed times; steady-state average time to signal; variable sample size; Hotelling’s T2 chart; Markov chain method

1. INTRODUCTION The usual practice in using the control charts is to take samples of fixed size from the process at fixed sampling interval. Recently the variable sample size and variable sampling interval (VSSI) Hotellling’s T2 chart has been shown to give substantially faster detection of most process mean shifts than the standard Hotellling’s T2 chart (Aparisi and Haro, 2003). In the design of the VSSI chart, the sample size and the sampling interval are allowed to change based on the chart statistic. It is reasonable to relax the control by taking the next sample at long sampling interval with small sample size if the current sampling point is close to the target. On the other hand, it is reasonable to tighten the control by taking the next sample at short sampling interval with large sample size if the current sampling point is far from the target but still within the control limit. Thus the actual number of samples taken in any time period will be a random variable, and the time points at which the samples are taken will be unpredictable. The variability in the sampling intervals may be inconvenient from an administrative viewpoint and also undesirable for drawing inferences about the process (Reynolds, 1996a; Reynolds, 1996b). To alleviate the disadvantage of unpredictable sampling times, Reynolds (1996a; 1996b) proposed a modification of the variable sampling interval (VSI) idea for X chart in which samples always be taken at some specified fixed equally spaced time points but additional samples are allowed between these time points whenever there is some indication that the process has shifted from the target. This chart is called variable sampling interval with sampling at fixed times (VSIFT) control chart. The VSIFT control chart may conform more closely to the natural periods of the process and be more convenient to administer. It seems reasonable to increase the size of such samples to improve the performance of the control chart since the additional samples are always taken when there is some indication that the process has changed (Costa, 1998). Lin and Chou (2005) extended this idea of sampling at fixed times to the VSSI X chart, and they showed that the VSSI X chart with sampling at fixed times gives almost the same detection ability as the original VSSI X chart. From the practical viewpoint of administration, the variable sample size and sampling intervals with fixed times (VSSIFT) X chart is relatively easy to set up and implement. In this study, the VSSIFT feature is extended to the multivariate chart, which is the Hotellling’s T2 chart.

2. VSSIFT HOTELLING’S T2 CHART Consider a process with p quality characteristics of interest for each item are observed over time, and the distribution of the observations is p-variate normal with mean vector µ 0 and covariance matrix Σ0 when the process is in-control. Assume that a sample of size n is taken at every sampling point, and let X t be the average vector for tth sample. Then the chart statistic Tt 2 = n( Xt − µ 0 ) Σ0−1 ( Xt − µ 0 ) 2

is plotted in the Hotelling’s T chart with control limit CL = χ

2 p ,α

where χ

(1) 2 p ,α

is the upper α percentage point of the chi-

square distribution with p degrees of freedom. As pointed out by Aparisi (1996), α = 0.005 has been widely employed in ISSN 1943-670X

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International Journal of Industrial Engineering, 20(5-6), 319-328, 2013

SYSTEM RELIABILTIY WITH ROUTING SCHEME FOR A STOCHASTIC COMPUTER NETWORK UNDER ACCURACY RATE Yi-Kuei Lin and Cheng-Fu Huang Department of Industrial Management National Taiwan University of Science & Technology Taipei 106, Taiwan, R.O.C. Under the assumption that each branch’ capacity of the network is deterministic, the quickest path problem is to find a path sending a specific of data from the source to the sink such that the transmission time is minimized. However, in many real-life networks such as computer systems, the capacity of each branch is stochastic with a transmission accurate rate. Such a network is named a stochastic computer network. Hence, we try to compute the probability that d units of data can be sent through the stochastic computer network within both the time and accuracy rate constraints according to a routing scheme. Such a probability is a performance indicator to provide to managers for improvement. This paper mainly proposes an efficient algorithm to find the minimal capacity vector meeting such requirements. The system reliability with respect to a routing scheme then can be calculated. Keywords: Accuracy rate; Time; Quickest path; Routing scheme; Stochastic computer network; System reliability.

1. INTRODUCTION From the perspectives of network operations, management, and engineering, service level agreements (SLAs) are an important part of the networking industry. SLAs are used in contracts between network service providers and their customers. An SLA can be measured by many criteria: for instance, availability, delay, loss, and out-of-order packets. A basic index is the accuracy rate, which is often used to measure the performance of enterprise networks. Therefore, from the viewpoint of quality of service (QoS) (Sausen et al., 2010; Wei et al. 2008), maintaining a high network traffic accuracy rate is essential for enterprises to survive in a competitive environment. Many researchers have discussed issues related to measuring local area network (LAN) traffic (Amer, 1982; Chlamtac, 1980; Jain and Routhier, 1986) and previous studies have considered flow accuracy in traffic classification. Such flows are called elephant flows. Because high packet-rate flows have a great impact on network performance, identifying them promptly is important in network management and traffic engineering (Mori et al., 2007). A conventional method for estimating the accuracy rate of large or elephant flows is the use of packet sampling. However, packet sampling is the main challenge in network or flow measurements. Feldmann et al. (2001) presented a model for traffic demands to support traffic engineering and performance debugging of large Internet service provider networks. Choi et al. (2003) used packet sampling to accurately estimate large flows under dynamic traffic conditions. The file is said to be transmitted correctly only if the file received at the sink is identical to the original file. In fact, data transfer is done through packet transmission. The network supervisor should monitor the number of error packets to assess the accuracy rate of the network. However, the previous papers did not involve system reliability when measuring the accuracy rate Nowadays, computer technology is becoming more important to modern enterprises. Computer networks are the major medium for transmitting data/information in most enterprises. As the stability of computer networks strongly influences the quality of data transmissions from a source to a sink, especially for accurate traffic measurement and monitoring, the system reliability of the computer network is always of concern for information technology departments. Many enterprises regard system reliability evaluation or improvement as crucial for network management, traffic engineering, and security tasks. In general, a computer network is usually modeled as a network topology with nodes and branches, in which each branch represents a transmission line and each node represents a transmission device such as a hub, router, or switch. In fact, a transmission line is combined with several physical lines such as twisted pairs, coaxial cables, or fiber cables. Each physical line may provide a capacity or may fail; this implies that a transmission line has several states where state c means that c physical lines are operational. Hence, the capacity of each branch has several values. In other words, the computer network should be multistate due to the various capacities of each transmission line. Such a network is a typical stochastic flow network (Aven, 1985; Cheng, 1998; Jane et al., 1993; Levitin, 2001; Lin et al., 1995; Lin, 2001, 2003, 2007a, 2007b, 2009a-c; Yeh, 1998, 2004, 2005) and is called a stochastic computer network (SCN) herein. Another important issue is transmission time for the computer network. From the point of view of quality management and decision making, it is an important task to reduce the transmission time through a computer network. When data are transmitted through the computer network, it should select a shortest delayed path to 

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International Journal of Industrial Engineering, 20(5-6), 329-338, 2013.

OBSERVED BENEFITS FROM PRODUCT CONFIGURATION SYSTEMS Lars Hvam1, Anders Haug2, Niels Henrik Mortensen3, ChristianThuesen4 Department of Management Engineering1 Operations Management Technical University of Denmark Building 426, DK-2800 Kgs. Lyngby Email: [email protected] Department of Entrepreneurship and Relationship Management2 University of Southern Denmark Engstien 1, DK-6000 Kolding Email: [email protected] Department of Mechanical Engineering3 Product Architecture Group Technical University of Denmark Building 426, DK-2800 Kgs. Lyngby Email: [email protected] Department of Management Engineering4 Production and Service Management Technical University of Denmark Building 426, DK-2800 Kgs. Lyngby Email: [email protected] This article presents a study of the benefits obtained from applying product configuration systems based on a case study in four industry companies. The impacts are described according to main objectives in literature for implementing product configuration systems: lead time in the specification processes, on-time delivery of the specifications, and resource consumption for making specifications, quality of specifications, optimization of products and services, and other observations. The purpose of the study is partly to identify specific impacts observed from implementing product configuration systems in industry companies and partly to assess if the objectives suggested are appropriate for describing the impact of product configuration systems and identifying other possible objectives. The empirical study of the companies also gives an indication of more overall performance indicators being affected by the use of product configuration systems e.g. increased sales, decrease in the number of SKU’s, improved ability to introduce new products, and cost reductions. Significance: Product configuration systems are increasingly used in industrial companies as a means for efficient design of customer tailored products. There are examples of companies who have gained significant benefits from applying product configuration systems. However companies considering use product configuration systems have a challenge in assessing the potential benefits to reach from applying product configuration systems. This article provides a list of potential benefits based on a case study of four industry companies. Keywords: Mass Customization, product configuration, engineering processes, performance measurement, complexity management.

1. INTRODUCTION Customers worldwide require personalised products. One way of obtaining this is to customise the products by use of product configuration systems (Tseng and Piller, 2003), (Forza and Salvador, 2007), (Hvam et al 2008). Product configuration systems are increasingly used as a means for efficient design of customer tailored products, and this has led to significant benefits for industry companies. However, the specific benefits gained from product configuration are difficult to measure. This article discusses how to assess the benefits from the use of product configuration based on a suggested set of measurements and an empirical study of four industry companies. Several companies have acknowledged the opportunity to apply product configuration systems to support the activities of the product configuration process (see for example www.configurator-database.com). Companies like Dell Computer and American Power Conversion (APC) rely heavily on the performance of their configuration sysISSN 1943-670X

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International Journal of Industrial Engineering, 20(5-6), 339-371, 2013.

Decision Support for the Global Logistics Positioning Chun-Wei R. Lin a, Sheng-Jie J. Hsu b,c,* a

Department of Industrial Engineering and Management, National Yunlin University of Science and Technology, 123, University Road Section 3, Douliou, Yunlin, Taiwan, 640, R.O.C. E-mail: [email protected] b

Graduate School of Management, National Yunlin University of Science and Technology, Douliou, Yunlin, Taiwan, 640, R.O.C. E-mail: [email protected]

c

Department of Information Management, Transworld Institute of Technology, Douliou, Yunlin, Taiwan, 640, R.O.C. E-mail: [email protected]

According to the enterprise's global operations, its global logistics system had to be cooperated. It is clear that the global logistics (GL) is more complicated than the local logistics. However, it lacks a generic structure for GL's position to support its decision-making. Therefore, this article proposed a Global Logistic Positioning (GLP) framework by means of literatures review and practice experience. And, constructed the variables in this framework to be a Decision Support System (DSS), which is useful for the GLP decision-making. This DSS can suggest the decision-maker to decide the positions of the operation headquarters, research and development bases, production bases, and distribution bases. For efficiency, this article proposed a four-phase algorithm which integrates the goal programming, revised Analytic Hierarchy Process method, Euclidean distance, and Fitness concept, to execute the GLP computation. Finally, by a virtual example: ABC Company, to verify the GLP theoretical feasibility. Keywords：Global Logistic Management, Global Logistic Positioning, Framework, Decision Support System.

1. INTRODUCTION Many organizations have a significant and growing presence in resource and/or demand markets outside their country of origin. Current business conditions blur the distinctions between domestic and international logistics. Successful enterprises have realized that to survive and prosper they must go beyond the strategies, policies, and programs of the past and adopt a global view of business, customers, and competition. [Stock and Lambert, 2001] Therefore, enterprise extends its operation to the global and become a Multi-National Enterprise (MNE). And its logistics system must to match up its enterprise strategy, to be a global logistics system. Dornier et al. [1998] argued that geographical boundaries are losing their importance. Companies view their network of worldwide facilities as a single entity. Implementing worldwide sourcing, establishing production sites on each continent, and selling in multiple markets all imply the existence of an operations and logistics approach designed with more than national considerations in mind. Bowersox et al. [1999] argued that the business model of successful global operations is

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International Journal of Industrial Engineering, 20(5-6), 372-386, 2013.  

A CLASSIC AND EFFECTIVE APPROACH TO INVENTORY MANAGEMENT J. A. López, A. Mendoza, and J. Masini Department of Industrial Engineering Universidad Panamericana Guadalajara, Jalisco 45010, MEXICO Corresponding author´s email: {Abraham Mendoza, [email protected]} Many organizations base their demand forecasts and replenishment polices only on judgmental or qualitative approaches. This paper presents an application where quantitative demand forecasting methods and classic inventory models are used to achieve a significant inventory cost reduction and improved customer service levels at a company located in Guadalajara, Mexico. The company currently uses a naive method to forecast demand. By proposing the use of Winters method, the forecast accuracy was improved by 41.12%. Additionally, as a result of an ABC analysis for the product under analysis, a particular component was chosen (it accounts for the 70.24% of the total sales and 60.06% of the total volume) and two inventory policies studied for that particular component. The first inventory policy considers the traditional EOQ model, whereas the second one uses a continuous-review (Q,R) policy. The best policy achieves a 43.69% total cost reduction, relative to the current inventory policy. This policy translates into several operational benefits for the company, e.g., improved customer demand planning, simplified production and procurement planning, lower level of uncertainty and a better service level. Significance: While many organizations base their demand forecast and replenishment decisions only on judgmental or qualitative approaches, this paper presents an application where forecasting methods and classic inventory models are used to achieve a significant inventory cost reduction and improved customer service levels at a company located in Guadalajara, Mexico. Keywords: Inventory Management, Forecasting Methods.

1. INTRODUCTION On one hand, small and medium companies seem to be characterized by the poor efforts they make optimizing their inventory management systems. They are mainly concerned with satisfying customers’ demand by any means and barely realize about the benefits of using scientific models for calculating optimal order quantities and reorder points while minimizing inventory costs (e.g., holding and setup costs) and increasing customer service levels. On the other hand, large companies have developed stricter policies for controlling inventory. However, most of these efforts are not supported by scientific models either. Many authors have proposed inventory policies based on mathematical models that are easy to implement in practical situations. For example, Harris introduced the well-known Economic Order Quantity (EOQ) model to calculate optimal inventory policies for situations in which demand is relatively constant (Harris, 1990). This model has been extended to include transportation freight rates, production rates, quantity discounts, quality constraints, stochastic environments and multi-echelon systems. The reader is referred to Silver, Pyke and Peterson (1998), Nahmias (2001), Chopra and Meindl (2007), Mendoza (2007), and Hillier and Lieberman (2010) for more detailed texts on these extensions. Moreover, the EOQ has been successfully applied by some companies around the world. For instance, Presto Tools, at Sheffield, UK, obtained a 54% annual reduction in their inventory levels (Liu and Ridgway, 1995). Despite the benefits shown in some companies, “in these days of advanced information technology, many companies are still not taking advantage of fundamental inventory models”, as stated by Piasecki (2001). For example, companies do not rely on the effectiveness of the EOQ model because of its apparent simplicity. Part of the problem is due to the lack of thorough knowledge of the model’s assumptions and benefits. Along these lines, Piasecki (2001) stated: “many ERP packages have built-in calculations for EOQ that work automatically, so the users do not know how it is calculated and therefore do not understand the data inputs and system set-up that control the output”. The success of any inventory policy depends on an effective customer demand planning (CDP), which begins with accurate forecasts (Krajewski and Ritzman, 2005). At least in small companies, the application of quantitative methods for forecasting, as well as the implementation of replenishment policies, through scientific models, is not well-known. Many organizations base their demand forecasts and replenishment polices only on judgmental or qualitative approaches. This paper presents an application where quantitative demand forecasting methods and classic inventory models are used to achieve a significant reduction in inventory costs. We offer an analysis of the current inventory replenishment policies of a company located in Guadalajara, Mexico, and propose significant cost improvements. Because of confidentiality issues, ISSN 1943-670X

 

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International Journal of Industrial Engineering, 20(5-6), 401-411, 2013.

PRACTICAL DECOMPOSITION METHOD FOR T2 HOTELLING CHART Manuel R. Piña-Monarrez Department of Industrial and Manufacturing Engineering Institute of Engineering and Technology Universidad Autónoma de Ciudad Juárez Cd. Juárez Chih. México, C.P. 32310 Ph (656) 688-4843│Fx (656) 688-4813 Corresponding author’s e-mail: [email protected] In multivariate control process, T2 Hotelling chart had shown to be useful to efficiently detect a change in a system, but it is not capable of diagnosing the root causes of the change. This because the used MTY decomposition method presents p! different possible decompositions of the T2 statistic and p*2(p-1) terms to be estimated for each possible decomposition; so when p is large the estimation of the terms and their diagnostic became too complex. In this article by considering the inverse of the covariance matrix of phase I as the standard one, a practical decomposition method, based on the relations of each pair of variables is proposed. In the proposed method only p*p different terms are estimated and its decomposition gives the variable contribution due its variance and due its covariance with each one of the other (p-1) variables. Since the proposed method is a transformation of the T2 polynomial, the estimated T2 and its corresponding decomposition always hold. Detailed guide for the application of the T2 chart and numerical application to a set of three and twelve variables is given. Significance: Since the proposed method let to practitioners determine which variable(s) generate the out of control signal, and because it quantifies the proportion of the estimated T2 statistic that is due the variance and due the correlation, its application to a multivariate control process is useful. Keywords: Decomposition method, T2 Hotelling chart, Mahalanobis distance, Multivariate control process.

1. INTRODUCTION Nowadays, the manufacturing processes are more complex and products are multifunctional, so they have more than one quality characteristic to be controlled. For these processes, one of the most useful multivariate control charts is the T2 Hotelling chart, which is based on the multivariate normal distribution theory (for details see Alvin 2002). When a multivariate control chart signals, it is necessary to identify the variable(s) which causes the out of control signal. With this particular purpose the Minitab 16 (MR) software, presents a decomposition method based on the MTY method proposed by (Mason et. al 1995, 1997,1999), (for details go in Minitab16 to Stat>Control Charts>Multivariate Charts>Tsquared–Generalized variance>Help>see also>methods and formulas >Decomposed T2 statistic). Unfortunately since the Mahalanobis distance (MD) used in the T2 Hotelling chart is estimated as a nested process (see section 3.1 and Piña 2011), its individual decomposition, and the estimated MD does not hold (see section 3 for details). Other decomposition methods had been proposed. Among them we find in literature the methods proposed by Roy (1958), Murphy (1987), Doganaksoy et al. (1991), Hawkins (1991, 1993), Timm (1996) and Runger et. al (1996). Recently, Alvarez et, al (2007), proposed the method called Original Space Strategy (OSS), which unfortunately as Alvarez mention (pp. 192), “in the approach there exist several methods to calculate the used R value, therefore the decision to choose the R value could be very subjective, consequently; certain amount of the available information could be lost by the Projection” (for details see Alvarez et. al (2007)). Li, et. al. (2008), with the objective to reduce the computational complexity of the MTY method, they proposed a method called causation T2 decomposition method, which integrates the causal relationships revealed by a Bayesian network with the traditional MTY approach, and by theoretical analysis and simulation studies they demonstrated that their proposed method substantially reduces the computational complexity and enhances diagnosticability, this by comparing their method with the traditional MTY approach. Mason et. al. (2008), presented an interesting analysis to apply the MTY method to data of phase I, in order to use it as standard in phase II. Alfaro et. al. (2009) proposed a boosting approach by training a classification method with data of phase I and then by using the trained method in phase II, they determine the variable which causes the out of control signal. In their study, they use data sets of 2, 3, and 4 variables, and found their method was inconsistent for the 2 variable case, and for the 3 variable case, the error was below of 5%. (for details see Alfaro et. al. (2009)). Cedeño et. al. (2012), because the MTY approach has p! different but non-independent partitions of the overall T2 proposed a decomposition method based only in the first two unconditional elements of the MTY method. Nevertheless, when the ISSN 1943-670X

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International Journal of Industrial Engineering, 20(5-6), 412-418, 2013.

COST ASSESSMENT FOR INTEGRATED LOGISTIC SUPPORT ACTIVITIES Maria Elena Nenni Department of Industrial Engineering, University of Naples Federico II, Italy An Integrated Logistic Support (ILS) service has the objective to improve system availability at an optimum life cycle cost. It is usually offered to the customer by the system constructor, who becomes the Contractor Logistic Support (CLS). The aim of this paper is to develop a clear and substantial cost assessment method to support the CLS budgetary decisions. The assessment concerns the cost elements structure for ILS activities and includes an economic analysis to provide details among competing alternatives. A simple example derived from an industrial application is also provided in order to illustrate the idea. Significance: many documents and standards have been produced by military about ILS but the focus is always on performance or life cycle cost. The CLS perspective is completely not attended. Even models from scientific literature are not useful to support CLS decisions because they seem too far from ILS or too general to be implemented effectively. The lack of specific models has become a general problem because if the ILS service has been originally developed for military purposes, now it is applied in commercial product support or customer service organizations as well. Therefore many CLSs are requiring a deeper and wide-ranging investigation on the topic. The method developed in this paper approaches the problem from the perspective of the CLS and it is specifically tailored to the main issues of an ILS service. Keywords: Logistic Support, maintenance, cost model, lifecycle management, after-sale contract.

1. INTRODUCTION The Integrated Logistic Support (ILS) aims at ensuring the best system capability at the lowest possible life cycle cost (DOD Directive, 1970). According to this purpose the system owner builds a partnership with the Contractor Logistic Support (CLS) who implements the ILS process in a continuous way throughout the life cycle, frequently very long, 30 or 35 years. The CLS has usually specific technical skills on the system but he needs to improve decision-making about costs since early stages (Mortensen et alii, 2008). Literature is not really exhaustive. Many documents and standards have been produced about ILS by military (MIL-STD-1388/1A, 1983; Def-Stan 00-60, 2002; Army Regulation 700-127, 2007) and they don’t attend the CLS perspective. Basically the CLS requires appropriate methods to optimize overall costs in the operation phase that is the longest and the most costly (Asiedu and Gu, 1998; Choi, 2009) but approaches from scientific literature are often inadequate. Many authors have spent themselves to develop optimization models: Kaufman (1970) has provided a first original contribution on the structure of life cycle costs in general; other authors (Lapa et alii, 2006; Chen and Trivedi, 2009; Woohyun and Suneung, 2009) have focused more specifically on costs of operation phase with the aim to optimize preventive maintenance policies. Hatch and Badinelli (1999) have instead studied the way of gathering in a single objective function two conflicting components, Life Cycle Cost (LCC) and system availability (A). All the contributions partially address the issue and they are lacking into considering the problem from the perspective of CLS actor. A most fitting paper is from the same author (Nenni, 2013) but it is really recent and it takes the first step on the topic highlighting the discrepancies between the Life Cycle Management approach and the cost management from the perspective of the CLS and through the proposition of a basic cost element structure. The aim of this paper is to develop a cost assessment method based on a clear and substantial cost element structure. Moreover the author proposes a simulation in a real case to point out the importance of determining sensitivity to key inputs in order to find the best value solution among competing alternatives.

2. THE COST MODEL The CLS needs of cost estimates to develop annual budget requests, to evaluate resource requirements at key decision points, and to choose about investment. A specific cost model, really fitting with the ILS issues, is the base for the estimation. The author proposes a cost model where most of the elements are derived from DOD Guide (2005) but the link between cost and performance is original as well as some key decision parameters (Nenni, 2013). Before going through the cost model, it is necessary describe some assumptions. The first one concerns the area in which it runs. In this paper only costs for activities in maintenance planning and supply support have been ISSN 1943-670X

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International Journal of Industrial Engineering, 20(5-6), 419-428, 2013.

AXIOMATIC DESIGN AS SUPPORT FOR DECISION-MAKING IN A DESIGN FOR MAINTENANCE IMPROVEMENT MODEL: A CASE STUDY Jorge Pedrozo, Alfonso Aldape, Jaime Sánchez and Manuel Rodríguez Graduate Studies & Research Division Juarez Institute of Technology Ave. Tecnológico 1340, Cd. Juárez, Chih. 32500 México Corresponding author’s e-mail :{ Jorge Pedrozo, [email protected] } Decision-making is one of the most critical issues in design models. The design of new Maintenance methodologies that improve the levels of reliability, maintainability and availability of equipment has roused a great interest in the last years. Axiomatic Design (AD) is a design theory that provides a framework to decision-making in the designing process. The objective of this paper is to present the validation of a new maintenance improvement model as an alternative model to improve maintenance process.. Significance:The usage of information axiom as decision-making tool is examined, this paper present an example used to describe how AD was applied to select the best maintenance model in order to meet the maintenance functional requirements. Keywords: Decision Making, Axiomatic Design, Information Axiom, Maintenance, Reliability, Availability

1. INTRODUCTION Axiomatic Design (AD) theory provides a valuable framework for guiding designers through the decision process to achieve positive results in terms of final design object (Nordlund and Suh, 1996). Several companies have used the axiomatic design methodology successfully in order to develop new products, processes and even approaches. AD was born about 20 years ago and was conceived as a systematic model for engineering education and practice (Suh, 1990). It addresses designers in the complex process of the design, at the same time, it is catalogued as one of the most difficult tools to master (Eagan et al., 2001). Historically maintenance has evolved throughout time (Moubray 1997), from maintenance’s point of view, we can differentiate approaches of “best practices” applied each one at certain period. For a better understanding of the evolution and development of maintenance from its beginnings until these days, Moubray distinguishes three different generations, see Fig 1. First generation: It includes the period until the end of Second World War, at this time the industries had few machines, they were very simple, easy to repair and normally oversized. The volumes of production were low, reason why the down times were not important. The prevention of equipment’s failures were not of high priority for management, and only was applied the reactive or corrective maintenance the maintenance policy was run to failure. Second generation: It was born as a result of the war, at this time more complex machineries were gotten up, and the unproductive time began to be a preoccupation of the management since they were let perceive gains by effects of new demands, from this reason arose the idea that equipment’s failures could and must be prevented, idea that would take the name of preventive maintenance. In addition new control and planning systems of maintenance started to be implemented, in other words, revisions to predetermined time. This change of strategy made it not only possible to plan maintenance activities; it also made it possible to start controlling maintenance performance, costs and production assets availability. Third generation: It begins in the middle of the Seventies where the changes, as a result of the technological advance and of new researches are accelerated, mechanization and automatization in the industry were increased, operates with higher volumes of production, downtime achieve more importance due to the costs by losses of production, machineries reach greater complexity and increases our dependency of them, products and services of quality are demanded considering aspects of security and environmental and the development of preventive maintenance was consolidated. In the latter years we have lived a very important growth of new concepts of maintenance and methodologies applied to the management of maintenance (Duran 2000). Until ends of 90’s, the developments reached in 3º generation of the maintenance included: • Decision Aid tolls and new maintenance techniques. • Design teams, giving high relevance to reliability and maintainability • An important change in organization thinking towards the participation, the team work and the flexibility ISSN 1943-670X

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International Journal of Industrial Engineering, 20(5-6), 429-443, 2013.  

A STUDY OF KEY FACTORS IN THE INTRODUCTION OF RFID INTO SUPPLY CHAINS THROUGH THE ADAPTIVE STRUCTURATION THEORY Mei Ying Wu, Department of Information Management, Chung-Hua University, 707, Sec.2, WuFu Road, Hsinchu 300. Chun Wei Ku, Department of Information Management, Chung-Hua University Taiwan, Province of China Since 2003, the Radio Frequency Identification System (RFID) technology has gained importance and has been widely applied. Numerous statistics indicate a high potentiality for RFID development in the near future. This study focuses on the issues derived from RFID technology and explores the impact of its introduction into supply chains. Based on the framework of the Adaptive Structuration Theory (AST), a questionnaire is designed for collecting research data, and Structural Equation Modeling (SEM) is adopted in order to identify the relationships among research constructs. The research findings indicate that technological features, promoters, and group cooperation systems of RFID have significant effects on the supply chain operation structure and indirectly influence factors of RFID introduction. It is evident from this study’s results that certain factors of RFID and a good supply chain operation structure have positive effects on the introduction of RFID into supply chains. Keywords: Radio Frequency Identification System, Adaptive Structuration Theory, Structural Equation Modeling, Supply Chain Operation Structure, Introduction of RFID.

1. INTRODUCTION The objective of this study is to investigate the effects of the introduction of RFID into supply chains and the interactions between upstream and downstream firms. This objective is similar to that of the Adaptive Structuration Theory (AST) proposed by DeSanctis and Poole (1994). AST was developed in order to examine the interactions among groups and organizations using information technology (IT). Thus, based on the AST framework, Structural Equation Modelling (SEM) is adopted in order to analyse the relationship among research constructs. This study focuses on firms in a supply chain from upstream to downstream, whose businesses encompass manufacturing, logistics, warehousing, retailing, and selling. The firms are selected from the list of Top 500 Manufacturers released by Business Weekly; members of the Taiwan Association of Logistics Management; and the database of publicly-listed manufacturers, logistics firms, and retailers owned by the Department of Commerce in the Ministry of Economic Affairs. The results are expected to serve as a reference for enterprises that are planning or preparing for RFID introduction.

2. LITERATURE REVIEW 2.1 Introduction to RFID RFID was created in an attempt to replace the widely used barcode technology. Thus far, it has garnered much attention and has been extensively applied. Capable of wirelessly reading a large amount of data of various types, RFID can be used to create an information system that can easily identify an object and extract its attributes. Table 1 presents the features of RFID technology that have been mentioned in previous studies.

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International Journal of Industrial Engineering, 20(5-6), 444-452, 2013.

ORDER PROCESS FLOW OF MASS CUSTOMIZATION BASED ON SIMILARITY EVALUATION Xuanguo XU, Zhongmei LIANG Department of Economics & Management Jiangsu University of Science and Technology Mengxi street No.2 Zhenjiang, China 212003 Email: Xuanguo XU, [email protected] The main result presented in this paper is the order process flow of mass customization based on similarity evaluation. An order process flow of mass customization is put forward with a view to meet customers’ specific needs as well as to reduce difficulties in subsequent production. As the basis of this order process flow, we suppose that all the orders in the accepted order pool are profitable confirmed by the market. A similarity evaluation method is put forward which includes the following steps: determine whether an order is acceptable or not; put the profitable order into the accepted pool; for those not profitable, negotiate with customer to determine which pool it belongs to; order similarity analysis with system clustering method; arrange for batch production for those have much similarities; arrange for completely customized production for those specific orders; arrange order insertion for those have little similarity but can be inserted to the scheduled plan. At the end of this paper, an example case study of one China Air Conditioning Company is presented to illustrate the application of the process flow and the similarity evaluation method. Significance: Order acceptance has been studied in mass production mostly. This paper discussed how to process the orders in mass customization after they are being accepted, so as to make more profit. Keywords: Order process, Mass customization, System clustering, Similarity evaluation

1. INTRODUCTION Since 1990s, customer requirements have become increasingly diversified and individual. Manufacturing enterprises are gradually transferring their production mode from traditional mass production to customization in order to survive in severe competition. Especially, in recent years, due to the demand diversification, order is getting more and more obvious characteristics of personalized, and customized production has become very popular in manufacturing production. Production orders can be customized based on the need to provide customers with personalized products and services. On the other hand, complete customization is too much expensive, long delivery time, low productivity and low capacity utilization (X.-F. SHAO and J.-H.JI, 2008). In this context, mass customization (MC) came into being. As customers' requirements are different from each other, manufacturing enterprises must analyze customers' requirements and adopt specific procedures according to different customization requests and customization degree. Order acceptance is a critical decision-making problem at the interface between customer relationship management and production planning of order-driven manufacturing systems in MC. To solve this problem, the key issue is order selection to get the maximum profit by capacity management. Over the past decade the strategic importance of order acceptance has been widely recognized in practice as well as academic research in mass production (MP) and MTO (make to order) systems. Some papers have discussed order acceptance decisions when capacity is limited and penalty for late delivery (Susan A. Slotnick etc., 2007). Some paper uses different algorithm to solve the order acceptance problems (Walter O. Rom etc., 2008). Simultaneous order acceptance and scheduling decisions were examined in a single machine environment (Ceyda Oguz etc., 2010). All these papers studied the order properties such as release dates, due dates, processing times, setup times and revenues, and offer trade-off between earnings and cost. This strategy is more suitable separately to accept orders for the inventory production or order driven production (such as make to stock and make to order), only need to consider the profits and capacity. Therefore, in make to stock (MTS) mode, the problem is to consider the earnings and profits as a condition to accept or reject orders for the subsequent production is in accordance with high-volume production as quickly as possible to achieve the final product. Unlike MTS mode which holds final finished products in stock as a buffer against demand variability, MC production systems must hold production capacity and work in process (WIP) inventories to accept only orders of the most profitable type. Generally speaking, customers' requests can be divided into three categories in the view of enterprise: standard parts, simple customization and special customization. Standard part means the commonly used accessories in the customized product. Simple customization can further be divided into customization based on parameters and customization based on configurations. If customers' needs for customization are beyond the scope of simple customization, such as changing product's shape dramatically or adding some functions which are not ISSN 1943-670X

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International Journal of Industrial Engineering, 20(7-8), 453-467, 2013

MEAN SHIFTS DIAGNOSIS AND IDENTIFICATION IN BIVARIATE PROCESS USING LS-SVM BASED PATTERN RECOGNITION MODEL 

1

Cheng Zhi-Qiang1, Ma Yi-Zhong1 , Bu Jing2, Song Hua-Ming1 Department of Management Science and Engineering, Nanjing University of Science and Technology, Nanjing Jiangsu, 210094, P.R.China. [email protected], [email protected], [email protected] 2 Automation Institute, Nanjing University of Science and Technology, Nanjing Jiangsu, 210094, P.R.China. [email protected]

This study develops a least squares support vector machines (LS-SVM) based model for bivariate process to diagnose abnormal patterns of process mean vector, and to help identify abnormal variable(s) when Shewhart-type multivariate control charts based on Hotelling’s T 2 are used. On the basis of studying and defining the normal/abnormal patterns of the bivariate process mean shifts, a LS-SVM pattern recognizer is constructed in this model to identify the abnormal variable(s). The model in this study can be a strong supplement of the Shewharttype multivariate control charts. Furthermore, the LS-SVM techniques introduced in this research can meet the requirements of process abnormalities diagnosis and causes identification under the condition of small sample size. An industrial case application of the proposed model is provided. The performance of the proposed model was evaluated by computing its classification accuracy of the LS-SVM pattern recognizer. Results from simulation case studies indicate that the proposed model is a successful method in identifying the abnormal variable(s) of process mean shifts. The results demonstrate that the proposed method provides an excellent performance of abnormal pattern recognition. Although the proposed model used for identifying the abnormal variable(s) of bivariate process mean shifts is a particular application, the proposed model and methodology here can be potentially applied to multivariate SPC in general. Key words: multivariate statistical process control; least squares support vector machines; pattern recognition; quality diagnosis; bivariate process

1. INTRODUCTION In many industries, complex products manufacturing in particular, statistical process control (SPC)[1] is a widely used tool of quality diagnosis, which is applied to monitor process abnormalities and minimize process variations. According to Shewhart’s SPC theory, there are two kinds of process variations, common cause variations and special cause variations. Common cause variations are considered to be induced by the inherent nature of normal process. Special cause variations are defined as abnormal variations of process, which are induced by assignable causes. Traditional univariate SPC Control charts are the most widely used tools to reveal abnormal variations of monitored process. Abnormal variations should be identified and signaled as soon as possible to the effect that the quality practitioners can eliminate them in time and bring the abnormal process back to the normal state. In many cases, the manufacturing process of complex products may have more than two correlated quality characteristics and a suitable method is needed to monitor and identify all these characteristics simultaneously. For the purpose of monitoring the multivariate process, a natural solution is to maintain a univariate chart for each of the process characteristics separately. However, this method could result in higher fault abnormalities alarms when the process characteristics are highly correlated [2] (Loredo, 2002). This situation has brought about the extensive research performed in the field of multivariate quality control since the 1940s, when Hotelling introduced that the 

Corresponding author of this paper. E-mail address: [email protected], [email protected]

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International Journal of Industrial Engineering, 20(7-8), 468-486, 2013

PARALLEL KANBAN-CONWIP SYSTEM FOR BATCH PRODUCTION IN ELECTRONICS ASSEMBLY Mei Yong Chong, Joshua Prakash, Suat Ling Ng, Razlina Ramli, Jeng Feng Chin Universiti Sains Malaysia,Malaysia School of Mechanical Engineering, Universiti Sains Malaysia (USM), Engineering Campus This paper describes a novel pull system based on value stream mapping (VSM) in an electronics assembly plant. Production in an assembly plant can be characterized as multi-stage, high mix, by batch, unbalanced, and asynchronous. The novelty of the system lies on the two kanban systems working simultaneously: a standard lot size kanban system for high-demand products (high runners) and a variable lot size constant work-in-process (ConWIP) system for low-demand products (low runners). The pull system is verified through computer simulation and discussions with production personnel. Several benefits are achieved, including level scheduling and significant reduction in the work-in-process (WIP) level. Production flows are regulated through a process called pacemaker, which involves varying the standard lot size and the number of ConWIP kanban. The available interval time could be utilized for other non-kanban-driven parts and routine maintenance (5S). Only a moderate decline in the production output is seen, compared with the target, because of the increase in the overall set-up time, along with the small lot size production. Keywords: Pull system, kanban system, ConWIP system, batch production

1. INTRODUCTION The philosophy of lean manufacturing originated from the Toyota Production System (TPS) and was envisioned by Taiichi Ohno and Eiji Toyoda (Liker, 2004). This practice considers the deployment of resources only for activities that add value from the perspective of end customers. Other activities that depart from this intention are viewed as wasteful and should be a target for total elimination. Taiichi Ohno identified seven forms of waste: overproduction, queue, transportation, inventory, motion, over-processing, and defective product (Heizer and Render, 2008). Ultimately, the production must be a continuous single flow throughout the shop floor, driven by customer demand. However, this ultimate objective would take years to realize. Moreover, the service work applied to work-in-process (WIP), even if considered as waste, is still needed. The main function of WIP is to decouple parts among machines running at different capacities, set-up times, and failure rates. An excessive amount of WIP prolongs lead time, whereas an insufficient amount of WIP results in the occasional starving and blocking of machine during production (Hopp and Spearman, 2000; Silver et al., 1998). Thus, the pertinent question is how to maintain the minimum amount of WIP in the manufacturing system. One way is to move WIP only when needed, rather than pushing it on the next machine. This is the essence of the pull system. Specifically, a preceding machine produces parts only after receiving a request from its succeeding machine for the immediate replacement of items removed from the stock. Therefore, the flow of information is in the opposite direction of the material flow (Bonney et al., 1999). Lean practitioners often use a kanban (card) to signal the production (authorization) for the next container of material (Gaury et al., 2000). A review of literature (Berkley, 1992; Lage Junior and Godinho Filho, 2010) reveals at least 20–30 existing kanban systems, all of which differ in terms of the medium used, lot sizes, and transferring mechanism. Hybrid systems involving multiple types of kanbans have also been established and studied. The development has led to belief that future kanban systems will be increasingly complex. Some systems, such as those by Takahashi and Nakamura (1999), require the aid of software for real-time adjustments. Other researchers (Markham et al., 2000; Zhang et al., 2005; Moattar Husseini et al., 2006) have ventured into creating optimum kanban settings using advanced computer techniques, such as artificial intelligence. In this paper, we offer a new hybrid system based on a value stream mapping (VSM) exercise. The system is a combination of two well-known techniques: kanban and ConWIP. To the best of our knowledge, even though the mechanism employed is simple and naturally fits into the production under study, this system has yet to be proposed elsewhere. The system is also sufficiently generic to warrant wider applications, especially as the production setting and problems faced in the case study are not unique. The paper begins with an introduction on the pull system and its various types. Afterwards, VSM is introduced as the main methodology, and the sequences of its implementation leading to the final value stream map are presented. The description of the proposed system is then given. Finally, the setup of computer simulation and discussions on the results obtained are provided. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(7-8), 487-501, 2013

LEAN INCIPIENCE SPIRAL MODEL FOR SMALL AND MEDIUM ENTERPRISES Mei Yong Chong, Jeng Feng Chin, Wei Ping Loh Universiti Sains Malaysia Malaysia School of Mechanical Engineering, Universiti Sains Malaysia (USM), Engineering Campus, 14300 Nibong Tebal, Penang, Malaysia

Small and medium enterprises (SMEs) support a balanced local economy by providing job opportunities and industry diversity. However, weak management practices result in suboptimal operations and productivity in SMEs. Few generic lean models conceived with SMEs in mind. In this light, a lean transformation framework for SMEs is conceived. The model is known as lean incipience spiral model (LISM). It aims to effectively introduce lean concepts and later to facilitate sustainable transformation in SME which has limited relevant prior exposure to the concepts. The model builds upon a steady and parsimonious diffusion of lean practices. A progressive implementation is promoted through a spiral life cycle model, where each cycle must undergo four phases. The lean transformation is guided with value stream mapping and a commercial lean assessment tool. Finally, the model was implemented in a suitable case study. Keywords: Lean manufacturing, lean enterprise, small and medium enterprises, value stream mapping

1. INTRODUCTION In general, small and medium enterprises (SMEs) are business enterprises operating with minimal resources for a small market. However, the actual definition tends to vary among countries and is subject to constant revision. In Malaysia, a manufacturing company with less than 150 employees or less than RM 25 million sales turnover is categorized as an SME (Small and Medium Industries Development Corporation, 2011). SMEs are acknowledged as key contributors to the development of the economy, increase in job opportunities, and general health and welfare of global economies. SMEs provide more than half of the employment and value-added services in several emerging countries; their impact is bigger in developed countries. Nevertheless, SMEs always fall behind large enterprises in terms of gross domestic product (GDP). For example, a 2006 report in Kaloo (2010) showed that although SMEs accounted for 99.2% of the total establishment in Malaysia, with 65.1% of the total workforce, they only generated 47.9% of the GDP. Kaloo (2010) reasoned that large enterprises have a size advantage and are able to acquire mass production technologies to reduce production cost. The required setup costs and relevant technologies may be financially infeasible or unavailable for SMEs. With thinner profit margin, SMEs are also more vulnerable to financial losses than large enterprises. SMEs also face fierce competition due to low marketing channels and small niche market share (Analoui and Karami, 2003). Most SMEs heavily rely on general machines that are shared by a high variety of products. To maximize machine utilization, batch production is adopted with ad-hoc scheduling. Inefficient management practices further add to the variability of production forms. This entails long production lead times, impeding rapid response to customer demand. SMEs are seed beds for future large enterprises. Eventually, a SME needs to grow into a large enterprise. The inability of an SME to capitalize on the benefits of accumulated knowledge and experiences over long periods of time may be a sign that something is amiss. In this premise, the constant upgrade of operations is vital. Best practices have to be introduced and adopted for SMEs to achieve high performance in operational areas, rightly with the stage of expansion. Unfortunately, case studies by Davies and Kochhar (2000) found the predominance of malpractices and the high rate of fire fighting in SMEs. The mixed implementation of best practices also did not appear to be the result of a structured selection process. Poor understanding of the relationship between practices and the effects of implementing practices was ascertained. With protecting capital investment as top priority, SMEs largely adopt a conservative and follower mindset that prefers short-term benefits.

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International Journal of Industrial Engineering, 20(7-8), 502-514, 2013

DESIGN AND IMPLIMENTATION OF LEAN FACILITY LAYOUT SYSTEM OF A PRODUCTION LINE Zhenyuan Jia, Xiaohong LU, Wei Wang, Defeng Jia To resolve the problem that the unreasonable facility layout of a production line directly or indirectly leads to inefficient production efficiency are very common in Chinese manufacturing workshops, facility lean layout system of a production line is designed and developed. By analyzing the influence factors of the facility layout, Optimization objectives and constraint conditions of facility layout were summarized. A functional model and a design structure model of the lean layout system are built. Based on the in-depth analyses of the mathematical model designed to denote the optimization of facility layout of a production line, a prototype lean facility layout system of a production line is developed. The results of applying the facility layout system in cylinder liner product line showed that the designed lean facility layout system can effectively enhance the productivity efficiency and increase the efficiency of the using of equipments.

Key words: production line, lean, facility layout, model, design

1. INTRODUCTION Due to the phenomena that the unreasonable facility layout of a production line directly or indirectly leads to inefficient production efficiency are very common in Chinese manufacturing workshops, the research on facility layout of a production line has always been the key research area of industrial engineering domain(Sahin, Ramazan and Türkbey, Orhan, 2009, and Zhang, Min et al., 2009, Diego-Mas, J.A. et al., 2009 and Raman, Dhamodharan et al., 2009). The facility layout form of a production line depends on the types of enterprises and forms of production organization(Khilwani, N. et al., 2008 and Amaral, André R. S. ,2008). The facility layout types are divided into the technological layout, product layout, fixed-station layout (SUO Xiaohong and LIU Zhanqiang, 2007), chain distribution (SUN Hailong, 2005) and the particular layout combining with the actual situation (CAO Zhenxin et al., 2005), and so on. Traditional qualitative methods of facility layout mainly include modeling method, sand table method, drawing pictures method and graphic illustration method, etc. (QU Shiyong and MU Yongcheng, 2007); these methods rely mainly on personal experience and lack of scientific basis. When there are many production units the relationships between the facilities become more complex and the qualitative layout methods are often unable to meet the requirements of the workshop, thus the quantitative distribution technologies emerge. The quantitative layout methods mainly include process flow diagram method, from-to table method, relationships of the work units method and SLP method (advanced by Richard Muther), etc (ZHU Yaoxiang and ZHU Liqiang, 2004). SLP method provides a layout planning method, which selects the relationship analyses of the logistics and non-logistics of the production units as the main line of the planning method, and is the most typical system layout planning method (Richard Muther, 1988). In recent years, with the improvement of the computer’s performance and the development of the digital analysis methods, appeared computer-aided system layout planning (CASLP) method on the basis of applying computer and its related technologies on SLP method (CHANG Jian’e and MA Likun, 2008). The CASLP method not only greatly speeds up the layout plan process, but also provides simulation display for the layout scheme depending on the advanced functions of people-machine-interaction and computer aided drawing.

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International Journal of Industrial Engineering, 20(7-8), 515-525, 2013

A CRITICAL PATH METHOD APPROACH TO A GREEN PLATFORM SUPPLY VESSEL HULL CONSTRUCTION Eda TURANa, Mesut GÜNERb a

Department of Naval Architecture and Marine Engineering, Yildiz Technical University, 34349 Besiktas, Istanbul, Turkey E-mail: [email protected] Phone: +902123833156 Fax: +902122364165 b Department of Naval Architecture and Marine Engineering, Yildiz Technical University, 34349 Besiktas, Istanbul, Turkey E-mail: [email protected] Phone: +902123832859 Fax: +902122364165 This study generates a critical path method approach for the first Green Platform Supply Vessel hull constructed in Turkey. The vessel was constructed and partly outfitted in a Turkish Shipyard and delivered to Norway. The project management of the vessel was conducted utilizing Critical Path Method (CPM) and the critical paths during construction and partly outfitting period of this sophisticated vessel were presented. Additionally, the precautions in order to prevent the delay of the project were discussed. Keywords: Project Management, Production, Critical Path Method (CPM), Green Vessel, Platform Supply Vessel.

1. INTRODUCTION A Platform Supply Vessel (PSV) carries various types of cargoes such as chemicals, water, diesel oil, fuel oil, mud, brine oil etc. between the platforms and ports. She supplies the requirements of the platforms during operations and brings the wastes to the port. Platform supply vessels are separated into three groups as small-sized, medium-sized and large-sized platform supply vessels according to their deadweight tonnages. The platform supply vessels with a capacity less than 1500 DWT are named as small-sized, between 1500 DWT – 4000 DWT are medium-sized and more than 4000 DWT are large-sized platform supply vessels. The vessel in this paper is a large-sized platform supply vessel with her 5500 DWT capacity. This type of construction is the first application in the Turkish Shipyards. The vessel is the first and biggest merchant ship using a fuel cell to produce power on board. The length of the vessel is 92,2 meters and the beam is 21 meters. After completion of the hull construction and partly outfitting in a Turkish Shipyard, the vessel was delivered to Norway. Remaining works were completed in a Norwegian Shipyard. The vessel operates in the North Sea. The vessel uses not only heavy oil or diesel but also liquefied natural gas engines and fuel cell. This is the difference of the vessel from other merchant vessels. SOx, NOx and CO2 emissions are reduced with the combination of gas engines and the fuel cell on board. The construction of Platform Supply Vessels is more difficult and complicated than the vessels that the Turkish Shipyards are experienced in construction of vessels such as chemical carriers and cargo vessels. The length of these vessels are shorter than conventional cargo vessels, however since the steel weights are more than conventional cargo vessels, there is a high demand to build these vessels from the shipyards. Nowadays, these vessels also become the mostly demanded vessels for construction subject to the above reasons. Ship production is a project type production. Therefore project management is a vital factor in the construction of a vessel. The most common planning type in Turkish Shipyards is block planning. In this planning approach, the ship is divided into various sizes of blocks before the construction commences. Firstly, blocks are constructed separately and they are erected on the slipway after completion (Odabasi, 1996). Since the block weights are determined according to crane capacities of the shipyards, the block weights may vary from one shipyard to another. There are various processes during a shipbuilding stage. In order to complete the ship construction profitably on time, information, material, workmanship and workflows should be managed under control, which is appropriate to the shipyard (Turan, 2008). The material flow is also significant for the delivery of the vessels on time. Required materials should be present at the needed time and location. The delays on material supplies may slow down the production or even stop it (Acar, 1999). In the literature, Yang and Chen (2000), performed a study in order to determine the critical path in an activity network. Lu et al. (2008), deals with resource constrained critical path analysis for construction area. Duan and Liao (2010), evaluated improved ant colony optimization for determining project critical paths. Guerriero and Talarico (2010), ISSN 1943-670X

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International Journal of Industrial Engineering, 20(9-10), 526-533, 2013

RECENT DIRECTIONS IN PRODUCTION AND OPERATION MANAGEMENT: A SURVEY Vladimir Modrak1 and Ion Constantin Dima2 Technical University of Kosice, Bayerova, Nr. 1, Presov, Slovakia e-mail: [email protected] 2 Valahia University of Targoviste, B-dul Regele Carol I, Nr. 2, Targoviste, Romania e-mail: [email protected] 1

Although the overviews on overall historical developments in given cognition domains are useful, in this survey a modern era of operations management is treated. This work starts with describing the development and current position of operation management in production sector. Subsequently, decisive development features of operations management are articulated and analyzed. Finally, in the paper, opportunities and challenges of a modern operations management for practitioners are discussed. Keywords: strategic management, operations strategy, organizational change, innovation

1. INTRODUCTION Operations management (often called as production management) may be defined in different ways depending upon angle of view. Since this discipline is a field of management then it focuses on carefully managing the processes to produce and distribute products faster, better, and cheaper than competitors. Operations Management (OM) practically concerns all operations within the organization and objectives of its activities focuses on efficiency and effectiveness of processes. Modern history of production and operations management was initiated in 1950s by an extensive development of operation research tools of waiting line theories, decision theories, mathematical programming, scheduling techniques and other theories. However, the material covered in higher education was quite fragmented without umbrella what it is called as production and operations management (POM). Subsequently, the first publications ‘Analysis of Production Management’ by Bowman and Fetter (1957) and ‘Modern Production Management’ by Elwood Buffa (1961) represented an important transition from industrial engineering to operations management. Operations management finally appears to be gaining position as a respected academic discipline. OM as a discipline went through its own evolution that has been comprehensively characterized by Chase and Aquilano (1989). Thus, this may be a good time to update the evolution of the field. To achieve this goal, the major publications/citations in this field and their evolving research utility over the decades will be identified in this paper.

2. OPERATION MANAGEMENT IN THE CONTEMPORARY ERA The process of building operation management theory and definition of its scope or area has been treated by a number of authors. As it has been mentioned above, a modern era of POM is closely connected with a history of industrial engineering (IE). The development of IE discipline has been greatly influenced by the impact of operation research (Turner et al, 1993). Operation research (OR) was originally aimed at solving difficult war-related problems through the use of mathematics and other scientific branches. The diffusion of new mathematical models, statistics and algorithms to aid in decision-making had a dramatic impact on industrial engineering development. Major industrial companies established operation research groups to help solve their problems. In the 60’s, expectations from OR were extremely high, and as was commented by Luss and Rosenwein (1997), “over the years it often appeared that the mathematics of OR became the goal rather the means to support solving real problems”. It caused that OR groups in companies were transferred to traditional organization units within companies. As a reaction on this disappointment Corbett and Van Wassehove (1993) classified OR specialists into three classes: theoreticians, management consultants, who focus on using available methods to solve practical problems, and the “in-between” specialists called operations engineers, who adapt and enhance methods and approaches in order to solve practical problems. The term “operations engineers” was formulated due to lack of better term and accordingly the group could be also called as operations managers and the field conducting applied research that ISSN 1943-670X

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International Journal of Industrial Engineering, 20(9-10), 534-547, 2013

A CASE STUDY OF APPLYING FUZZY DEMATEL METHOD TO EVALUATE PERFORMANCE CRITERIA OF EMPLOYMENT SERVICE OUTREACH PROGRAM Jiunn-I Shieh 1, Hsuan-Kai Chen 2 (Corresponding Author), Hsin-Hung Wu 3 1

Department of Information Science and Applications, Asia University No. 500, Lioufeng Rd., Wufeng , Taichung County, Taiwan 41354 E-mail: [email protected]

2

Department of Marketing and Logistics Management, Chaoyang University of Technology No. 168, Jifong E. Rd., Wufeng, Taichung County 41349, Taiwan E-mail: [email protected] 3

Department of Business Administration, National Changhua University of Education No. 2 Shida Road, Changhua City, Taiwan 500 E-mail: [email protected]

The economic and financial crisis leads to deterioration in the employment market in Taiwan. The Bureau of Employment and Vocational Training, Council of Labor Affairs of Executive Yuan has been aggressively conducting Employment Service Outreach Program to resolve this tough issue. Under such program, the outreach personnel are recruited, trained, and supervised to perform the duties including identifying unemployed persons and then providing job information for them, using the social resource link to increase employment opportunities, conducting employer forum or workshops for job-seekers, and so on. This study applies fuzzy decision-making trial and evaluation laboratory method to not only evaluate the importance of the criteria but also construct the causal relationships among the criteria of evaluating outreach personnel. The results show that job-seeking service is the most critical criterion among the three first-tier criteria. In addition, identification of the number of unemployed people and number of follow-up visit are the two most important causes under the category of job-seeking service when the performance of outreach personnel in Employment Service Outreach Program is evaluated. Keywords: Employment service outreach program, Outreach personnel, Fuzzy theory, Fuzzy DEMATEL

1. INTRODUCTION In the early 2008, the unemployment rate in Taiwan was 3.80%. Because of the economic and financial crisis, the average unemployment rate in 2009 has been increased to 5.85%. Further, the highest unemployment rate was occurred in August 2009 with 6.13%, representing 672 thousand unemployed persons. As a result, reducing the unemployment rate has become a tough issue faced by the government. In order to ease the negative impact on unemployment, the Bureau of Employment and Vocational Training, Council of Labor Affairs of Executive Yuan has been aggressively conducting Employment Service Outreach Program. This program performed by outreach personnel consists of identifying unemployed persons and then ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 20(9-10), 548-561, 2013

UTILIZING SIGN LANGUAGE GESTURES FOR GESTURE-BASED INTERACTION: A USABILITY EVALUATION STUDY Minseok Son 1, Woojin Park* 1, Jaemoon Jung 1, Dongwook Hwang 1 and Jungmin Park 2 1 Seoul National University, Seoul, 1 Gwanak-ro, Gwanak-gu, Seoul Korea, 151-744 2 Korea Institute of Science and Technology, 5 Hwarang-ro, Seongbuk-gu, Seoul Korea,136-791 *Woojin Park is the corresponding author of the paper

Utilizing gestures of major sign languages (signs) for gesture-based interaction seems to be an appealing idea as it has some obvious advantages, including: reduced time and cost for gesture vocabulary design, immediate accommodation of existing sign language users and supporting universal design and equality by design. However, it is not well understood whether or not sign language gestures are indeed adequate for gesture-based interaction, especially in terms of usability. As an initial effort to enhance our understanding of the usability of sign language gestures, the current study evaluated Korean Sign Language (KSL) gestures employing three usability criteria: intuitiveness, preference and physical stress. A set of 18 commands for manipulating objects in virtual worlds was determined. Then, gestures for the commands were designed using two design methods: the sign language method and the user design method. The sign language method consisted of simply identifying the KSL gestures corresponding to the commands. The user design method involved having user representatives freely design gestures for the commands. A group of evaluators evaluated the resulting sign language and user-designed gestures in intuitiveness and preference through subjective ratings. Physical stresses of the gestures were quantified using an index developed based on Rapid Upper Limb Assessment. The usability scores of the KSL gestures were compared with those of the user-designed gestures for relative evaluation. Data analyses indicated that overall, the use of the KSL gestures cannot be regarded as an excellent design strategy when viewed strictly from a usability standpoint, and the user-design approach would likely produce more usable gestures than the sign language approach if design optimization is performed using a large set of user-designed gestures. Based on the study findings, some gesture vocabulary design strategies utilizing sign language gestures are discussed. The study findings may inform future gesture vocabulary design efforts. Keywords: sign language, gesture, gesture-based interaction, gesture vocabulary, usability

1. INTRODUCTION Gesture-based interaction has been actively researched in the human computer interaction (HCI) community as it has a potential to improve human-machine interaction (HMI) in various circumstances (Nielsen et al., 2003; Cabral et al., 2005; Bhuiyan et al., 2009; Wachs et al., 2011; Choi et al., 2012). Compared with other modalities of interaction, the use of gestures has many distinct advantages: first, gestures are the most basic means of human-tohuman communication along with speech, and thus, may be useful for realizing natural, intuitive and comfortable interaction (Baudel and Beaudouin-Lafon, 1993). Second, human gestures are rich in expressions and can convey many different meanings and concepts as can be seen in the existing sign languages’ extensive gesture vocabularies. Third, gesture-based interaction can be utilized in situations where the use of other interaction methods is inadequate. For example, covert military operations in battle fields would preclude the use of voice-based or keyboard and mouse-based interaction. Fourth, the use of touchless gestures would be ideal in environments that require absolute sanitation, such as operating rooms (Stern et al., 2008a; Wachs et al., 2011). Fifth, gestures may promote chunking, and therefore, may alleviate cognitive burden during human-computer interaction (Baudel and Beaudouin-Lafon, 1993; Buxton, 2013). Sixth, gesture can be combined easily with other input modalities, including voice, to enhance ease of use and expressiveness (Buxton, 2013). Finally, the use of the hands (or other body parts) as the input device eliminates the needs for intermediate transducers, and thereby, may help reduce physical stresses on the human body (Baudel and Beaudouin-Lafon, 1993). One of the key research issues related to gesture-based interaction is the design of gestures. Typically, a gesture design problem is defined as determining the best set of gestures for representing a set of commands necessary for an application. Such set of gesture-command pairs is often referred to as a gesture vocabulary (GV) (Wachs et al., 2008; Stern et al., 2008a). Gesture design is important because whether or not gesture-based interaction achieves naturalness, intuitiveness and comfort largely depends on the qualities of designed gestures. ISSN 1943-670X

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International Journal of Industrial Engineering, 20(9-10), 562-573, 2013

A STUDY ON PREDICTION MODELING OF KOREA MILLITARY AIRCRAFT ACCIDENT OCCURRENCE Sung Jin Yeoum1, Young Hoon Lee2 1 Department of IIE,Yonsei University 2 Department of IIE, Yonsei University, Korea, Republic Of This research reports the analysis on the causes of accidents and case studies during the last 30 years in order to predict chances of accident occurrences for the Republic of Korea Air Force (ROKAF) proactively. Systematic and engineered analytical methods i.e. artificial neural network (ANN) and logistics regression are employed in practice to develop prediction models in order to predict accidents for the purpose of identifying superior technique among the two. After experimentation, it is revealed that ANN outperforms logistic regression technique in terms of enhanced prediction rate. Significance: This research proposes accident prediction models which are anticipated to perform in an effective manner regarding superior accident prediction and prevention rate for military aircrafts. Moreover, this research also serves the purpose of providing an academic base, data and direction for future research on this specific topic. Keywords: Prediction Modeling, Accident Prediction Rate, Artificial Neural Network

1. INTRODUCTION The ROKAF is facing chronic challenge of one or two aircraft accidents per year during commencement of its scheduled air operations and training exercises. The aforesaid fact inevitably incurs high aircraft cost and results in loss of precious pilot’s life having detrimental effects in terms of lowering of morale and causing great grief among citizens. The ROKAF is making best of its effort to address this challenge and has established Air Safety Management Wing in this regard. Few improvements in a scientific and realistic fashion compared to the existing situation have been reported but complete accident prevention is yet to be achieved (Byeon et al., 2008, Myung, 2008). An extensive research with focus on pilot error has been conducted but no research with focus on jet fighter accident variable determination and consequent accident prevention models is available. The reason behind aforesaid shortcoming is that the data related to jet fighter accident is restricted, off-limits and not accessible due to security issues. Due to aforementioned reason, accident prevention models have been developed for nuclear facilities and civilian aircrafts etc. but no research has been conducted regarding jet fighter accident prediction and prevention. This research is one of its kinds because it analyzes a total of 38 major jet fighter (F-A, F-B, F-C and F-D types) accidents over the span of last 30 years (from 1980 to 2010) in an effort to comprehensibly determine all factors and variables affecting military aircraft accidents. Instead of using traditional qualitative accident prevention variables, a quantitative analysis is engineered to extract accident prevention data. To increase the credibility of aforesaid data, we have used two data mining and analysis techniques i.e. logistic regression analysis and ANN. Casual jet fighter accident causes have also been included in the proposed accident prevention model as ‘applicable variables’ along with other factors or variables depicting major accident causes. Individual flight capability is: fighter jet pilot of age 23 years, 2400 hours of flight duration, experience as safety flight leader and squadron leader is included in the crash prediction model. It is worth mentioning that literature on theoretical considerations, suitable research methods with safety management and crash prediction theories related to this specific domain of knowledge have been studied in detail before this research. Two groups were made prior to collecting data via basic statistical analysis i.e. t-evaluation in order to distinguish between accident prone variables and accident free variables. Durbin-Watson’s statistic was used to resolve variable independence, multi co-linearity, tolerance limit, dispersed expansion factor, state index and degree of dispersion issues. Crash prediction models were made through the analysis of aforementioned data via logistics regression and ANN (using SPSS-18TM). The aforesaid models were also verified using test data for the purpose of validation. The superiority of one model over another is determined based on better and enhanced prediction rate. Comprehensive literature survey related to this area of research is presented in Section-2. In Section 3-5, models for jet fighter accident prediction have been developed and validated using test data as gathered for the span of last 30 years. In Section-6-7, few imperative conclusions are drawn along with future research directions and suggested implications.

ISSN 1943-670X

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International Journal of Industrial Engineering, 20(9-10), 574-588, 2013

A COMINED APPROACH OF CYCLE TIME ESTIMATION IN MASS CUSTOMIZATION ENTERPRISE Feng Liang1*, Richard Y K Fung2 and Zhibin Jiang3 Dept. of Industrial Engineering, Nankai University, Tianjin 300457, China 2 Department of Manufacturing Engineering & Engineering Management City University of Hong Kong, Hong Kong, China 3 Dept. of Industrial Engineering, Shanghai Jiao Tong University, Shanghai 200240, China 1

To enhance customer satisfactions and improve ability of quick responses, the production type of mass customization is advocated in many manufacturing enterprises. But in the mass customization enterprises, the customization demands will influence the standard cycle time estimation, which is essential in the analysis of contracts negotiation, capacity planning, and the assignments of due dates. Hence in this paper, a combined methodology employing an analytical model and a statistical regression method is proposed to facilitate the cycle time estimation in the mass customization enterprise. Using inferential reasoning for the analytical optimal model for cost minimization, it is deduced that the relationship between the customization degree and cost coefficient provider an efficient way to estimate the cycle time accurately. And their relationship is described with a statistical regression method. Finally, a case study from a bus manufacturing enterprise is used to illustrate the detailed estimation procedures and the further discussion is presented to explicate the significance for practice. Key words: Cycle Time; Mass Customization; Statistics Regression; Customization Degree; Cost Coefficient

1.

INTRODUCTION

One of the essential criteria having reliable due date commitments and maintaining high level of customer service is to have accurate estimates of cycle time. Owing to the lack of the fast and accuracy cycle time estimation methods in the mass customization enterprise, practitioners often use constant cycle times as bases for due date assignment and scheduling. However, the constant cycle time is so much simplified that due dates and schedules may not be assigned and constructed with acceptable accuracy. Actually in many production systems, this approach results in a high degree of late deliveries as the mean cycle-time is used as a basis to determine the delivery date. Therefore, the development of a model for cycle time estimation for the mass customization enterprise is essential though it may be rather complex. However, beyond the objective of due date setting, accurate cycle time estimates are also needed for better management of the shop floor control activities, such as order review/release, evaluation of the shop performance, identification of jobs that requires expediting, leadtime comparisons, etc. All these application areas make the cycle time estimation problem as important as other shop floor control activities (Sabuncuoglu and Comlekci, 2002). In fact, in the mass customization enterprise, the difficulty of cycle time estimation is not only due to the complexity of manufacturing systems, but also the high customization degree. It is well known that the actual cycle time may vary from the theoretical cycle time because of the demands of customization. For example, in an automobile enterprise which is a typical mass customization enterprise, there are 35 important parts in which 14 parts are optional for the customers. Therefore the cycle time vary from 20 days to 24 days. If the average cycle time is determined as the promised cycle time, the delivery late rate may be 23%. Hence in order to avoid late deliveries, the actual cycle time has to be determined according to the required customization degree. However under a mass customization environment, estimating the cycle time as the important base to meet due dates on time and utilize existing capacity efficiently is a complex problem than in other production systems due to the example stated below. According to the statistics and analysis of history production and after service data in a bus manufacturing company, the measures of customer satisfaction on the six factors as shown in Figure 1.

* Correspondence author: Dr Feng Liang, Dept. of Industrial Engineering, Nankai University, 23 Hongda Street, Tianjin Economical Development Area, Tianjin 300457, China. Phone: (+86) 22 6622 9204, Fax: (+86) 22 6622 9204, Email: [email protected].

ISSN 1943-670X

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International Journal of Industrial Engineering, 20(11-12), 589-601, 2013

SYSTEM ENGINEERING APPROACH TO BUILD AN INFORMATION SYSTEM FOR EMERGENCY CESAREAN DELIVERIES IN SMALL HOSPITALS Gyu M Lee Department of Industrial Engineering, Pusan National University, Korea, Republic of The human is an imperfect being so that he/she has a limitation in perceiving the situations appropriately and making a right decision quickly. His/her perceptions and decisions often come from the personal experiences and characteristics. This vulnerability leads to the frequent errors or mistakes and aggravates things in an emergency situation of time pressure and complex confusions. In a situation where an emergency cesarean delivery (ECD) is required, the immediate and appropriate medical cares are very important to the fetus and the mother. However, the number of high-risk pregnancy obstetrics doctors is decreasing in recent days and more medical staffs are currently in a great need. The American College of Obstetricians and Gynecologists (ACOG) stated in 1989 that hospitals with obstetric services should have the capability to begin an ECD within 30 minutes of the decision. This requirement places intense time pressure on the preparation and surgical teams. A distributed, mobile communication and information system to facilitate ECDs at Pusan National University Hospital has been developed along with its healthcare staffs. The developed ECD Facilitator has been demonstrated to the staff at the hospital and their responses has been obtained to assess that such a system would reduce the decision-to-incision intervals (DII) to well below the 30-minute ACOG guideline and reduce the likelihood of human errors that compromise patient safety. This system engineering approach can be readily adaptable to other emergency disastrous situations.

1. INTRODUCTION The operating room (OR) in hospitals is a complex system in which the effective integration of personnel, equipment, and information is essential to the delivery of high quality health care services. A team of surgeons, nurses, and technicians with appropriate knowledge and skills must be assembled to perform many complex tasks necessary to properly prepare for and successfully complete the surgery. Then, they must have the appropriate equipment, supplies, and materials at hand, and those items must not only be present, but properly placed and correctly configured to be used by the OR team. Besides the knowledge and skills they bring to the OR, team members require additional information to support their decisions and guide their actions, including accurate vital data, proper protocols and procedures, and medical reference information, particularly if they encounter unfamiliar situations or complications in the course of the surgery. All of these components in the complex OR system must be properly coordinated. The surgery must be carefully planned, personnel must be in the right places at the right times, activities must be properly synchronized, logistics must be executed efficiently, and the right information must be available when and where needed. This coordination is made more difficult by the fact that emergency surgery is time-critical, where the life of the patient may depend on the hospital’s ability to assemble the OR team, prepare the OR and equipment, and provide the necessary information to begin a surgical procedure within minutes. Emergency surgeries challenge even the largest, most capable hospitals, but they are especially challenging for small, rural hospitals that do not have enough personnel and resources. When a patient needing emergency surgery presents at a small hospital, the medical staffs may be at home, on call, and must be contacted and summoned to the hospital. As the team members begin arriving, they must start preparing the patient, the OR and equipment for surgery. This is often complicated by the fact that small hospitals have few ORs and it may not be practical to have one always ready for any specific class of emergency surgical procedure, thus requiring a more lengthy preparation process. Moreover, small, rural hospitals often lack the information infrastructure needed to deliver patient data, procedural knowledge, and medical reference information in an effective and timely manner. The potential chaos and confusion of an emergency surgery in the middle of the night is compounded by the fact that the medical personnel involved in the case are human, and human beings are fallible. Since human beings are limited by nature in their abilities to sense, perceive, and act accurately and quickly, and innate cognitive biases compromise their judgment and decision making capabilities. These fallibilities combine and interact with characteristics of the complex system and complicated situation, as described above, to yield delays and errors that may lead to further harm to the emergency patient, or even, in some cases, the death. With that principle in mind, we utilize medical knowledge and engineering methods to design efficient, best-practice processes and to create information and communication systems to facilitate emergency surgeries in small, rural hospitals. The developed Emergency Cesarean Delivery Facilitator (ECD Facilitator) is a job performance aid to help summon, ISSN 1943-670X

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International Journal of Industrial Engineering, 20(11-12), 602-613, 2013

EXPLORING BUSINESS MODELS FOR APPLICATION SERVICE PROVIDERS WITH RESOURCE BASED REVIEW JrJung Lyua, Chia-Hua Changb *, aDepartment of Industrial and Information Management, National Cheng Kung University, Tainan 701, Taiwan, ROC [email protected] bDepartment of Management and Information Technology, Southern Taiwan University of Science and Technology, Tainan City 710, Taiwan, ROC [email protected] The Application Service Provider (ASP) concept is extended from traditional information application outsourcing as currently used by numerous industries for information applications. Although value-added service can be generated with ASPs, it can still have a high failure rate in ASP markets. This research applies Resource Based Theory (RBT) to evaluate the business models of ASPs in order to assess their positions and provide suggestions for development directions. Top ten application service providers among the fifty most significant ASPs were selected to investigate the global markets of the ASP industry and the trend of services beforehand. Then three of them were explored to illustrate the RBT review. Based on the market review and the empirical investigation, it was found that only a few ASPs can provide integrated service contents which can adapt to fit the real demands of customers. ASPs should focus on the perspective of the ecosystem and consider employing strategic alliances in order to provide an integrated solution for their customers and sustain competitive advantage. Keywords: Application Service Provider, Resource Based Theory, Outsourcing Strategy, Business Model

1. INTRODUCTION Information technology (IT) has become one of the most critical survival strategies for enterprises wishing to adapt to rapidly evolving environments as a result of the advent of the network economy. To retain competitive advantage, enterprises must seek out more efficient ways to utilize available resources. Thus, when internal resources cannot meet environmental changes, enterprises may turn to outsourcing strategy and ally with their suppliers to better use external resources. In this way, industries can broaden their services, reduce transaction cost, maintain core competence, and increase benefit margins through the employment of such combinations of outsourced resources (Cheon et al, 1995). Since information technology has become a critical resource for business, outsourcing strategy is therefore an option involving commitment of all or parts of information system (IS) activities, manpower and other IS resources to exterior suppliers (Adeley et al., 2004). The most critical reason for employing IS outsourcing strategy is to decrease the inherent risks and compensate for the lack of abilities to develop such strategic applications in-house. Application service providers (ASPs) have emerged in recent years offering services like traditional outsourcing, which receive much attention in IS markets. Although the market scale of ASPs shows continued growth, most enterprises do not realize or are not familiar with the way to outsource through ASPs (Currie and Seltsikas, 2001; Chen and Soliman, 2002). Therefore, the purpose of this research is to develop an evaluation structure for exploring and evaluating ASPs from a supply side perspective. The consequences could then help ASPs recognize corresponding strategic marketing directions in the future.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 20(11-12), 602-613, 2013

EXPLORING BUSINESS MODELS FOR APPLICATION SERVICE PROVIDERS WITH RESOURCE BASED REVIEW JrJung Lyua, Chia-Hua Changb *, aDepartment of Industrial and Information Management, National Cheng Kung University, Tainan 701, Taiwan, ROC [email protected] bDepartment of Management and Information Technology, Southern Taiwan University of Science and Technology, Tainan City 710, Taiwan, ROC [email protected] The Application Service Provider (ASP) concept is extended from traditional information application outsourcing as currently used by numerous industries for information applications. Although value-added service can be generated with ASPs, it can still have a high failure rate in ASP markets. This research applies Resource Based Theory (RBT) to evaluate the business models of ASPs in order to assess their positions and provide suggestions for development directions. Top ten application service providers among the fifty most significant ASPs were selected to investigate the global markets of the ASP industry and the trend of services beforehand. Then three of them were explored to illustrate the RBT review. Based on the market review and the empirical investigation, it was found that only a few ASPs can provide integrated service contents which can adapt to fit the real demands of customers. ASPs should focus on the perspective of the ecosystem and consider employing strategic alliances in order to provide an integrated solution for their customers and sustain competitive advantage. Keywords: Application Service Provider, Resource Based Theory, Outsourcing Strategy, Business Model

1. INTRODUCTION Information technology (IT) has become one of the most critical survival strategies for enterprises wishing to adapt to rapidly evolving environments as a result of the advent of the network economy. To retain competitive advantage, enterprises must seek out more efficient ways to utilize available resources. Thus, when internal resources cannot meet environmental changes, enterprises may turn to outsourcing strategy and ally with their suppliers to better use external resources. In this way, industries can broaden their services, reduce transaction cost, maintain core competence, and increase benefit margins through the employment of such combinations of outsourced resources (Cheon et al, 1995). Since information technology has become a critical resource for business, outsourcing strategy is therefore an option involving commitment of all or parts of information system (IS) activities, manpower and other IS resources to exterior suppliers (Adeley et al., 2004). The most critical reason for employing IS outsourcing strategy is to decrease the inherent risks and compensate for the lack of abilities to develop such strategic applications in-house. Application service providers (ASPs) have emerged in recent years offering services like traditional outsourcing, which receive much attention in IS markets. Although the market scale of ASPs shows continued growth, most enterprises do not realize or are not familiar with the way to outsource through ASPs (Currie and Seltsikas, 2001; Chen and Soliman, 2002). Therefore, the purpose of this research is to develop an evaluation structure for exploring and evaluating ASPs from a supply side perspective. The consequences could then help ASPs recognize corresponding strategic marketing directions in the future.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 20(11-12), 614-630, 2013

HYBRID FLOW SHOP SCHEDULING PROBLEMS INVOLVING SETUP CONSIDERATIONS: A LITERATURE REVIEW AND ANALYSIS Márcia de Fátima Morais, Moacir Godinho Filho, Thays Josyane Perassoli Boiko Affiliation: Federal University of São Carlos Department of Industrial Engineering Rodovia Washington Luiz, km 235 - São Carlos - SP - Brazil email: [email protected] This research is dedicated to the Production Scheduling Problem in a hybrid flow shop with setup times separated from processing times. The goal is to identify and analyze the current literature to identify papers that develop methods to solve this problem. In this review, it was possible to identify and analyze 72 papers that have addressed this issue since 1991. Analyses were performed using the number of papers published over the years, the approach used in the development of the methods for the solutions, the type of objective function, the performance criterion adopted, and the additional constraints considered. The analysis results provide some conclusions about the state of the art in the subject and also enable us to identify suggestions for future research in this area. Keywords: Production Scheduling, Hybrid Flow Shop, Sequence-Dependent Set-up Time, Sequence-Independent Set-up Time.

1. INTRODUCTION In scheduling theory, a multi-stage production process with the property that all of the products must pass through a number of stages in the same order is classified as a flow shop. In a simple flow shop, each stage consists of a single machine that handles at most one operation at a time. When it is assumed that, at least in one stage, a number of machines that operate in parallel are available, this model is known as a hybrid flow shop (Sethanan, 2001). According to Ruiz and Vázquez-Rodríguez (2010), a hybrid flow shop (HFS) system processes jobs in a series of production stages, each containing parallel machines, with the aim of optimizing one or more objective functions. Solving the production scheduling in such an environment is, in most cases, NP-hard. Many real manufacturing systems are hybrid flow shop systems. The products manufactured in such an environment can differ in certain optional components; consequently, the processing time on a machine differs from one product to the next, and the need to prepare one or more machines before beginning a job or after finishing a job is frequently present. In scheduling theory, the time required to shift from one job to another on a given machine is defined as the additional production cost or the setup time. The corresponding scheduling problems, which consider the setup times, have a higher computational complexity (Burtseva, Yaurima and Parra, 2010). An explicit treatment of the setup times in most of the applications is required and represents a special interest, as machine setup time is a significant factor for production scheduling in many practical cases. Setup time could easily consume more than 20% of the available machine capacity if it is not handled well (Pinedo, 2008). Many examples of scheduling problems that consider separable setup times are given in the literature, including electronics manufacturing, automobile assembly plants, the packaging industry, the textile industry, steel manufacturing, airplane engine plants, label sticker manufacturing companies, the semiconductor industry, maritime container terminals, and the ceramic tile manufacturing sector, as well as in the electronics industry in sections for inserting components on printed circuit boards (PCB), where this type of problem occurs frequently. Hybrid flow shop scheduling problems that consider setup times are among the most difficult classes of scheduling problems. Research in production scheduling began in the 1950s; however, until the mid-1990s, most research considered setup times to be irrelevant or a slight variation and usually included it in the processing times of jobs and/or batch jobs (Allahverdi, Gupta and Aldowaisan, 1999). Ruiz and Vázquez-Rodríguez (2010) show that studies that address hybrid flow shop scheduling and that consider separate setup cost or time arose in the early 1990s. Within this context, the main goal of this research is to perform a literature review on hybrid flow shop scheduling problems with setup considerations. After the literature review, this paper also presents an analysis of this review, attempting to find literature gaps and suggestions for future research in this field.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(1), 1-17, 2014

DEVELOPING A ROBUST PROGRAMMING APPROACH FOR THE RESPONSIVE LOGISTICS NETWORK DESIGN UNDER UNCERTAINITY Reza Babazadeh , Fariborz Jolai, Jafar Razmi, Mir Saman Pishvaee Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran Iran, Islamic Republic Of Operational and disruption risks derived from the environment have forced firms to design responsive supply chain networks. This paper presents a multi-stage multi-product robust optimization model for responsive supply chain network design (SCND) under operational and disruption risks. First, a deterministic mixed-integer linear programming (MILP) model is developed considering different transportation modes, outsourcing, flexibility and cross-docking options. Then, the robust counterpart of the presented model is developed to deal with the inherent uncertainty of input parameters. The proposed deterministic and robust models are assessed under both operational and disruption risks. Computational results show the superiority of the proposed robust model in managing risks with a reasonable increase in the total costs compared to deterministic model. Keywords: Robust Optimization, Responsive Supply Chain Network Design, Operational & Disruption Risks. 1. INTRODUCTION Facility location is one of the most important decisions in the supply chain network design (SCND) problem and plays a crucial role in the overall performance of the supply chain. Generally, the SCND problem includes determining the numbers, locations and capacities of facilities, as well as the amount of shipments between them (Amiri, 2006). Nowadays, time and cost are common gauges used to assess the performance of the supply chains and both are minimized, as they are treated simultaneously. The delivery time criterion is considered to be an individual objective that leads to a bi-objective problem. Minimizing delivery time and cost objectives in the form of a bi-objective problem are in conflict with each other (Pishvaee and Torabi, 2010). That is, quick delivery implies high amount of costs. The time minimization objective, however, can be integrated in cost objective when it is expressed in terms of monetary value. Increased environmental changes in the competitive markets force manufacturing companies to be more flexible and improve their responsiveness (Gunasekaran and Kobu, 2007). Some components, such as direct shipments from the supply centres to customers and decisions on opening or closing facilities (plants, distribution centres and etc.) for the forward seasons (Rajabalipour et al., 2013), utilizing different transportation modes can improve the flexibility of an SCN. Cross-docking is a logistics function in which products are shipped directly from the origin to the destination, without being stored in warehouses or distribution centres (Choy et al., 2012). Utilizing cross-dock centres as an intermediary stage between supply centres and customer zones leads to significant advantages for the manufacturing and service industries (Bachlaus et al., 2008). In recent decades, some companies, including Wal-Mart used cross-docks in different sites to achieve competitive advantages in distribution activities. Although inventory holding is not attractive, especially in lean production systems, it could play a significant role in dealing with supply and demand uncertainty (You and Grossmann, 2008). In today’s world, the increased diversity of customer needs prevents manufacturing and service industries from making fast changes, unless it is done through outsourcing. Outsourcing is performed for many reasons, such as saving on costs, focus on core business, quality improvement, knowledge, reduced time to market, enhance capacity for innovation and risk management (Kang et al. 2012). Some of companies, like Gina and Zara Tricot, which use the outsourcing approach, have a massive advantage (Choudhury and Holmgren, 2011). Many previously presented models consider fixed capacities for all facilities, whereas determining capacity of facilities is often difficult in practice (Wang et al., 2009). Therefore, capacity level of facilities should be determined as a decision variable in mathematical programming models. Since opening and closing of facilities are strategic and timeconsuming decisions (Pishvaee et al., 2009), an SCN should be designed in the way that could be sustained under operational and disruption risks. Chopra and Sodhi (2004) and Chopra et al. (2005) mentioned that the organizations should consider uncertainty issues with its various forms in supply chain management to deal with their destructive and burdensome effects on supply chain. Exploring various sources proves that most presented works in the SCND area assume that input parameters, such as demands, are deterministic (see Melo et al., 2009; Klibi et al. 2010). Although some studies have considered the SCND under tentative conditions, most of them used the concept of stochastic and chance constrained programming methods (Alonso-Ayuso et al., 2003; Santoso et al., 2005; Listes and Dekker, 2005; Salema et al., 2007). The major drawbacks ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(1), 18-32, 2014

DEVELOPMENT OF A CLOSED-LOOP DIAGNOSIS SYSTEM FOR REFLOW SOLDERING USING NEURAL NETWORKS AND SUPPORT VECTOR REGRESSION Tsung-Nan Tsai1 and Chiu-Wen Tsai2 Department of Logistics Management, Shu-Te University, Kaohsiung, 82445, Taiwan 2 Graduate School of Business and Administration, Shu-Te University, Kaohsiung, 82445, Taiwan Corresponding author’s e-mail: {Tsung-Nan Tsai, [email protected]} 1

This study presents an industrial application of artificial neural network (ANN) and support vector regression (SVR) to diagnose control reflow soldering process in a closed-loop framework. Reflow soldering is the principal process for the fabrication of a variety of modern computer, communication, and consumer (3C) electronics products. It is important to achieve robust electrical connections without changing the mechanical and electronic characteristics of the components during reflow soldering process. In this study, a 38-4 experimental design was conducted to collect the structured process information. The experimental data was then used for data-training via the ANN and SVR techniques to investigate both the forward and backward relationships between the heating factors and the resultant reflow thermal profile (RTP) and so as to develop a closed-loop reflow soldering diagnosis system. The proposed system includes two modules: (1) a forward-flow module used to predict the output elements of the RTP and evaluate its performance based on ANN and a multi-criteria decision-making (MCDM) criterion; (2) a backward-flow module employed to ascertain the set of heating parameter combinations which best fulfill the production requirements of the expected throughput rate, product configuration, and the desired solderability. The efficiency and cost-effectiveness of this methodology were empirically evaluated and the results show the promising to improve soldering quality and productivity. Significance: The proposed closed-loop reflow soldering process diagnosis system can predict the output elements of a reflow temperature profile according to process inputs. This system is also able to ascertain the set of heating parameter combinations which best fulfill the production requirements and the desired solderability. The empirical evaluation demonstrates the efficiency and cost-effectiveness for the improvements of soldering quality and productivity. Keywords: SMT, analytic hierarchy process, neural network, reflow soldering, support vector regression

1

INTRODUCTION

A high-speed surface mount technology (SMT) is an important development to fabricate many types of modern 3C products in the electronics assembly industry. A SMT assembly process consists of three main process steps: the stencil printing application, component placement, and reflow soldering. Reflow soldering is the principal process used to melt powder particles in the solder paste and then solidify them to create strong metallurgical joints between the pads of printed circuited board (PCB) and the surface mounted devices (SMDs) through a reflow oven. The reflow soldering operation is widely recognized as a key determinant of production yield in PCB assembly (Soto, 1998; Parasad, 2002). A poor understanding of reflow soldering behavior can result in remarkable troubleshooting time, soldering defects, considerable manufacturing costs. The required function of a reflow oven is to heat the assembled boards to a predefined temperature at the proper heating rates for a specific elapsed time. The forced convection reflow oven is the most commonly used heating source in the SMA since it meets the economic and technical requirements of mass production. A reflow thermal profile (RTP) is a time-temperature graph used to monitor and control the heating phases and duration, so that the assembled boards are heated enough to form reliable solder joints without changing the mechanical and electronic characteristics of the components. An inhomogeneous and inefficient reflow temperature profile may cause various soldering failures (Illés, 2010), as shown in Figure 1. A typical RTP is comprised of preheating, soaking, reflowing and cooling phases using a leaded solder paste, as shown in Figure 2. During the preheating phase, the board and the relevant components are heated quickly from room temperature to about 150 ºC. In the soaking phase, the temperature continues rising to approximately 180 ºC. At the same time, flux is activated to gradually wet and clean oxidation from the surfaces of the metal pads and component leads. The solder paste is melt and changing into a liquid solder mass in the reflowing phase. Eventually, during the cooling phase, electrical connections form between the component leads and the PCB pads. The grey area between the contoured and faint lines shows the acceptable temperature range that might produce acceptable soldering quality according to the specification provided by solder paste maker (Itoh, 2010).

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(1), 33-44, 2014

EFFICIENT DETERMINATION OF HELIPORTS IN THE CITY OF RIO DE JANEIRO FOR THE OLYMPIC GAMES AND WORLD CUP: A FUZZY LOGIC APPROACH Claudio S. Bissoa, Carlos Patricio Samanezb a Production Engineering Program Federal University of Rio de Janeiro (UFRJ), COPPE, Brazil b Industrial Engineering Department Pontifical Catholic University of Rio de Janeiro PUC-Rio, Brazil The purpose of this study was to determine a method of evaluation for the use and adaptation of Helicopter Landing Zones (HLZs) and their requirements for registered public-use for the Olympic Games and the World Cup. The proposed method involves two stages. The first stage consists of clustering the data obtained through the Aerial and Maritime Group/Military Police of the State of Rio de Janeiro (GAM/PMERJ). The second stage uses the weighted ranking method. The weighted ranking method was applied to a selection of locations using fuzzy logic, linguistic variables and a direct evaluation of the alternatives. Based upon the selection of four clusters, eight HLZs were obtained for ranking. The proposed method may be used to integrate the air space that will be used by the defense and state assistance agencies with the locations of the sporting events to be held in 2014 and 2016. Significance: In this paper we proposed a model for evaluating the use and adaptation of Helicopter Landing Zones. This method involves clustering data and the selection of locations using fuzzy logic and a direct evaluation of the alternatives. The proposed method allowed for precise ranking of the selected locations (HLZs) contributing to the development of public policies aimed at reforming the local aerial resources. Keywords: Fuzzy logic, Site selection, Transport, Public Policy.

1. INTRODUCTION The city of Rio de Janeiro will host the 2014 World Cup and 2016 Olympic competitions. Thus, the development of more effective and technical mapping is urgently needed to rationalize the use of aerial resources (helicopters) that belong to the state of Rio de Janeiro. Consequently, the helicopters will meet the demands for human health and safety better, as well as actively participate in these large sporting events. The main objective of this study was to determine a method that could be used to justify potential investment opportunities in registered public-use heliports based on their requirements and their locations relative to points of public interest. To accomplish this task, Helicopter Landing Zones, or HLZs, were mapped and identified by the Aerial and Maritime Group (Grupamento Aéreo e Marítimo (GAM)) of the Military Police of the State of Rio de Janeiro (Polícia Militar do Estado do Rio de Janeiro (PMERJ)). In the city of Rio de Janeiro, various zones were identified by the GAM as HLZs. Yet, these zones do not have the appropriate identification, illumination or signage. Thus, these HLZs do not meet the appropriate technical standards that would define them as zones being appropriate for helicopter landing. Here, several aspects, including the proximity of the HLZs to hospitals, PMERJ (Military Police of the State of Rio de Janeiro) units, Fire Department (CBMERJ), Civil Police (PCERJ) and the major sporting competition locations, were used to identify the most relevant HLZs in the city of Rio de Janeiro (according to these criteria). In addition, this study serves to stimulate the use of the HLZs and provide subsidies for developing public policies for streamlining the existing aerial resources (helicopters) that belong to corporations within the state of Rio de Janeiro. Considering that is not likely that the city will have a fitting conventional terrestrial transport that can handle the numerous tourists and authorities, Rio de Janeiro will face an increased demand for air transport via helicopter to move between the different sports facilities, integrated with the local assistance and defense agencies. Today, Rio de Janeiro faces a challenge that it has never face before. The burden of investments in various sectors – led by the oil and gas industry – sum, according to the Federation of Industries of the State of Rio de Janeiro (FIRJAN), $ 76 billion during the period from 2011 to 2013. This is one of the largest concentrations of investment in the world, given the volume of investments in relation to the small territorial dimension of the state. Air transport demand brought by those investments, combined with the fact that the city will host the 2014 World Cup and the 2016 Olympic Games, requires a focused technical mapping that allows streamlining the aerial resources ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(1), 45-51, 2014

AN APPLICATION OF CAPACITATED VEHICLE ROUTING PROBLEM TO REVERSE LOGISTICS OF DISPOSED FOOD WASTE Hyunsoo Kim1, Jun-Gyu Kang2*, and Wonsob Kim3 Department of Industrial and Management Engineering, University of Kyonggi San 94-6, Iui-dong, Yeongtong-gu, Suwon, Gyeonggi-do 443-760, Republic of Korea 2 Department of Industrial and Management Engineering, Sungkyul University Sungkyul Daehak-Ro 53, Manan-gu, Anyang, Gyeonggi-do 430-742, Republic of Korea *Corresponding author’s e-mail: [email protected] 1,3

Reverse logistics amended transportation of food waste from local collecting areas to designated treatment facilities produce enormous amounts of greenhouse gas. The Korean government has recently introduced the RFID technology in hopes of reducing CO2 production problems. In this study, we evaluated the reduction of total route distance required for reverse logistics based on the total weight of food waste in each collecting area. We defined the testing environment as CVPR (capacitated vehicle routing problem) based on the actual field data. As our first alternative method, we introduced Fixed CVRP for the improvement of current reverse logistics and also applied the daily Dynamic CVRP, which considers daily weight information of total food waste at each collecting area in order to determine the optimum routes for reverse logistics. We performed and compared experimental results of total routing distance using three different scenarios; current, Fixed CVRP, and daily Dynamic CVRP. Key words: Reverse logistics, Food waste, CVRP, Sweep method, RFID, Greenhouse gas (CO2)

1. INTRODUCTION The amount of disposed food waste has been continuously increasing since January of 2013 when the Korean government prevented the dumping of food waste into the marine. This act was a correspondence to the 1996 London Dumping Convention Protocol to stop marine pollution by dumping of waste and other matter (Daniel. 2012). Food waste is the largest portion (28.8%) of domestic municipal waste and the disposed amount has been increasing continuously since 2005; 65ton/day (2005), 72.1ton/day (2007), 79.1ton/day (2009), and 79.8ton/day (2011) (Seoul Metropolitan Government. 2012). In order to reduce and properly manage disposed food waste, the Ministry of Environment and the Ministry of Public Administration and Security started a pilot project in 2011 over the weight-based charging system, under which the fee charged increases in proportion to the weight of food waste discarded using RFID technology. The system can charge a monthly fee to an individual based on the total amount of disposed food waste measured via RFID reader equipped containers. Originally operational in only 10 of 229 local governments, this system has now spread to 129 local governments as of June, 2013. According to the report from the Gimcheon-gu local government in Gyeongsangbuk-do provincial government, which has already adopted this system, 47% of disposed food waste has been reduced since 2011 (Korea Environment Corporation. 2012). With the advent of RFID technology, it has become possible to take full advantage of all information (Zhang et al. 2011). Currently, the RFID technology solely operates using the identification of the individual whom disposes food waste and its measured weight. Unfortunately, however, the important information of the total weight of food waste disposed at each container, which can be obtained from current RFID system, is not being used by reverse logistics providers (we call ‘collectors’) who collect the disposed food waste from each containers. Therefore, fixed routings based on fixed schedules are still applied for reverse logistics of disposed food waste now. The problem dealt in this paper is considered as a Vehicle Routing Problem (VRP, here after), which is a combinatorial optimization and integer programming problem designing optimal delivery or collection routes from one or several depots to a number of geographically scattered cities of customers with a fleet of vehicles (Laporte, 1992). In general, the VRP comprises of two combinatorial optimization problems, i.e., the Bin-Packing Problem (BPP) and the Travelling Salesman Problem (TSP). Assigning each customer to a vehicle is considered a BPP while designing the optimal route for each vehicle with assigned customers is considered a TSP (Fenghe and Yaping, 2010). VRP is the intersection of two difficult problems, typically known as NP-hard problem, which becomes more difficult or even impossible to solve as the number of customers or vehicles increases (Lin et al., 2014). Since the first proposal of VRP by Danzig and Ramser in 1959, it has been playing an important role in the fields of transportation, distribution and logistics. According to additional practical restrictions, there exists a wide variety of VRPs. Along with the traditional variation of VRPs, Capacitated VRP (CVRP), VRP with Time Window (VRPTW), Multi depot VRP (MDVRP), and ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(2), 53-65, 2014

DELIVERY MANAGEMENT SYSTEM USING THE CLUSTERING BASED MULTIPLE ANT COLONY ALGORITHM: KOREAN HOME APPLIANCE DELIVERY Taeho Kim and Hongchul Lee School of Industrial Management Engineering, Korea University, Seoul, Republic of Korea

This paper deals with the heterogeneous fleet vehicle routing and scheduling problems with time windows (HFVRPTW) in the area of Korean home appliance delivery. The suppliers of modern home appliance products in Korea not only have to provide the traditional service of simply delivering goods to customers within the promised time, but they also need to perform additional services such as installation of the product and explanation of the products functions. Therefore, businesses reducing the delivery cost while improving the quality of the service experienced by customers is an important issue. In order to meet these two demands, we generated a delivery schedule by using a heuristic clustering-based multiple ant colony system (MACS) algorithm. In addition, to improve service quality, we set up an expert system composed of a manager system and an android-based driver system. The system was tested for home appliance delivery in Korea. This paper is significant in that it constructs an expert system for the entire process of distribution, from the generation of an actual schedule to management system setup. Keywords: HFVRPTW, Ant colony algorithm, Home appliance delivery, Android; Information System

1. INTRODUCTION The physical distribution industry is facing a rapid change in its business environment due to the development of information and communication technology and the spread of Internet accessibility. Products are ordered both online and offline. Through online communities, customers can freely share information relating to the entire process of product purchasing such as product functions, delivery and installation. In particular, products handled in home appliance delivery in recent years, like Smart TVs, notebooks, air conditioners and refrigerators, have complex functions in contrast to their predecessors. Hence why it is important to provide installation and demonstration service while guaranteeing accurate and timely delivery. Such extended services have actually become an important factor for customers in building an image of a given company. Accordingly, separately from the traditional work of simply delivering a product to a customer, qualitative improvements of service, like product installation and explanation of product functions, have become an important part of home appliance delivery in Korea (Kim et al., 2013). From the companies’ point of view, reducing delivery costs while improving the quality of delivery service experienced by customers is an important problem. Basically, the problem of satisfying the constraints of delivery time desired by customers while finding the shortest traveling route for vehicles is known as the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW model is a representative NP-hard problem (Lenstra and kan, 1981; Savelsbergh, 1985). There are many studies that have used metaheuristics to solve this problem (Cordeau et al., 2001; Haghani and Banihashemi, 2002; Sheridan et al., 2013). In this paper, we used the ant colony system (ACS) among the various metaheuristic methods to generate schedules (Dorigo and Gambardella, 1997a, 1997b). ACS has the advantage of being able to respond flexibly even when the constraint rules change. We also utilized a heuristic clustering algorithm in this paper to improve the calculation speed of the local search part that requires the longest calculation time among the ACS processes (Dondo and Cerdá, 2007). A delivery management system is required for qualitative delivery service improvement. (Santos et al., 2008; Moon et al. 2012). We constructed an Android-based delivery management system to flexibly handle such problems as delivery delays and delivery sequence changes that can occur due to the characteristics of delivery work. With this system, managers can easily manage various accidents that can occur during deliveries and more effectively monitor the locations of drivers and manage the delivery progress rate as well as idle drivers.

2. LITERATURE REVIEW Ever since Dantzig and Ramser (1959) attempted to solve the vehicle routing problem (VRP) by using an LP heuristic, many researchers have introduced various mathematical models and solutions. Of the VRP types, VRPTW is the VRP with the customer-demanded time constraint. Since VRPTW is an NP-hard problem, an optimum solution within the restricted time cannot be found. Studies related to VRPTW have advanced greatly with insertion heuristic research (Solomon, 1987) as the starting point. Supported by recent advances in computer technology, studies applying metaheuristic methods such as simulated annealing (Osman,1993; Czech and Czarnas, 2002; Lin et al., 2011), tabu search ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(2), 66-73, 2014

INFLUENCE OF DATA QUANTITY ON ACCURACY OF PREDICTIONS IN MODELING TOOL LIFE BY THE USE OF GENETIC ALGORITHMS Pavel Kovac, Vladimir Pucovsky, Marin Gostimirovic, Borislav Savkovic, Dragan Rodic University of Novi Sad, Faculty of Technical Science, Trg Dositeja Obradovica 6, 21000 Novi Sad, Serbia [email protected], [email protected], [email protected], [email protected], [email protected] It is widely known that genetic algorithms can be used in search space and modeling problems. In this paper theirs ability to model a function while varying the amount of input data is tested. Function which is used for this research is a tool life function. This concept is chosen because by being able to predict tool life, workshops can optimize their production rate – expenses ratio. Also they would gain profit by minimizing number of experiments necessary for acquiring enough input data in process of modeling tool life function. Tool life by its nature is a multiple factor dependent problem. By using four factors, to acquire adequate tool life function, vivid complexity is simulated while acceptable duration of computational time is maintained. As a result almost clear threshold, of data quantity inputted in optimization model to gain acceptable results in means of output function accuracy, is noticed. Keywords: Modeling; Genetic Algorithms; Tool Life; Milling; Heuristic Crossover

1. INTRODUCTION From early days when artificial intelligence was introduced, there is a prevailing trend of discovering capabilities which lies inside this branch of science. As all machine related domain, with this one being no exception, there are limits. These limits and boundaries of usage are often expanded and new purposes are constantly discovered. To be able to achieve this goal one must be a very good student of the best teacher that is known to mankind; mother nature. With an experience of more than five billion years our nature is a number one scientist and we are all proud that we have an opportunity to learn whatever she has to offer. Mastery of creation such a variety of living beings is no easy task and maintaining this delicate balance between species is something that requires time, experience and understanding. No scientist is able to create something graceful, like variety of life on Earth, by share coincidence. There has to be a consistency in process of creating and maintaining this complexity of living beings. Law which lies behind this consistency had prevailed more than we can remember and is a simple postulate which tells us that only those who are most adaptable to their environment will survive. By surviving more than others, less adaptable individuals, every living organism is increasing chance to mate, with equally adaptable member of same specie and creating offspring which posses the same, or higher level of adaptability to their environment. This law of selection is something that enabled creation of this world that we live in. Seeing its effectiveness yet understanding simplicity of this concept, we decided to model it. One way of succeeding in this is through genetic algorithms (GA). Since they have been introduced, in early 1970’s, GA present a very powerful tool in space search and optimization fields. Introduce them to a certain area and, with a proper guidance, they will create a population of their own and eventually yield individuals with highest attributes. Through time many scientist manage to successfully implement GA as a problem solving technique. Sovilj et al. (2009) developed a model for predicting tool life in milling process. Pucovsky et al. (2012) studied dependence between modeling ability of tool life with genetic algorithm and the type of function. Čuš and Balič (2003) used GA to optimize cutting parameters in process of milling. Similar procedure for optimizing parameters in turning processes was employed by Srikanth and Kamala (2008). And optimization of multi-pass turning operations using genetic algorithms for the selection of cutting conditions and cutting tools with tool-wear effect has been successfully reported by Wang and Jahawir (2005). Zhu (2012) managed to implement genetic algorithm with local search in solving the job shop scheduling problem. Since job shop scheduling is major area of interest and progress, Wang et al. (2011) succeeded in constructing the genetic algorithm with a new repair operator for assembly procedure. Ficko et al. (2005) reported positive experiences in using GA in forming a flexible manufacturing system. Regarding tool life in face milling, statistical approach by the use of response surface method have been covered by Kadirgama et al (2008). Khorasani et al (2011) used both Taguchi’s design of experiment and artificial neural networks for tool life prediction in face milling. Pattanaik and Kumar (2011), using a bi-criterion evolution algorithm for identification of Pareto optimal solution, developed a system for product family formation in area of reconfigurable manufacturing. And knapsack problem is now widely considered as a classical example of GA implementation (Ezzaine, 2002). Taking in consideration weight and importance of milling tool life modeling with evolutionary algorithms, very small amount of articles on this subject was noticed. Also no papers discuss on influence of quantity of input data on results of genetic algorithms optimization function. In absence of these two facts this article is presented as a way to, at least partially, fill existing gap. ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(2), 74-85, 2014

PROACTIVE IDENTIFICATION OF SCALABLE PROGRAM ARCHITECTURES: HOW TO ACHIEVE A QUANTUM-LEAP IN TIME-TO-MARKET Christian Lindschou Hansen & Niels Henrik Mortensen Department of Mechanical Engineering Product Architecture Group The Section of Engineering Design & Product Development Technical University of Denmark Building 426 DK-2800 Kgs. Lyngby Email: [email protected], [email protected], This paper presents the Architecture Framework for Product Family Master Plan. This framework supports the identification of a program architecture (the way cost competitive variance is provided for a full range of products) for a product program for product-based companies during the early stages of a product development project. The framework consists of three basic aspects: the market, product program, production and a time aspect – captured in the multi-level roadmap. One of the unique features is that these aspects are linked, allowing for an early clarification of critical issues through a structured process. The framework enables companies to identify a program architecture as the basis for improving time-to-market and R&D efficiency for products derived from the architecture. Case studies show that significant reductions of development lead time up to 50% is possible. Significance: Many companies are front-loading different activities when designing new product programs. This paper suggests an operational framework for identifying a program architecture during the early development phases, to enable a significantly improved ability to launch new competitive products with fewer resources. Keywords: Product architecture, program architecture, product family, platform, time-to-market, scalability

1. INTRODUCTION Many industrial companies are experiencing significant challenges in maintaining competitiveness. There are many individual explanations behind these, but some of the common challenges that are often recorded from companies are:  Need to reduce time-to-market in R&D: o Shorter product life cycles are increasing the demand for faster renewal of the product program in order to postpone price drops and maintain competitive offerings (Manohar et al., 2010) o Loss of market share in highly competitive markets call for improved launch responsiveness to match and surpass the offerings of competitors (Chesbrough, 2013) o Protection of niche markets and their attractive price levels requires continuous multi-launches of competitive products (Hultink et al., 1997)  Need for achieving attractive cost and technical performance levels for the entire product program o Increased competitiveness requires all products to be attractive both cost wise and performance wise (Mortensen et al., 2010) o Focusing of engineering resources requires companies to scale solutions to fit across the product program (by sharing) and prepare them for future product launches (by reuse) (Kester et al., 2013) o Sales forecasts from global markets are affected by an increasing number of external influences making it more and more difficult to predict the sales of individual product variants, thus leaving no room for compromising competitive cost and performance for certain product variants (Panda and Mohanty, 2013) These externally induced challenges pose a major task to the whole company. As such, many approaches exist to handle these challenges which are of organizational- , process-, tool-, and competence nature originating within research from sciences across business, marketing, organization, technology, socio-technical, and engineering design. The research presented here originates within engineering design and product development focusing on the development of a program architecture for a company. Although originating from the engineering design domain which is naturally centered in the R&D function of a company, the development of program architectures have relations that stretches far into the marketing, product planning, sourcing, production, and supply chain domains as well as into the companies’ overall product strategy. ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(2), 86-99, 2014

AN APPROACH TO CONSIDER UNCERTAIN COMPONENTS’ FAILURE RATES IN SERIES-PARALLEL RELIABILITY SYSTEMS WITH REDUNDANCY ALLOCATION Ali Ghafarian Salehi Nezhada,*, Abdolhamid Eshraghniaye Jahromib, Mohammad Hassan Salmanic, Fereshte Ghasemid a M.Sc. Graduated Student of Industrial Engineering at Sharif University of Technology, Tehran, 14588-89694, Iran. b Associate professor of Industrial Engineering at Sharif University of Technology, Tehran, 14588-89694, Iran. c PhD Student of Industrial Engineering at Sharif University of Technology, Tehran, 14588-89694, Iran d M.Sc. Graduated Student of Industrial Engineering at Amirkabir University of Technology, Tehran, 15875-4413, Iran. * Author Phone Number: +98 936 337 7547 Fax Number: +98 331 262 4268 Emails: [email protected], [email protected],[email protected], [email protected]

Redundancy Allocation Problem (RAP) is a combinatorial problem to maximize system reliability by discrete selection from available components. The main purpose of this study is to prove the effectiveness of robust optimization to solve RAP. In this study it is assumed to have Erlang distribution density for components' failures where to implement robust optimization. We suppose that failure rate attains dynamic values instead of exact and fixed values. Therefore, a new calculation method is presented to consider dynamic values for failure rate in RAP. Another assumption is that each subsystem can have one of cold-standby or active redundancy strategies. Moreover, due to complexity of RAP, two Simulated Annealing (SA) and Ant Colony Optimization (ACO) algorithms are designed to determine the robust system with respect to uncertain values for parameters. In order to solve this problem and prove efficiency of proposed algorithms, a problem benchmark in literature is solved and discussed. Keywords: Reliability Optimization; Robust Optimization; Series-Parallel System; Uncertain Failure Rate; Ant Colony Optimization; Simulated Annealing.

1. INTRODUCTION In general, reliability is the ability of a system to perform and maintain its functions in routine circumstances, as well as hostile or unexpected circumstances. Redundancy Allocation Problem (RAP) is one of the classical problems in engineering and other sciences to plan the selection of components for a system simultaneously, where these components can be combined by different strategies. Generally, this problem is defined to maximize the system reliability such a way that some predetermined constraints such as total weight, total cost, and total volume be satisfied. The attractiveness of this problem to design an appropriate system will be arisen for different products with high reliability value. In general, it is possible to categorize the series-parallel systems into three major parts: the reliability allocation, the redundancy allocation and the reliability and the redundancy allocation. In the reliability allocation problems, the reliability of the components is determined such that the consumption of a resource under a reliability constraint is minimized while the redundancy allocation problem generally involves the selection of components and redundancy levels to maximize the system reliability given various system-level’s constraints [1]. In fact, we can implement two approaches to improve the reliability of such a system using RAP. The first one is to increase the reliability of the system components while the second one is using redundant components in various subsystems in the system [2; 3]. This problem also has four major inputs; λ   λ iz  which represents failure rate for



component

zi

i



in subsystem i , C  Ciz  and W   Wiz  which are cost and weight of component  i  i

subsystem i , respectively, and

    i t   which is switch reliability in subsystem

zi

for

i at a predetermined time t

. The general structure series-parallel systems is shown in Fig. 1 where i indicates index of each subsystem. Generally, previous studies are contributed in deterministic environment in which the failure rate of each component is constant. Conversely, in real world the precise failure rates for each component are usually very hard to estimate and it would be more practical to consider flexible values for these groups of parameters. This assumption seems more invaluable when the failure rates can be affected by different factors such as labors, machines, environmental conditions, and the way which components are using. In this study, it is assumed that there are no deterministic values available for failure rates. In general, the major goal of this study is to solve RAP under uncertainty values for failure rate by implementing robust optimization approach. The general structure if this paper is as following. First of all, a concise and comprehensive literature review is presented for various studies which have been done in last decades. Afterward, an extensive definition is proposed for robustness in RAP and according to this definition, an appropriate mathematical model is developed. Following with these sections, we present two SA and ACO algorithms in sections 5 and 6, respectively. Then, the proposed ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(2), 100-116, 2014

A MODEL BASED QUEUING THEORY TO DETERMINE THE CAPACITY SUPPORT FOR TWIN-FAB OF WAFER FABRICATION Ying-Mei Tua,Chun-Wei Lub Department of Industrial Management Chung Hua University 707, Sec.2, WuFu Rd., Hsinchu, Taiwan 30012, R.O.C. b. Ph.D. Program of Technology Management- Industrial Management Chung Hua University 707, Sec.2, WuFu Rd., Hsinchu, Taiwan 30012, R.O.C. Corresponding author´s e-mail: [email protected] a.

The twin-fab concept has been established over the past decade due to considerations of cheaper facility cost, faster installation and more flexible productivity management. Nevertheless, if lacking in completed backup policies, the benefits of twin-fab will decrease significantly, particularly in production flexibility and effectiveness. In this work, the control policy of capacity support is established and two control thresholds are developed. The first is the threshold of Working in Process (WIP) amount, which acts as a trigger for backup action. The concept of protective capacity is applied to set this threshold. In order to endorse the effectiveness of WIP transfer between twin fabs, the threshold of WIP amount difference (WDTH) is set as a control gate. The design of WDTH is to maximize the expected saved cycle time. The GI/G/m model is applied to develop equations for the calculation of expected saved time. Finally, the capacity support policy is validated by a simulation model. The results show that this policy is both feasible and efficient. Keywords: Twin-fab, Capacity support policy, Protective capacity, Queuing theory

1. INTRODUCTION Compared with other industries, the manufacturing processes of wafer fabrication is more complicated, such as reentrant flows, batch processing, and time constraints (Rulkens et al., 1998; Robinson and Giglio, 1999; Tu et al., 2010). In order to maintain high competitiveness, the capacity expansion and upgrade of advanced technology are necessary. However, managers have to suffer many difficulties in these situations; the market demand changes quickly and equipment costs are more expensive. Given this situation, expanding capacity in dynamic environments is risky ( Chou et al., 2007). Over the past decades, many semiconductor manufacturing companies have adopted the twin-fab concept where two neighboring fabs are installed in the same building and connected to each other through an Automatic Material Handling System (AMHS). The advantages of twin-fab are as follows. 1. Reducing the cost of capacity expansion through sharing essential facilities, such as gas pumps and recycling polluted water systems. 2. Due to the building and basic facilities established in the beginning stage, the construction time of the second fab is reduced. 3. As twin-fab is two neighboring fabs, the real-time capacity backup can be achieved by AMHS.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(3), 117-128, 2014

LOCATION DESIGN FOR EMERGENCY MEDICAL CENTERS BASED ON CATEGORY OF TREATABLE MEDICAL DISEASES AND CENTER CAPABILITY Young Dae Ko1, Byung Duk Song2, James R. Morrison2 and Hark Hwang2† 1 Deloitte Analytics, Deloitte Anjin LLC Deloitte Touche Tohmatsu Limited One IFC, 23, Yoido-dong, Youngdeungpo-gu Seoul 150-945, Korea 2 Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Guseong-dong, Yuseong-gu Daejeon 305-701, Korea † Corresponding author’s e-mail: [email protected]

With the proper location and allocation of emergency medical centers, the mortality rate of emergency patients could be improved by providing the required treatment within an appropriate time. This paper deals with the location design of emergency medical centers in a given region under the closest assignment rule. It is assumed that the capability and capacity to treat various categories of treatable medical diseases are provided for each candidate medical center as a function of possible subsidies provided by the government. It is further assumed that the number of patients occurring at each patient group node during a unit time is known along with the categories of their diseases. Additionally, to emphasize the importance of timely treatment, we use the concept of a survival rate dependent on patient transportation time as well as the category of disease. With the objective of minimizing the total subsidies paid, we select from among the candidate medical centers subject to minimum desired survival rate constraints. Keywords: Emergency Medical Center, Location Design, Closest Assignment Rule, Genetic Algorithm, Simulation, and Survival Rate

1. INTRODUCTION 1.1 Background A medical emergency is an injury or illness that is acute and poses an immediate risk to a person's life or long-term health. For emergencies starting outside of medical care, two key components of providing proper care are to summon the emergency medical services and to arrive at an emergency medical center where the necessary medical care is available. To facilitate this process, each country provides its own national emergency telephone number (e.g., 911 in the USA, 119 in Korea) that connects a caller to the appropriate local emergency service provider. Appropriate transportation, such as an ambulance, will be dispatched to deliver the emergency patient from the site of the medical emergency to an available emergency medical center. In Korea, there are four classes of emergency medical center: regional emergency medical center, specialized care center, local emergency medical center, and local emergency medical facilities. One regional emergency medical center can be assigned to each metropolitan city or province based on the distribution of medical infrastructure, demographics and population. Specialized care centers can be allocated by the Korean Ministry of Health, Welfare and Family Affairs with the special purpose of treating illnesses caused by poison, trauma and burns. According to Act 30 of the Korean Emergency Medical Service Law, one local emergency medical center should be operated per 1 million people in metropolitan cities and major cities. One such center per 0.5 million people is provided in the provinces. The facility to be designated as such a center should be selected from among the general hospitals in a region based on the accessibility to local residents and capability to address the needs of emergency patients with serious medical concerns. To retain the designation as a local emergency medical center, the general hospital should provide more than one specialist in the fields of internal medicine, surgery, pediatrics, obstetrics and gynecology and anesthesiology. Local emergency medical facilities may be appointed from among the local hospitals to support the local emergency medical center and to treat less serious conditions. A flow chart depicting the Korean emergency medical procedure is provided in Figure 1; it is from the National Emergency Medical Center of Korea (National Emergency Medical Center, 2013). Initially, the victim(s) or a first responder calls 119 to request emergency medical service. The Emergency Medical Information Center (EMIC) then dispatches an ambulance to the scene. When an ambulance arrives at the scene, firstly, on-scene treatment is performed by an emergency medical technician (EMT). And then, the patient(s) transport to an emergency medical service (EMS) facility by an ambulance. During transport, information on the patient’s condition may be communicated to the EMIC. ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(3), 129-140, 2014

OPTIMAL JOB SCHEDULING OF A RAIL CRANE IN A RAIL TERMINAL Vu Anh Duy Nguyen and Won Young Yun Department of Industrial Engineering, Pusan National University, 30Jangeon-Dong, Geumjeong-Gu, Busan 609-735, South Korea Corresponding author’s email: [email protected]

This study investigates the job sequencing problem of a rail crane at rail terminals with multiple train lanes. Two kinds of containers are carried between trains and trucks. Inbound containers are loaded onto trains and outbound containers are unloaded from trains. We consider the dual-cycle operation of the crane to load and unload containers between trains and trucks. A branch-and-bound algorithm is used to obtain the optimal solution. A parallel simulated annealing algorithm is also proposed to obtain near optimal solutions to minimize the makespan in job sequencing problems of large size. Numerical examples are studied to evaluate the performance of the proposed algorithm. Finally, three different layouts for rail terminals with different temporary storage areas are considered and their performance of three layouts is compared numerically.

1. INTRODUCTION Rail transportation becomes more important in intermodal freight transportation, to cope with the rapid changes which are taking place in global trade. However, the percentage of goods carried by trains within Europe has dropped to 16.5% in 2009, from 19.7 %, in 2000 (Boysen et al. 2012). Main reasons for this decrease are the difficulties in door-to-door transportation and the enormous initial investments involved in the construction of railroad infrastructure. However, the unit transportation costs decrease as the transportation distance increases. In addition, rail transportation is more environmentally friendly than road transportation. Inbound and outbound containers are loaded and unloaded by rail cranes (RMGC, RTGC), forklifts and reach stackers at rail stations, so that the handling equipment plays an important role of the infrastructure at rail terminals. When the trains arrive at the rail station, outbound containers must first be unloaded from the trains, after which inbound containers that are located in the container yard need to be loaded onto the trains. We consider the job sequencing problem for a rail crane because its performance affects significantly the dwelling duration of trains at rail terminals and the throughput of the terminals. In this paper, we deal with the job sequencing problem associated with a rail crane at rail terminals and want to minimize the makespan for unloading and loading operations. Dual-cycle operation of a crane is defined as follows; 1) picking up an inbound container from a truck, 2) loading it onto one of flat wagons in a train, 3) picking up an outbound container from a train, and 4) loading it onto a truck that moves it to the yard terminal. The operational problems in rail stations including layout design, load planning and rail crane scheduling have been studied in the past. Kozan (1997) considered a heuristic decision rule for the crane split and a dispatching rule to assign trains to rail tracks. Ballis and Golias (2002) considered the optimal design problem of some main design parameters of a rail station, including length and utilization of transshipment tracks, train and truck arrival behavior, type and number of handling equipment, and stacking height in storage areas. Abacoumkin and Ballis(2004) studied a design problem with a number of user-defined parameters and equipment selections. Feo and González-Velarde(1995) proposed a branch and bound algorithm and greedy randomized adaptive search procedure to optimally assign highway trailers to railcar hitches. Bostel and Dejax(1998) studied the process of loading containers onto trains in a rail-rail transshipment shunting yard. They proposed both optimal and heuristic methods to solve it. Corry and Kozan (2006) studied the load planning problem on flat wagons, considering a number of uncertain parameters including dual-cycle operations and mass distribution. Bruns and Knust(2012) studied an optimization problem to assign containers to wagons in order to minimize the set-up and transportation costs along with the aim of maximizing the utilization of the train when a rail terminal is developed. Boysen and Fliedner (2010) determined the disjunctive working area for each rail crane by dynamic programming, although they did not consider the job sequence of the rail cranes. They employed simple workflow measures to separate the crane working areas. Jeong and Kim(2011) dealt with the scheduling problem of a rail crane and parking position problem of trucks in rail stations located at seaport container terminals. In their scheduling problem, a single crane covers each train and moves in one direction along the train. Pap et al. (2012) developed a branch and bound algorithm to determine optimally the crane scheduling arrangement. They focused on the operation of a single crane, which is used to transfer containers directly between the container yard and the train. (Guo et al. 2013) dealt with a scheduling problem of loading and unloading containers between a train and yards. They assumed that multiple gantry cranes are used, safety distance is required and cranes cannot cross other cranes. However, the article assumed one dimension travel (gantry travel) of the cranes and did not consider the dual-cycle operation and the re-handle issues of transferring containers. ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(3), 141-152, 2014

BAYESIAN NETWORK LEARNING FOR PORT-LOGISTICS-PROCESS KNOWLEDGE DISCOVERY Riska Asriana Sutrisnowati1, Hyerim Bae1 and Jaehun Park2 1 Pusan National University, Korea Republic of, 2 Worcester Polytechnic Institute, United States

A Bayesian network is a powerful tool for various analyses (e.g. inference analysis, sensitivity analysis, evidence propagation, etc.); however, it is first necessary to obtain the Bayesian network structure of a given dataset, and this, an NP-hard problem, is not an easy task. However, an enhancement approach has been followed in order to learn Bayesian network from event logs. In the present study, a genetic-algorithm-based method for generation of a Bayesian network is developed and compared with a dynamic programming method. We herein also present the useful knowledge found using our inference method. Keywords: Bayesian network learning, mutual information, event logs

1

INTRODUCTION

Currently many businesses are supported by information systems that provide insight into what actually happens in business process execution. This abundant data has been studied mainly in the growing research area of process mining (Weijters et al., 2006; Goedertier et al., 2007; Gunther and van der Aalst, 2007; Song et al., 2009; van der Aalst, 2011; De Weerdt et al., 2012;). There are four perspectives on process mining (van der Aalst, 2011): control flow, organizational flow, time, and data. Current process mining techniques for the most part can accommodate only one of these. A Bayesian network, however, can handle two perspectives at once (e.g. control flow and data). In our previous work (Sutrisnowati et al., 2012), we used a dependency graph, retrieved by Heuristic Miner (Weijters et al., 2006), and decomposed any cycles found into a non-cycle structure. This methodology, though enabling quick retrieval of the constructed Bayesian network, has drawbacks relating to the fact that its non-cycle structure is dependent solely on the structure of the dependency graph. In other words, we have to take note of the fact that the structure is supported only by the successive occurrences between activities and not by the common information shared. To remedy this shortcoming, we have developed a dynamic programming procedure (Sutrisnowati et al, 2013) of mutual information score using Mutual Information Test (MIT) (De Campos, 2006). The data used to calculate MIT score was originally not in a form of event logs, and, indeed, MIT was not designed for the business process management field. Therefore, the formula was modified to accommodate the problem at hand. However, the dynamic programming, while capable of delivering the optimal score, still lacks in performance. Therefore, genetic algorithms along with a comparison of dynamic programming are also presented in this paper. This paper is organized as follows: section 2 discusses the background; sections 3 and 4 introduce the proposed method and a case study from a real-world example, respectively; section 5 offers a discussion, and finally, section 6concludes our work.

2

BACKGROUND

2. 1 Process Structure The dataset used in the present study was in the form of an event log, denoted L. According to Van der Aalst (2011)’s proposed hierarchical structure of process execution event logs, a process consists of cases, denoted c, and each case consists of events, denoted e, such that an event is always related to one case. For instance, suppose a tuple  A, B, C , D  and  A, C , B, D  , which represents an event-log case in which an event A is followed by an event B and then an event C and, eventually, an event D. Since a case c in the event logs contains a sequential process execution, we can assume that the data in the event logs is ordered. For convenience, we assume that each event in the event log is represented by one random variable X , so that X A represents a random variable of an event A. Pa ( X i ) and Pa( X i ) denote a set of candidate parent(s) and actual parent(s) of an event in the event logs, respectively. We can say that Pa( X i )  Pa( X i ) always holds, due to the fact that a candidate parent that makes no higher contribution in the iterative calculation of MI L ( X i , Pa( X i )) cannot be considered as the actual parent. For example, an event A has an empty candidate parent, since event A is the start event, denoted Pa( X A )  {} , ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(3), 153-167, 2014

A HYBRID ELECTROMAGNETISM-LIKE ALGORITHM FOR A MIXED-MODEL ASSEMBLY LINE SEQUENCING PROBLEM Hong-Sen Yan, Tian-Hua Jiang, and Fu-Li Xiong MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering, and School of Automation, Southeast University, Nanjing, China Corresponding author’s e-mail: {Hong-Sen Yan, [email protected]}

With the growth in customer demand diversification, research on mixed-model assembly lines have been given increasing attention in the field of management. Sequencing decisions are crucial for managing mixed-model assembly lines. To improve production efficiency, the product sequencing problem with skip utility work strategy and sequence-dependent setup times is focused on in this study, and its mathematical model is established, whereby the idle cost, the utility cost and the setup cost are to be optimized simultaneously. A necessary condition for skip policy of the system is set, and a lower bound of utility work cost is given and theoretically proved. Strong NP-hardness of the problem is confirmed. Addressing the main features of the problem, a hybrid EMVNS (electromagnetism-like mechanism-variable neighborhood search) algorithm is developed. To enhance the local search ability of EM, a VNS algorithm is employed and five neighborhood structures are designed. With the aid of the VNS algorithm, the fine neighbour search of the optimum individual is made available, thus improving the solution to a certain extent. Simulation results demonstrate that the algorithm is feasible and valid. Significance: This paper presents a hybrid EMVNS algorithm to solve the product sequencing problem of a mixed-model assembly line with skip utility work strategy and sequence-dependent setup times. The simulation results demonstrate that the proposed method is feasible and valid. Keywords: Scheduling, Mixed-model assembly line sequencing, Skip utility work strategy, Sequence-dependent setup times, Hybrid EMVNS algorithm

1. INTRODUCTION To cope with diversification of customers demand, mixed-model assembly lines have gained increasing importance in the field of management. A mixed model assembly line (MMAL) is a type of production line where a variety of product models similar in product characteristics are assembled. Two important decisions for managing mixed-model assembly lines are balancing and sequencing. Sequencing is a problem of determining a sequence of the product models, whereby a major emphasis is placed on maximizing the line utilization. In MMAL, products are transported on the conveyor belt and operators move along with the belt while working on a product. An operator can work on a product only when it is within his work zone limited by upstream and downstream boundaries. Whenever multiple labor-intensive models, e.g., all having an elaborate option, follow each other in direct succession at a specific station, a work overload situation occurs, which means that the operator cannot finish work on a product before it leaves his station. Many outstanding results have been achieved in this field. Okamura and Yamashina (1979) developed a sequencing method for mixed-model assembly lines to minimize line stoppage. Yano and Rachamadugu (1991) addressed the problem of sequencing mixed-model assembly lines to minimize work overload. Miltenburg and Goldstein (1991) developed heuristic approaches to smooth production times by minimizing loading variation. Kim and Cho (2003) studied the sequencing problem in a mixed-model final assembly line with multiple objectives by using simulated annealing algorithm. Zhao and Ohno (1994, 1997) proposed a branch-and-bound method for finding an optimal or sub-optimal sequence of mixed models that minimizes the total conveyor stoppage time. Chutima et al. (2003) applied fuzzy genetic algorithm to the sequencing problem of mixed-model assembly line with processing time. Simaria and Vilarinho (2004) presented an iterative genetic algorithm-based procedure for the mixed-model assembly line balancing problem with parallel workstations to maximize the production rate of the line for a pre-determined number of operators. Akpinar and Baykasoğlu (2014) proposed a multiple colony hybrid bee algorithm to solve the mixed-model assembly line balancing problem with setups. To simultaneously optimize the idle and overload costs, Sarker and Pan (1998) studied MMAL design problem in the cases of closed and opened workstation. Yan et al. (2003) presented three heuristic methods combining tabu search with quick schedule simulation for optimizing the integrated production planning and scheduling problem on automobile assembly lines to minimize the idle and setup cost. Moghaddam and Vahed (2006) addressed a multi-objective mixed assembly line sequencing problem to optimize the costs of utility work, productivity and setup simultaneously. Tsai (1995) studied a class of assembly line sequencing problem to minimize the utility work and the risk of line stop simultaneously. Fattahi and Salehi (2009) addressed a mixed-model assembly line sequencing optimization problem with variable production cycle time to minimize the idle time and utility work costs. Bard et al. (1994) developed a mathematical model that involved two objective functions in the mixed model assembly line sequencing (MMALS): minimizing the overall line length and keeping a constant rate of part usage. They combined the two objectives using a weighted sum and suggested a tabu search algorithm. Mohammadi and Ozbayrak (2006) ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(3), 168-178, 2014

A VARIANT PERSPECTIVE TO PERFORMANCE APPRAISAL SYSTEM: FUZZY C – MEANS ALGORITHM Coskun Ozkana, Gulsen Aydin Keskinb,*, Sevinc Ilhan Omurcac [email protected], [email protected], [email protected] a Yıldız Technical University, Mechanical Engineering Faculty, Industrial Engineering Department, Istanbul – Turkey, Tel: +90 212 383 2865, Fax: +90 212 383 2866 b Kocaeli University, Engineering Faculty, Industrial Engineering Department, Umuttepe Campus, Kocaeli – Turkey c Kocaeli University, Engineering Faculty, Computer Engineering Department, Umuttepe Campus, Kocaeli – Turkey

Performance appraisal and evaluating the employees for awarding is an important issue in human resource management. In performance appraisal systems, ranking scales and 360 degree are the most commonly used types of evaluating methods in which the evaluator gives a score for each criterion to assess all employees. Ranking scales are relatively simple assessment methods. Despite using ranking scales allows the management to complete the evaluation process in a short time, they have some disadvantages. In addition, although, all the performance appraisal methods evaluated the employees in different ways, the employees get scores for each evaluation criteria and then their performances are evaluated according to total scores. In this paper, the fuzzy c – means (FCM) clustering algorithm is applied as a new method to overcome the common disadvantages of the classical appraisal methods and help managers to make better decisions in a fuzzy environment. FCM algorithm not only selects the most appropriate employee(s), but also clusters them with respect to the evaluation criteria. To explain the FCM method clearly, a performance appraisal problem is discussed and employees are clustered both by the proposed method and the conventional method. Finally, the results obtained by the current system and FCM have been presented comparatively. This comparison concludes that, in performance appraisal systems, FCM is more flexible and satisfactory compared to conventional method. Key words: Performance appraisal, fuzzy c – means algorithm, fuzzy clustering, multi criteria decision making, intelligent analysis.

1. INTRODUCTION Employee performances such as capability, knowledge, skill, and other abilities are significantly important for the organizations (Gungor et al., 2009). Hence, accurate personnel evaluation has a significant role in the success of an organization. Evaluation techniques that allow companies to identify the best employee from the personnel are the key components of human resource management (Sanyal and Guvenli, 2004). However, this process is so complicated due to human nature. The objective of an evaluation process depends on appraising the differences between employees, and estimating their future performances. The main goal of a manager is to attain ranked employees who have been evaluated with regard to some criteria. Therefore, the development of efficient performance appraisal methods has become a main issue. Some authors define the performance appraisal problem as an unstructured decision problem, that is, no processes or rules have been defined for making decisions (Canos and Liern, 2008). Previous researches have shown that performance appraisal information is used especially in making decisions requiring interpersonal comparisons (salary determination, promotion, etc.), decisions requiring personal comparison (feedback, personal educational need, etc.), decisions orientated to the continuation of the system (target determination, human force planning, etc.) and documentation. It is clear that in a conventional way, there are methods and tools to do those tasks (Gürbüz and Albayrak, 2014); however, each traditional method has certain drawbacks. In this paper, fuzzy c – means (FCM) clustering algorithm is proposed to make a more efficient performance evaluation by removing these drawbacks. The proposed method enables the managers group their employees with respect to several criteria. Thus, managers can determine the most appropriate employee(s), in case of promotion, salary determination, and so on. In addition, in case of personal educational requirement, they will know which employee(s) needs training by the proposed method. This paper proposes an alternative suggestion to performance appraisal system. After a brief review of performance appraisal in Section 2, FCM algorithm is described in Section 3. A real-life problem is solved both by FCM and the conventional method to evaluate their performances and the findings are discussed in Section 4. Finally, this paper concludes with a discussion and a conclusion.

ISSN 1943-670X

©INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(4), 179-189 , 2014

AN EARLY WARNING MODEL FOR THE RISK MANAGEMENT OF GLOBAL LOGISTICS SYSTEMS BASED ON PRINCIPAL COMPONENT REGRESSION Jean Betancourt Herrera1, Yang-Byung Park2 Department of Industrial and Management Systems Engineering College of Engineering, Kyung Hee University 1 Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do 446-701, Republic of Korea 1 [email protected], [email protected] (corresponding author)

This paper proposes an early warning model for the risk management of global logistics systems based on principal component regression (PCR) that predicts a country’s global logistics system risk, identifies risk sources with probabilities, and suggests ways of risk mitigation. Various quantitative and qualitative global logistics indicators are utilized for monitoring the global logistics system. The Enabling Trade Index is used to represent the risk level of a country’s global logistics system. Principal component analysis is applied to identify a small set of global logistics indicators that account for a large portion of the total variance in the original set. An empirical study is carried out to validate the predictive ability of PCR using datasets of years 2010 and 2012 published by the World Economic Forum. Furthermore, the superiority of PCR is evaluated by comparing its performance with that of a neural network with respect to the correlation coefficient and coincident rate. Finally, a real-life example of the South Korean global logistics system is presented. Keywords: early warning model, global logistics system, risk management, principal component regression, neural network.

1. INTRODUCTION Global logistics is a collection of moving and storage activities required for trade between countries. In general, global logistics is much more complicated and difficult to perform than domestic logistics because the goods flow over borders and thus take a long time to transport. Complex administrative processes are involved, and more than one mode of transportation is required (Shamsuzzoha and Helo, 2012). The components of a typical global logistics system of a country are tariff, customs, documentations, transport infrastructure and services, information and communication services, regulations, and security (Gourdin, 2006). As global trade continues to expand, the sustainable global logistics system of a country plays a crucial role in achieving global competiveness by shortening the logistics process time, reducing the logistics cost, and securing interoperability between different logistics sectors (Yahya et al., 2013). The establishment of the sustainable global logistics system requires a big investment for a government and takes a period of multiple years. If a country cannot provide traders with a satisfactory global logistics system, it will lose valuable customers and experience a significant drop in trade. Therefore, it is very important for a country to predict its global logistics system risk in advance, identify risk sources where improvements are most needed, and investigate effective ways for risk mitigation. An early warning system is responsible for monitoring the system conditions and determining the issue of a warning signal in advance through the analysis of various system indicators. Thus, an early warning system is an effective tool for the operation of a sustainable global logistics system for a country. An early warning system may contribute to providing relevant government ministries with strong evidence for improving certain areas of the global logistics system, especially when allocating limited resources or establishing various global logistics policies. A few researchers have studied the development of risk early warning system. Fordyce et al. (1992) proposed a method for monitoring the manufacturing flow of semi-conductor facilities in a logistics management system. Xie et al. (2009) developed an early warning and control management process for inner logistics risk in small manufacturing enterprises based on label-card system equipped with RFID, through which an enterprise can monitor the quantity and quality of work in process in a dynamic manner. Xu et al. (2010) presented the early warning model for food supply chain risk based on principal component analysis and logistics regression. Li et al. (2010) presented a novel framework for early warning and proactive control systems in food supply chain networks that combine expert knowledge and data mining methods. Feng et al. (2008) proposed a simple early warning model with thresholds for four indicators as a subsystem of the decision support system for price risk management of the vegetable supply chain in China. Xia and Chen (2011) proposed a decision-making model for optimal selection of risk management methods and tools based on ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(4), 190-208, 2014

AGILE AND FLEXIBLE SUPPY CHAIN NETWORK DESIGN UNDER UNCERTAINITY Morteza Abbasi, Reza Hosnavi, Reza Babazadeh Department of Management and Sot Technologies, Malek Ashtar University of Technology, P.O. Box 1774/15875, Tehran, Iran

Agile supply chain has proved its efficiency and capability in dealing with the disturbances and turbulences of today’s competitive markets. This paper copes with the strategic and tactical level decisions in agile supply chain network design (SCND) under interval data uncertainty. In this study, an efficient mixed integer linear programming (MILP) model is developed that is able to consider the key characteristics of agile supply chain such as direct shipments, outsourcing, different transportation modes, discount, alliance (process and information integration) among opened facilities and maximum waiting time of customers for deliveries. In addition, in the proposed model capacity of facilities is determined as decision variables which are often assumed to be as an input parameter. Then, the robust counterpart of the presented model according to the recent advances in robust optimization theory is developed to deal with the inherent uncertainty of input parameters. Computational results illustrate that the proposed robust optimization model has high degree of responsiveness in dealing with uncertainty compared with deterministic model. Therefore, the robust model can be applied as a power tool in agile and flexible SCND which faces with different risks in competitive environments. Keywords: Robust optimization, Agile supply chain network design, Flexibility, Outsourcing, Responsiveness.

1.INTRODUCTION Today’s, high fluctuations and disturbances in business environments have caused the supply chains to seek an effective way to deal with the undesirable uncertainties which affect the overall supply chain performance. Supply chain network design (SCND) decisions, as the most important strategic level decisions in supply chain management, concerned with complex interrelationships between various tiers, such as suppliers, plants, distribution centers and customer zones as well as determining the number, location and capacity of facilities to meet customer needs, effectively. Supply chain management integrates interrelationships between various entities through creating alliance, i.e. information-system integration and process integration, between entities to improve response to customers in various aspects such as, higher product variety and quality, lower costs and quick responses. Typically, risks in SCND are classified in two categories: operational or internal risk factors and disruption or external risk factors. Operational risks is related to those risks which occur because of internal factors in supply chain because of improper coordination between entities in various tiers, such as, production risk, distribution risk, supply risk and demand risk. In contrast, disruption risks are resulted because of external risk factors which occur due to interaction between supply chain and environment, such a natural disasters, exchange rate fluctuations and terrorist attacks (Singh et al., 2011). Increasing utilization of outsourcing approach through sub-contracting some of customer demands as well as reduction in life cycle of products due to enthusiasm of customers to welcome fashion goods rather than commodities has increased the uncertainties in competitive environments. Therefore, the supply chain network (SCN) should be designed in the way that could sustain in dealing with such uncertainties. Chopra and Sodhi (2004) mentioned that the organizations should consider uncertainty issue with its various forms in planning and supply chain management to deal with their destructive and burdensome effects on supply chain network. One of the vital challenges for organizations in today’s turbulent markets is the need to respond to customer needs with different volumes and vast variety quickly and efficiently (Amir, 2011). Agility with its various contexts is the most popular approach that enables organizations to face with unstable and high volatile customer demands. The most important concepts of agility are described in the next section. The point that should be mentioned here is that the agility concepts should be applied in upstream and downstream relationships of the supply chain management involving supplier selection, logistics, information system and etc. Since the SCND is the most important strategic level decision which affects the overall performance of supply chain, it is necessary to consider agility concepts such as response to customers in maximal allowable time, direct shipment, alliance (i.e., information and process integration) between entities in different echelons, discount to achieve competitive supply chain, outsourcing and using different transportation modes to achieve flexibility as well as safety stock to improve responsiveness. It is evident that considering agility concepts in SCND plays incredible role in agility of the overall supply chain. As yet many researchers have tried to show the most important factors in agile supply chain management conceptually and this context has omitted in mathematical modeling area especially in supply chain network design area.

ISSN 1943-670X

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International Journal of Industrial Engineering, 21(4), 209-230, 2014  

SIMULATION OPTIMIZATION OF FACILITY LAYOUT DESIGN PROBLEM WITH SAFETY AND ERGONOMICS FACTORS 1

Ali Azadeh1, Bita Moradi Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran Corresponding author e-mail address: [email protected]

This paper presents an integrated fuzzy simulation-fuzzy data envelopment analysis (FDEA)-fuzzy analytic hierarchy process (FAHP) algorithm for optimization of flow shop facility layout design (FSFLD) problem with safety and ergonomics factors. Almost all FSFLD problems are solved and optimized without safety and ergonomics factors. At first, safety and ergonomics factors are retrieved from a standard questionnaire. Then, feasible layout alternatives are generated by a software package. Third, FAHP is used for weighting non-crisp ergonomics and safety factors in addition to maintainability, accessibility and flexibility (or qualitative) indicators. Fuzzy simulation is used consequently to incorporate the ambiguity associated with processing times in the flow shop by considering all generated layout alternatives with uncertain inputs. The outputs of fuzzy simulation or non-crisp operational indicators are average waiting time in queue, average time in system and average machine utilization. Finally, FDEA is used for finding the optimum layout alternatives with respect to ergonomics, safety, operational, qualitative and dependent indicators (distance, adjacency and shape ratio). The integrated algorithm provides a comprehensive analysis on the FSFLD problems with safety and ergonomics issues. The results have been verified and validated by DEA, principal component analysis and numerical taxonomy. The unique features of this study are the ability of dealing with multiple non-crisp inputs and outputs including ergonomics and safety factors. It also uses fuzzy mathematical programming for optimum layout alternatives by considering safety and ergonomics factors as well as other standard indicators. Moreover, it is a practical tool and may be applied in real cases by considering safety and ergonomics issues within FSFLD problems. Keywords: Simulation Optimization; Flow Shop Facility Layout Design; Fuzzy DEA; Safety; Ergonomics Motivation and Significance: Almost all FSFLD problems are solved and optimized without safety and ergonomics factors. Moreover, standard factors related to operational and layout dependent issues are only considered in such problems. There are usually missing data, incomplete data or lack of data with respect to FSFLD problems in general and safety and ergonomics issues in particular. This means data could not be collected and analyzed by deterministic or stochastic models and new approaches for tackling such problems are required. This gap motivated the authors to develop a unique simulation optimization algorithm to handle such gaps in FSFLD problems. The integrated fuzzy simulation-fuzzy DEA algorithm-fuzzy AHP presents exact solution to the FSFLD problems with safety and ergonomics issues whereas previous studies present incomplete and non exact alternatives. Also, it provides a comprehensive analysis on the FSFLD problems with uncertainty by incorporating non-crisp ergonomics and safety indicators in addition to fuzzy operational, dependent and qualitative indicators. Moreover, it provides complete and exact rankings of the plant layout alternatives with uncertain and fuzzy inputs. The superiority and effectiveness of the proposed integrated algorithm is compared with previous DEA-Simulation-AHP, AHP-DEA, AHP-principal component analysis (PCA), and numerical taxonomy (NT) methodologies through a case study. The unique features of the proposed integrated algorithm are the ability of dealing with multiple fuzzy inputs and outputs (ergonomics and safety in addition to operational, qualitative and dependent). It also optimizes layout alternatives through fuzzy DEA. Third it is a practical approach due to considerations of ergonomics, safety, operational and dependent aspects of the manufacturing process within FSFLD problems.

1. INTRODUCTION Facility Layout design (FLD) is a critical issue in productivity and profitability through redesigning, expanding, or designing the manufacturing systems, e.g. flow shop systems (FSFLD). Zhenyuan, et al. (2013) showed that the designed lean facility layout system can increase the productivity efficiency. Also, Niels Henrik Mortensen, et al.

                                                                                                                          ISSN 1943-670X

 

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International Journal of Industrial Engineering, 21(4), 231-242, 2014

A CONCURRENT APPROACH FOR FACILITY LAYOUT AND AMHS DESIGN IN SEMICONDUCTOR MANUFACTURING Dongphyo Hong1, Yoonho Seo1*, Yujie Xiao2 School of Industrial Management Engineering, Korea University, Seoul, Korea 2 Department of Logistic Management, School of Marketing & Logistic Management, Nanjing University of Finance & Economics, Nanjing, People's Republic of China *Corresponding author: [email protected] 1

This paper presents a concurrent approach to solve the design problem of facility layout and automated material handling system (AMHS) for semiconductor fabs. The layout is composed of bays which are unequal-area blocks with equal height but flexible width. In particular, the bay width and locations of a shortcut, bays, and their stockers, which are major fab design considerations, are concurrently determined in this problem. We developed a mixed integer programming (MIP) model for this problem to minimize the total travel distance (TTD) based on unidirectional interbay flow and a bidirectional shortcut. To solve large-sized problems, we developed a five-step heuristic algorithm to exploit and explore the solution space based on the MIP model. The computational results show that the proposed algorithm is able to find optimal solutions of small-sized problems and to solve large-sized problems within acceptable time. Keywords: Facility Layout, Bay Layout, AMHS Design, Concurrent Approach, Semiconductor Manufacturing

1. INTRODUCTION In a 300 mm wafer fabrication facility (fab), a wafer typically travels about 13–17 km and visits 250 process equipment during the processing (Agrawal and Heragu, 2006). An effective facility layout and material handling system design can significantly reduce the total travel distance of wafers. As stated by Tompkins et al. (2010), 20–50% of the total operating expenses within manufacturing are attributed to material handling. An efficient design of facility layout and material handling can reduce operational cost by at least 10–30%. Therefore, two challenges are presented to a fab designer: (1) facility layout; (2) automated material handling system (AMHS) design (Montoya-Torres, 2006). This paper focuses on the fab design comprising a bay layout and AMHS design with a spine configuration, which usually has a unidirectional flow and bidirectional shortcuts, as presented by Peters and Yang (1997). Here, each bay is composed of equipment that performs similar processes and forms a rectangular shape. However, they approached the two sub-problems in a sequential manner, which may result in a local optimal solution. In this study, a concurrent approach is proposed to find optimal solution of the two sub-problems simultaneously as shown in Figure 1.

Figure 1. Layout example using a shortcut

Figure 2. Representation of the problem

The facility layout problem (FLP) is to determine the physical placement of departments within the facility (Kusiak and Heragu 1987). In semiconductor manufacturing, the layout design usually has a bay structure with a spine configuration to enhance the utilization of process equipments and frequent maintenance (Agrawal and Heragu, 2006). Peters and Yang (1997) suggested a methodology for an integrated layout and AMHS design which enables spine and perimeter configurations in a semiconductor fab. Azadeh and Izadbakhsh (2008) presented an analytic hierarchy process and principal component analysis to solve the FLP. Ho and Liao (2011) proposed a two-row dual-loop bay layout. They ISSN 1943-670X

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International Journal of Industrial Engineering, 21(5), 243-252, 2014

 

ASSISTING WHEELCHAIR USERS ON BUS RAMPS: A POTENTIAL CAUSE OF LOW BACK INJURY AMONG BUS DRIVERS Piyush Bareria1, Gwanseob Shin2 1

Department of Industrial and Systems Engineering State University of New York at Buffalo Buffalo, New York, USA Corresponding author’s e-mail: [email protected] 2

School of Design and Human Engineering Ulsan National Institute of Science and Technology Ulsan, Korea Manual assistance to wheelchair-users while boarding and disembarking a bus may be an important risk factor for musculoskeletal disorders of bus drivers, but no study has yet assessed biomechanical loads associated with the manual assist operations. In this study, off-duty bus drivers simulated wheelchair-user assisting operations using forward and backward strategies for boarding and disembarking ramps. Low-back compression and shear forces, shoulder moments and percent population capable of generating required shoulder moment were estimated using the University of Michigan Three-Dimensional Static Strength Prediction Program. L4-L5 compression force ranged from 401.6 N for forward boarding to 2169.3 N for backward boarding (pulling), and from 2052.4 N for forward disembarking to 434.2 N for backward disembarking (pushing). The shoulder moments were also consistently higher for the pushing tasks. It is recommended that bus drivers adopt backward boarding and forward disembarking strategies to reduce the biomechanical loads on the low back and shoulder. Keywords: musculoskeletal injury, bus driver, wheelchair pushing/pulling, bus access ramp (Received on September 9, 2012; Accepted on September 15, 2014) 1. INTRODUCTION Bureau of Labor Statistics data (BLS, 2009) indicate that among bus drivers (transit and intercity), back injuries and disorders constitute about 25% of reported cases of nonfatal work-related injuries and illnesses resulting in days away from work. Data from the same year reports a work-related nonfatal back injury/illness incidence rate (IR) of 12.3 per 10,000 full time bus drivers, which was greater than that of construction laborers (IR = 10.6). A number of studies have also evaluated the prevalence of work-related musculoskeletal disorders in the upper body quadrant (neck, upper back, shoulder, elbow, wrist, etc.) in drivers of different types of vehicles (Greiner & Krause, 2006; Langballe, Innstrand, Hagtvet, Falkum, & Aasland, 2009; Rugulies & Krause, 2008). The prevention of musculoskeletal injuries of bus drivers and associated disability has become a major challenge for employers, insurance carriers, and occupational health specialists. Physical risk factors that have been associated with the high prevalence of work-related musculoskeletal disorders of drivers include frequent materials handling activities as well as prolonged sitting and exposures to whole body vibration (WBV) (Magnusson, Pope, Wilder, & Areskoug, 1996; Szeto & Lam, 2007). Specifically, bus drivers in public transportation may also be exposed to the risks of heavy physical activities from manual assisting of wheelchair users. Bus drivers of public transit system are mandated by law to assist a person in wheelchair to board and disembark buses if needed. Sub-section 161(a) of the Code for Federal Regulation on Transportation services for individuals with disability (49 CFR 37, U.S.) requires “public and private entities providing transportation services maintain in operative condition those features of facilities and vehicles that are required to make the vehicles and facilities readily accessible to and usable by individuals with disabilities”. In addition, 49 CFR 37 sub-section 165 (f) states that “where necessary or upon request, the entity's personnel shall assist individuals with disabilities with the use of securement systems, ramps and lifts. If it is necessary for the personnel to leave their seats to provide this assistance, they shall do so.” With an estimated 1.6 million non-institutionalized wheelchair users in U.S. of which about 90% are hand-rim propelled or so-called manual wheelchairs (Kaye, Kang, & LaPlante, 2005), bus drivers are likely to assist wheelchair users during their daily shift which could involve manual lifting, pushing and/or pulling the occupied wheelchair. Pushing a wheelchair could cause overexertion and lead to injury since even ramps that comply with the Americans with Disabilities Act (ADA) standards can be difficult to climb for wheelchair pushers of any strength (Kordosky, Perkins, ISSN 1943-670X

 

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International Journal of Industrial Engineering, 21(5), 253-270, 2014

OPEN INNOVATION STRATEGIES OF SMARTPHONE MANUFACTURERS: EXTERNAL RESOURCES AND NETWORK POSITIONS Jiwon Paik1, Hyun Joon Chang2 1,2

Graduate School of Innovation and Technology Management Korea Advanced Institute of Science and Technology Daejeon 305-701, South Korea Corresponding author’s e-mail: [email protected]

A smartphone is not only a product made up of various integrated components, but also a value-added service. As the smartphone ecosystem has evolved within the value chain of the ICT industry, smartphone manufacturers can benefit from open innovation, such as by making use of external resources and collaboration networks. However, most studies on smartphones have focused on aspects of product innovation, such as functional differentiation, usability, and market penetration rather than on innovation networks. The aim of this study is to examine how the open innovation approaches and strategic fit of smartphone manufacturers function in delivering innovation outcomes and business performance. This research examines the relationship between seven smartphone manufacturers and their collaboration partners during a recent three-year period, by analyzing four specific areas: hardware components, software, content services, and telecommunications. Keywords: smartphone, open innovation, external resources, network positions (Received on September 7, 2012; Accepted on August 7, 2014) 1. INTRODUCTION Information and communications technology (ICT) firms are now experiencing a new competitive landscape that is redefining and eroding the boundaries between software, hardware, and services. In 2000, the first device marketed as a ‘smartphone’ was released by Ericsson; it was the first to use an open operating system and to combine the functions of a mobile phone and a personal digital assistant (PDA). Then in 2007, the advent of the iPhone redefined the smartphone product category, with the convergence of traditional mobile telephony, Internet services, and personal computing representing a paradigm shift for this emerging industry (Kenney and Pon 2011). Smartphones are becoming increasingly popular: smartphone sales to end users accounted for 19 percent of total mobile communications device sales in 2010, a 72.1 percent increase over 2009. In comparison, worldwide mobile device sales to end users increased by 31.8 percent during the same perioda The smartphone industry is undergoing rapid and seismic change. Within two years, the iPhone went from nothing to supplying 30% of Apple's total revenue. Indeed, the iPhone has been the best performer in terms of global sales, capturing more than 14% of the market in 2009; whereas Nokia, once the smartphone industry leader, has seen its market share fall dramatically. Stephen Elop, the former chief executive officer of Nokia, expressed a sense of crisis in February 2011: “We are standing on a burning platform.” Figure 1 shows the global market share of eight smartphone manufacturers, and provides an indication of the fierce competition in this industry. During the remarkable flourishing of the smartphone industry, most theoretical analysis has strongly emphasized either the product or the service aspects of smartphones, such as their usability, diffusion, software development, and service provision (Funk 2006; Kenney and Pon 2011; Eisenmann et al. 2011; Doganova and Renault 2011). In contrast, the competitive management aspects, such as integration or collaboration, have been relatively neglected. The purpose of this paper is to analyze the open innovation strategy of smartphone manufacturers who have experienced sudden performance changes; examples of such open innovation strategies include managing complementary assets and integrating or collaborating with other companies. This paper examines the impact of utilizing external resources on the innovation output, performance, and network position of smartphone manufacturers; and also formulates and tests several hypotheses, by means of theoretical analyses and empirical research. This paper is organized as follows: the next section provides an overview of the relevant literature, and the hypotheses are defined in accordance with the theoretical analysis; in the third section, the dataset and methodology are explained; the fourth a

Gartner press releases, 2011. Gartner Says Worldwide Mobile Device Sales to End Users Reached 1.6 Billion Units in 2010; Smartphone Sales Grew 72 Percent in 2010

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International Journal of Industrial Engineering, 21(5), 271-283 2014

 

ENHANCING PERFORMANCE OF HEALTHCARE FACILITY VIA NOVEL SIMULATION METAMODELING BASED DECISION SUPPORT FRAMEWORK Farrukh Rasheed1, Young Hoon Lee2 1 2

, Department of Information and Industrial Engineering Yonsei University College of Engineering 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea. Corresponding author’s e-mail: [email protected] A simulation model of patient throughput in the community healthcare center (CHC) located in Seoul, Korea is developed. The aforementioned CHC is providing primary, secondary and tertiary healthcare (HC) services, i.e. diagnostic, illness, treatment, health screening, immunization, family planning, ambulatory care, pediatric and gynecologic along with various other support services to uninsured, under-insured and low income patients residing in the nearby medically underserved areas. The prime aim of this investigation is to identify main imperative variables via statistical analysis of de-identified customer tracking system dataset and based-on expert opinion. Afterwards, using proposed novel simulation metamodeling based decision support framework to gauge their impact on performance measures of interest. The identified independent variables are resource shortage and stochastic demand pattern while performance measures of interest are the average length of stay (LOSa), balking probability (Pb), reneging probability (Pr), overcrowding and resource utilization. Significance: The methodology presented in this research is unique in a sense: a single meta-model represents a single performance measure and the solution found may be sub-optimal, having a detrimental effect on other crucial performance measures of interest if not considered. Hence, it is emphasized to develop all possible meta-models representing all the crucial performance measures individually for the purpose of overcoming aforesaid draw back so that final solution may qualify itself as a real-optimal solution. Keywords: simulation, regression, performance analysis, healthcare system and application, decision making. (Received on December 18, 2012; Accepted on September 15, 2014) 1. INTRODUCTION Today's highly competitive HC sector must be able to adjust as per customers' ever changing requirements to survive. Specific HC installation as considered for this research is a CHC located in Seoul, Korea serving medically underserved areas. A HC facility can only survive by delivering high quality service at reduced cost while promptly responding to associated challenges: swift changes in technology, patient load fluctuations, longer patient LOS, sub-optimal resource utilization, unnecessary inter-process delays, inefficient information access and control, compromised patient safety, overcrowding, surge, emergency department (ED) use and misuse and medication errors (Erik. et al. (2010), Mare et al. (1995), Nan et al. (2009), Nathan and Dominik (2009)). Foregoing in view, the CHC administration was frantically looking for ways to improve service quality because if systems under investigation are multifaceted as in numerous practical situations, mathematical solutions become impractical and simulation is used as a contrivance for system evaluation. Simulation represents transportation, manufacturing and service systems in a computer program for performing experiments which enables testing of design changes without disruption to the system being modelled i.e. representation mimics system’s pertinent outward characteristics (Wang et al. (2009)). Many HC experts have used simulation for the analysis of different situations aiming at better service quality and improved performance. Hoot et al. (2007, 2008, 2009) used real-time simulation to forecast crowding in an ED. Kattan and Maragoud (2008) uses simulation to address problems of an ambulatory care unit in a large cancer center, where operations and resource utilization challenges led to overcrowding, excessive delays, and concerns regarding safety of critical patients. Santibanez et al. (2009) analyzes the impact of operations, scheduling and resource allocation on patient waiting time, clinic over-time and resource utilization using simulation. Zhu et al. (2009) analyzes appointment scheduling systems in specialist outpatient clinics to determine the optimal number of appointments to be planned under different performance indicators and consult room configurations using simulation. Wang et al. (2009) modelled ED services using ARIS / ARENA software. Su et al. (2010) used simulation to improve the hospital registration process by re-engineering actual process. Blasak et al. (2003) used simulation to evaluate hospital operations between emergency department (ED) and medical treatment unit to suggest improvements. Samaha et al. (2003) proposed a framework to reduce patient LOS using simulation. Holm and Dahl (2009) used simulation to analyze the effect of replacing nurse triage with physician triage. Reindl et al. (2009) used simulation to analyze and suggest improvements for the cataract surgery process. ISSN 1943-670X

 

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International Journal of Industrial Engineering, 21(5) ,284-294, 2014

 

ECONOMIC-STATISTICAL DESIGN OF THE MULTIVARIATE SYNTHETIC T2 CHART USING LOSS FUNCTION Wai Chung Yeong1, Michael Boon Chong Khoo1, Mohammad Shamsuzzaman2, and Philippe Castagliola3 1 School of Mathematical Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia Corresponding author’s e-mail: [email protected] 2

Industrial Engineering and Management Department, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates 3

Unam Université, Université de Nantes & Irccyn umr cnrs 6597, Nantes, France

This paper proposes the economic-statistical design of the synthetic T2 chart, where the optimal chart parameters are obtained by minimizing the expected cost function, subject to constraints on the in-control and out-of-control average run lengths (ARL0 and ARL1). The quality cost is calculated by adopting a multivariate loss function. This paper also investigates the effects of input parameters, shift sizes and multivariate loss coefficients toward the optimal cost, choice of chart parameters and ARLs. Interaction effects are identified through factorial design. Besides that, comparisons are made between the significant parameters of the synthetic T2 chart with that of the Hotelling’s T2 and Multivariate Exponentially Weighted Moving Average (MEWMA) charts. Conditions where the synthetic T2 chart shows better economic-statistical performance than the Hotelling’s T2 and MEWMA charts are identified. The synthetic T2 chart compares favorably with the other two charts in terms of cost, while showing better ability to detect shifts. Keywords: economic-statistical design; factorial design; Hotelling’s T2 chart; MEWMA chart; multivariate loss function; synthetic chart (Received on April 1, 2014; Accepted on September 25, 2014) 1. INTRODUCTION Multivariate control charts are used when more than one correlated variables need to be monitored simultaneously. The Hotelling’s T2 control chart is one of the most popular multivariate control charts used in practice. However, this chart is not very efficient in detecting small to moderate shifts. To improve the performance of the Hotelling’s T2 chart, Ghute and Shirke (2008) combined the Hotelling’s T2 chart with the conforming run length (CRL) chart, leading to a multivariate synthetic T2 chart. The multivariate synthetic T2 chart operates by defining a sample as non-conforming if the T2 statistic is larger than CLT 2 / S , the control limit of the T2 sub-chart. Unlike the T2 chart, an out-of-control signal is not immediately generated when the T2 statistic is larger than CLT 2 / S . An out-of-control signal will only be generated when the number of conforming samples between two successive non-conforming samples is smaller than or equal to L, the lower control limit of the CRL sub-chart. Ghute and Shirke (2008) have shown that the multivariate synthetic T2 chart gives better ARL performance, in comparison to the Hotelling’s T2 chart. Some recent studies on control charts include Zhao (2011), Chen et al. (2011), Kao (2012a), Kao (2012b), Pina-Monarrez (2013), and many more. Duncan (1956) developed an economic design of X control charts, for the purpose of selecting optimal control chart design parameters. This approach was generalized by Lorenzen and Vance (1986), so that it can be adopted on other charts. The major weakness of the economic design of control charts is that it ignores the statistical performance of the control charts. Woodall (1986) criticized that in the economic approach, the Type I error probability is considerably higher than it would usually be compared to statistical designs, which leads to more false alarms. To improve the poor statistical performance of the economically designed control chart, Saniga (1989) proposed an economic-statistical design of the univariate X and R charts. In the economic-statistical design, statistical constraints are incorporated into the economic model. The economic-statistical design can be viewed as a cost improvement approach to statistical designs, or as a statistical performance improvement approach to economic designs.

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ISSN 1943-670X

 

International Journal of Industrial Engineering, 21(6), 295-303, 2014

THE EFFECT OF WRIST POSTURE AND FOREARM POSITION ON THE CONTROL CAPABILITY OF HAND-GRIP STRENGTH Kun-Hsi Liao Department of Product Development and Design Taiwan Shoufu University Tainan, Taiwan Corresponding author’s e-mail: [email protected] Economic and industrial developments have yielded an increase in automated workplace operations; consequently, employees must learn to operate various hand tools and equipment. The hand grip strength exerted by workers during machinery operation has received increasing attention from engineers and researchers. However, research on the relationship between hand grip strength and posture—a crucial issue in ergonomics—is scant. Therefore, in this study, the relationships among wrist posture, forearm position, and hand grip strength were examined among 72 university students. Three wrist posture and forearm positions of grip span were tested to identify the maximum volitional contraction (MVC) and hand gripping control (HGC) required for certain tasks. A one-way analysis of variance was conducted using MVC and HGC as dependent variables, and the optimal wrist posture and forearm position were identified. The findings provide a reference for task and instrument design and protecting industrial workers from diseases. Keywords: wrist posture; forearm position; hand gripping control; maximum volitional contraction (Received on November 19, 2013; Accepted on September 25, 2014) 1. INTRODUCTION Hand-grip strength is crucial in determining the ability to handle and control an object. Two types of hand-grip strength are associated with tool operation—maximal grip force and hand-gripping control strength (HGC). Numerous previous studies have elucidated the factors associated with the design of industrial safety equipment and tools based on hand-grip strength and maximum volitional contraction (MVC), maximum force which a human subject can produce in a specific isometric exercise ( Hallbeck and McMullin, 1993; Carey and Gallwey, 2002; Kong et al., 2008; Lu et al., 2008; Schlüssel et al., 2008; Liao, 2009; Liao, 2010a, 2010b; Shin, 2012; Boonprasurt and Nanthavanij; 2012; Liao, 2014). Those studies have shown that hand-grip strength is a critical source of power for operating equipment and tools in the workplace. HGC represents a controlled force precisely exerted using the palm of the hand (Murase et al., 1996; Hoeger and Hoeger, 2002). For example, HGC can indicate the force required to cut electrical wire or to tighten a screw. Hoeger and Hoeger (2002) applied MVC to standardize test results. For example, 70% MVC (MVC-70%), the vale equals to seventy percent of maximum volitional contraction force, is a typical measurement standard. Numerous previous studies have applied HGC to measure the force exerted during daily tasks, work performance, and tool operation (Mackin, 1984; Murase, 1996; Kuo, 2003). Moreover, it has been proposed that hand-grip strength could predict mortality and the expectancy of being able to live independently. Hand-grip strength measurement is a simple and economical test that provides practical information regarding muscle, nerve, bone, or joint disorders. Thus, measuring the HGC required for work tasks can provide a useful reference for designing new hand tools. Numerous studies have shown that hand-grip strength is moderated by factors such as age, gender, posture, and grip span (Carey and Gallwey, 2002; Watanabe et al., 2005; Liao, 2009). In specific circumstances, posture is the most critical factor affecting grip strength; thus, measuring grip strength can provide crucial knowledge for tool designers. The American Academy of Orthopedic Surgeons (1965) and Eijckelhof et al. (2013) have identified the following three types of wrist and forearm posture scaling for observational job analysis: (1) flexion/extension; (2) radial/ulnar deviation; and (3) pronation/supination (Figure 1), demonstrating joint range of motion (ROM) boundaries of 85 to -95, 70 to -45, and 130 to -145, respectively. Numerous previous studies have reported various grip strengths based on differing postures (O’driscoll et al., 1992; Hallbeck and McMullin, 1993; Mogk and Keir, 2003; Shih et al., 2006; Arti et al., 2010; Barut and Demirel, 2012). Kattel et al. (1996) indicated that shoulder abduction, elbow and wrist flexion, and ulnar deviation significantly affect grip force. Regarding wrist posture, numerous studies have consistently shown that large deviations from the neutral position weaken grip force (Kraft and Detels, 1972; Pryce, 1980; Lamoreaux and Hoffer, 1995; Subramanian and Mita, 2009). Carey and Gallwey (2002) evaluated the effects of wrist posture, pace, and exertion on discomfort. They concluded that extreme ISSN 1943-670X

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International Journal of Industrial Engineering, 21(6), 304-316, 2014

INTEGRATING PHYSIOLOGICAL AND PSYCHOLOGICAL TECHNIQUES TO MEASURE AND IMPROVE USABILITY: AN EMPIRICAL STUDY ON KINECT APPLYING OF HEALTH MANAGEMENT SPORT Wei-Ying Cheng1, Po-Hsin Huang1, and Ming-Chuan Chiu1,* 1

Department of Industrial Engineering and Engineering Management National Tsing Hua University HsinChu, Taiwan, R.O.C * Corresponding author’s e-mail: [email protected]

This research aimed to develop an approach for measuring, monitoring and auditing the usability of a motion-related health management product. Based on an ergonomic perspective and principles, the interactions between test participants and a motion sports device were studied using physiological data gathered from a heart rate sensor. Based on our literature review, we customized a psychological usability questionnaire which considered effectiveness, efficiency, satisfaction, error, learnability, sociability, and mental workload, generating a tool meant to reveal the subjective cognition of product usability. This research analyzed the objective (physiological) and subjective (psychological) data simultaneously to gain greater insight about the product users. In addition, heart rate data, mental workload data and the questionnaire data were synthesized to generate a comprehensive, detailed approach for evaluating usability in order to provide suggestions for improving the usability of an actual health care product. Keywords: usability; physiological techniques; questionnaires; health management product (Received on November 19, 2014; Accepted on October 20, 2014) 1. INTRODUCTION According to the Directorate-General of Budget, Accounting and Statistics of the R.O.C., the average number of working hours per worker in Taiwan in 2012 was 2140.8, ranking third in the world. On average, employees in Taiwan work 44.6 hours every week and almost 9 hours every day. This busy status is echoed among workers in Korea, Singapore and Hong Kong, who are measurably among the busiest people throughout the world. To balance work, family, and quality of life, an increasing emphasis is being placed on the concept of personal exercise since the lack of exercise has been shown to lead to common long-range health problems such as high blood pressure, diabetes and hyperlipidemia. Despite this recognition, many people do not know how often or how long to exercise in order to achieve maximum benefit. In response to this need, various products have been designed and manufactured to address this problem and to help maintain personal health status. During such product development, usability has been considered an important design issue; however, there are few usability evaluation methods that totally fit with assessment for health maintenance or product improvement, especially for the infirm and the elderly. Therefore, a method to measure and assess product use and satisfaction is important and necessary in order to distinguish the usability features of these products and to improve their usability. Thus, the purpose of this research is to establish an evaluation method which can detect the intention of the customers so as to measure the usability of the products. 2. LITERATURE REVIEW New approaches to the ancient study of ergonomics continue to emerge. During the last decade, for instance, Baesler and Sepulveda (2006) applied a genetic algorithm heuristic and a goal programming model to address ergonomics in a cancer treatment facility. Jen et al. (2008) conducted a research on a VR-Based Robot Programming and Simulation System that was ergonomics dominated. Subramanian and Mital (2008) investigated the need to customize work standards for the disabled. Nanthavanij et al. (2010) made a comparison of the optimal solutions obtained from productivity-based, safetybased, and safety-productivity workforce scheduling models. The analysis of healthcare issues, processes, and products continues to increase, influenced by modernized work conditions as well by evolving government mandates.

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 317-326, 2014

AN OPERATION-LEVEL DYNAMIC CAPACITY SCALABILITY MODEL FOR RECONFIGURABLE MANUFACTURING SYSTEMS Zhou-Jing Yu1, Jeong-Hoon Shin1, and Dong-Ho Lee1,* 1

Department of Industrial Engineering Hanyang University Seoul, Republic of Korea * Corresponding author’s email: [email protected] This study considers the problem of determining the facility requirements for a reconfigurable manufacturing system to satisfy the fluctuating demand requirements and the minimum allowable system utilization over a given planning horizon. Unlike the existing capacity planning models for flexible manufacturing systems, the problem considered in this study has both design and operational characteristics since the reconfigurable manufacturing systems have the capability of changing its hardware and software components rapidly in response to market changes or system changes. To represent the problem mathematically, a nonlinear integer programming model is suggested for the objective of minimizing the sum of facility acquisition and configuration change costs, while the throughputs and utilizations are estimated using a closed queuing network model. Then, due to the problem complexity, we suggest three heuristics, two forward-type and one backward-type algorithms. To compare the performances of the three heuristic algorithms, computation experiments were done and the results are reported. Keywords: reconfigurable manufacturing system; capacity scalability; closed queuing network; heuristics. (Received on November 28, 2013; Accepted on October 20, 2014) 1. INTRODUCTION Reconfigurable manufacturing system (RMS), one of recent manufacturing technologies, is a manufacturing system designed at the outset for rapid changes in its hardware and software components in order to quickly adjust its production capacity and functionality in response to sudden market changes or intrinsic system changes (Koren et al. 1999, Bi et al. 2008). In fact, the RMS is a new manufacturing paradigm that overcomes the concept of flexible manufacturing system (FMS) with limited success in that it is expensive due to more functions than needed, not highly reliable, and subject to obsolescence due to advances in technology and their fixed system software and hardware (Mehrabi et al. 2000). See Koren et al. (1999), Mehrabi et al. (2000, 2002), ElMaraghy (2006) and Bi et al. (2008) for more details on the characteristics of RMS. There are various decision problems in designing and operating RMSs, which can be classified into system-level, component-level and ramp-up time reduction decisions (Mehrabi et al. 2000). Among them, we focus on system-level capacity planning, called the capacity scalability problem in the literature. Capacity planning, an important system-level decision in ordinary manufacturing systems, is especially important in the RMS since it has more expansion flexibility than FMSs. Here, the expansion flexibility is defined as the capability to expand or contract production capacity. In particular, the RMS can utilize the expansion flexibility in short-term operation-level because it has the inherent reconfigurability. See Sethi and Sethi (1990) for more details on the importance of expansion flexibility. From the pioneering work of Manne (1961), various models have been developed on the capacity expansion problem in traditional manufacturing systems. See Luss (1982) for an extensive review of the classical capacity expansion problems. Besides these, there are a number of previous studies on capacity planning or system design in FMSs. For examples, see Vinod and Solberg (1985), Dallery and Frein (1988), Lee et al. (1991), Rajagopalan (1993), Solot and van Vliet (1994), Tetzlaff (1994), Lim and Kim (1998) and Chen et al. (2009). Unlike the classical ones, not many studies have been done on capacity scalability in RMSs since the new paradigm has been emerged recently. One of the earlier studies is done by Son et al. (2001) that suggest a homogeneous paralleling flow line in which paralleling is done to scale and balance the capacity of transfer lines. Deif and ElMaraghy (2006a) suggest a dynamic programming model, based on the set theory and the regeneration point theorem, to find the optimal capacity scalability plans that minimize the total cost, and Deif and ElMaraghy (2006b) suggest a control theoretic approach for the problem that minimizes the delay in capacity scalability, i.e. ramp-up time of new configurations. See Deif and ElMaraghy (2007a, b) for other extensions. Also, Spicer and Carlo (2007) consider a multi-period problem that determines the system configurations over a planning horizon and suggest two solution algorithms, an optimal dynamic ISSN 1943-670X

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International Journal of Industrial Engineering, 21(6), 327-336, 2014

A ROBUST TECHNICAL PLATFORM PLANNING METHOD TO ASSURE COMPETITIVE ADVANTAGE UNDER UNCERTAINTIES Jr-Yi Chiou1 and Ming-Chuan Chiu1,* 1

Department of Industrial Engineering and Engineering Management National Tsing-Hua University 101Kuang-Fu Road, Hsinchu Taiwan 30013, R.O.C. * Corresponding author’s e-mail: [email protected]

Developing a technology-based product platform (technical platform) that can deliver a variety of products has emerged as a strategy for obtaining competitive advantage in the global marketplace. Technical platform planning can improve customer satisfaction by integrating diversified products and technologies. Prior studies have alluded to developing a robust framework of technical platforms and validated methodologies. We propose a multi-step approach to organize technical platforms based on corporate strength while incorporating technological improbability during platform development. A case study is presented to demonstrate its advantages, referencing a company developing 3-Dimension Integrated Circuitry (3D-IC) for the semiconductor industry. We evaluate four alternatives to ensure compliance with market demands. This study applies assessment attributes for technology, commercial benefits, industrial chain completeness, and risk. Using Simple Multi-Attribute Rating Technique Extended to Ranking (SMARTER), decision-makers can quickly determine efficient alternatives in uncertain situations. Finally, a scenario analysis is presented to simulate possible market situations and provide suggestions to the focal company. Results illustrate the proposed technical platform can enhance companies’ core competencies. Significance: The proposed method incorporates technical platform planning to help fulfill current and future market demands. This method can also provide robust solutions for enterprises should untoward events occur. Thus the competitive advantage of the focal company can be assured in the future. Keywords: technical platform planning; decision analysis; technology management; fuzzy simple multi-attribute rating technique extended to ranking (SMARTER); 3-dimension integrated circuit (3D-IC) (Received on November 28, 2013; Accepted on October 20, 2014) 1. INTRODUCTION In an effort to achieve customer satisfaction, many companies have adopted product family development and platformbased methods to improve product variety, to shorten lead times, and to reduce costs. The backbone of a successful product family is the product platform, which can be generated by adding, removing, or substituting one or more modules to the platform. The platform may also be scaled in one or more dimensions to target specific market niches. This burgeoning field of engineering planning has prospered for the past 10 years. However, most of the related research has solely considered customer-oriented metrics. Other key factors such as core technologies of enterprises and technology trends under uncertainties can also affect the development of the industry. This recognition is what motivated us to conduct this research. This paper integrates these elements within technical platform planning. Technical platform planning is considered in tandem with technology management to achieve efficient solutions so as to maintain and enhance the strength of the focal company. The proposed methodology can enable companies to incorporate future-bound technology in their technology roadmap to meet diverse customer needs in the future. It also enables enterprises to concentrate their resources in the right directions based on scenario analysis. In previous studies, the technology management framework and assessment methods for uncertain situations have rarely been addressed. Fuzzy SMARTER is a decision analysis method which can solve problems under uncertainty. Experts work with limited data and linguistic expressions like good or bad to forecast future trends. In this research, fuzzy analysis was applied to resolve this set of circumstances. SMARTER only required the sequence information of future products and technologies. Therefore, this study can address the gap and combine technical platform planning, technology management as well as decision analysis to generate a new planning tool for enterprises.

ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 337-347, 2014

UNCERTAINTY ANALYSIS FOR A PERIODIC REPLACEMENT PROBLEM WITH MINIMAL REPAIR: PARAMETRIC BOOTSTRAPPING Y. Saito1, T. Dohi1,*, and W. Y. Yun2 1

Department of Information Engineering Hiroshima University 1-4-1 Kagamiyama, Higashi-Hiroshima, 739-8527 Japan * Corresponding author’s e-mail: [email protected] 2

Department of Industrial Engineering Pusan National University 30 Jangjeon-dong, Geumjeong-gu, Pusan, 609-735 Korea

In this paper we consider a statistical estimation problem for a periodic replacement problem with minimal repair which is one of the most fundamental maintenance models in practice, and propose two parametric bootstrap methods which are categorized into simulation-based approach and re-sampling-based approach. Especially, we concern two data analysis techniques: direct data analysis of the minimal repair data which obeys a non-homogeneous Poisson process and indirect data analysis after data transformation to a homogeneous Poisson process. Through simulation experiments, we investigate statistical features of the proposed parametric bootstrap methods. Also, we analyze the real minimal repair data to demonstrate the proposed methods in practice. Significance: In practice, we often encounter situations where the optimal preventive maintenance policy should be trigged. However, only a few research results on the statistical estimation problems of the optimal preventive maintenance policy have been reported in the literature. We take place the high level statistical estimation of the optimal preventive maintenance time and its associated expected cost, and derive estimators of higher moments of the optimal maintenance policy, and its confidence interval. Then, the parametric bootstrap methods play a significant role. The proposed approach enables us the statistical decision making on the preventive maintenance planning under uncertainty. Keywords: statistical estimation; parametric bootstrap method; periodic replacement problem; minimal repair; nonhomogeneous poisson process; (Received on November 29, 2013; Accepted on October 7, 2014) 1. INTRODUCTION The periodic replacement problem by Barlow and Proschan (1965) is one of the simplest, but most important preventive maintenance scheduling problems. The extended versions of this model have been studied in various papers (Valdez-Flores and Feldman 1989, Nakagawa 2005). Boland (1982) gave the optimal periodic replacement time in case where the minimal repair cost depends on the age of component, and showed necessary and sufficient conditions for the existence of an optimal periodic replacement time in the case where the failure rate is strictly increasing failure rate (IFR). Nakagawa (1986) proposed generalized periodic replacement policies with minimal repair, in which the preventive maintenance is scheduled at periodic times. If the number of preventive maintenance reaches to a pre-specified value, the system is replaced at the next preventive maintenance time. Nakagawa (1986) derived simultaneously both the optimal number of preventive maintenance and the optimal preventive maintenance time. Recently, Okamura et al. (2014) developed a dynamic programming algorithm to obtain the optimal periodic replacement time in Nakagawa (1986) model effectively. Sheu (1990) considered a preventive maintenance problem in which the minimal repair cost varies with the number of minimal repairs and the age of component. Sheu (1991) also proposed another generalized periodic replacement problem with minimal repair in which the minimal repair cost is assumed to be composed of age-dependent random and deterministic parts. If the component fails, it is replaced randomly by a new one or repaired minimally. He showed that the optimal block replacement time can be derived easily in numerical examples.

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 348-359, 2014

STRATEGIC OPENNESS IN QUALITY CONTROL: ADJUSTING NPD STRATEGIC ORIENTATION TO OPTIMIZE PRODUCT QUALITY Dinush Chanaka Wimalachandra1,*, Björn Frank1, Takao Enkawa1 1

Department of Industrial Engineering and Management Tokyo Institute of Technology Tokyo, 152-8552 * Corresponding author’s e-mail: [email protected] Many firms have shifted to an ‘open innovation’ strategy by integrating external information into new product development (NPD). This study extends the open innovation paradigm to the area of product quality control practices in NPD. Using data collected in 10 countries, this study investigates the role of external information acquired through B2B/B2C customer, competitor, technology, and manufacturing orientation in meeting quality and performance specifications of newly developed products. It also illuminates the interconnected roles of B2B and B2C customer orientation in meeting these specifications. Contrary to conventional wisdom, the results show that leveraging a variety of external information sources (in particular, frequent and informal communication with B2B customers and coordination with the manufacturing department) indeed helps firms improve internal product quality control practices in NPD. Information on B2C customers is beneficial in B2B contexts only if effectively integrated by means of B2B affective information management. Keywords: product quality; B2B customer orientation; B2C customer orientation; manufacturing orientation (Received on November 29, 2013; Accepted on April 21, 2014) 1. INTRODUCTION Research has identified product quality as one of the key determinants of NPD performance (Sethi, 2000). Due to growing competition in most industries, managers thus have come to regard the quality of newly developed products as crucial for maintaining a competitive edge in the long run (Juran, 2004). Research based on Chesbrough’s (2003) ‘open innovation’ paradigm indicates that firms’ openness to its external environment can improve their ability to innovate by enabling them to leverage outside capabilities and follow changes in the environment (Laursen and Salter, 2006), but it remains unknown whether such openness might also help firms improve their mostly internally oriented quality management practices. Hence, our study seeks to verify whether the open innovation paradigm can be extended to the area of product quality control practices in NPD. Moreover, our study aims to identify the types of external information acquired through NPD strategies (B2B/B2C customer, competitor, technology, and manufacturing orientation) that best help firms meet quality and performance specifications of newly developed products in B2B contexts. Our original claim is that accounting for external information during quality control can help firms to minimize the reoccurrence of past quality-related problems detected by B2B customers, to minimize manufacturing problems, to improve the effectiveness of early-stage prototype testing, and to learn from competitors’ best practices in quality control. Hence, we argue that many firms would profit from greater openness in quality management. Firms in B2B markets may benefit from integrating external information on B2B customers and on their eco-system, which includes product technology, manufacturing techniques, and competitor strategies. As information on B2C customers at the end of the supply chain is not directly related to immediate concerns of internal quality control in B2B contexts, we argue that accounting for this type of information directly may be problematic. However, firms might learn to leverage such information to improve prototype testing in collaboration with B2B customers. Hence, even information on B2C customers may be beneficial to firms’ quality control practices in B2B contexts if such information is handled appropriately. To examine the effectiveness of strategic openness in quality control and thus provide industrial engineers with actionable knowledge of how to improve quality control practices, our study establishes hypotheses about the influence of externally oriented NPD strategies on product quality. To test these hypotheses empirically, we collected data from 10 countries (Bangladesh, Cambodia, China, Hong Kong, India, Japan, Sri Lanka, Taiwan, Thailand, and Vietnam) in the textile and apparel industry, covering firms across the supply chain starting from raw material suppliers via manufacturers and value-adding firms (printing/dyeing/washing) to buying offices. As our study is based on statistical analyses, confirmed hypotheses are valid and can be generalized to the entire population of firms from which our firm sample was drawn. Thus, our study is not simply a case study. Rather, it derives generalizable insights that can be applied across different contexts.

ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 360-375, 2014

A LAD-BASED EVOLUTIONARY SOLUTION PROCEDURE FOR BINARY CLASSIFICATION PROBLEMS Hwang Ho Kim1 and Jin Young Choi1,* 1

Department of Industrial Engineering Ajou University 206, World cup-ro, Yeongtong-gu, Suwon-si, Gyeonggi-do, Korea * Corresponding author’s e-mail: [email protected] Logical analysis of data (LAD) is a data analysis methodology used to solve the binary classification problem via supervised learning based on optimization, combinatorics, and Boolean functions. The LAD framework consists of the following four steps: data binarization, support set generation, pattern generation, and theory formulation. Patterns that contain the hidden structural information calculated from the binarized training data play the most important roles in the theory, which consists of a weighted linear combination of patterns and works as a classifier of new observations. In this work, we develop an efficient parameterized iterative genetic algorithm (PI-GA) to generate a set of patterns with good characteristics in terms of degree (simplicity-wise preference) and coverage (evidential preference) of patterns. The proposed PI-GA can generate simplicity-wise preferred patterns that also have high coverage. We also show the efficiency and accuracy of the proposed method through a numerical experiment using benchmark machine learning datasets. Keywords: logical analysis of data; binary classification; pattern generation; genetic algorithm (Received on November 29, 2013; Accepted on October 20, 2014) 1. INTRODUCTION Binary classification (Lugosi, 2002) is an issue arising in the field of data mining and machine learning and involves the study of how to classify observations with characteristics of two classes. It has been used in the medical, service, manufacturing, and various other fields. For example, binary classification methods are used for diagnostic criteria using information obtained through inspection of patients in medicine (Prather et al., 1997); in the service field, it is used for credit ratings based on customers’ applications and history (Berry and Linoff, 1997). Binary classification problems with two data classes as defective or non-defective goods in manufacturing are particularly important when we are looking for the cause of the defects and trying to increase productivity (Chien et al., 2007). To solve the binary classification problems, various data mining approaches such as decision trees (J48), support vector machines (SVMs), neural networks (NNs) have been proposed and utilized. However, one of the main drawbacks of these learning methods is the lack of interpretation ability of the results. An NN is generally perceived as a “black box” (Ahluwalia and Chidambaram, 2008; Yeoum and Lee, 2013), and it is extremely difficult to document how specific classification decisions are reached. SVMs are also “black box” systems that do not provide insights on the reasons or explanations about classification (Mitchell, 1997). Thus, these approaches do not exhibit both high accuracy and explanatory power for binary classification. Meanwhile, the major disadvantage of the decision tree is its computational complexity. Decision trees examine only a single field at a time so that large decision trees with many branches are complex and time-consuming (Safavian and Landgrebe, 1991). The logical analysis of data (LAD; Crama et al., 1998; Boros et al., 1997; Boros et al., 2000; Hammer and Bonates, 2006) proposed recently is a data analysis methodology used to solve the binary classification problem via supervised learning based on patterns that contain hidden structural information calculated from binarized training data. Therefore, LAD is an effective methodology that can easily explain the reasons for the classification using patterns. Moreover, LAD can provide higher classification accuracy than others if the patterns used for the classification represent all characteristics of data and the number of patterns is sufficient. In many medical application studies, LAD has been applied to classification problems for diagnosis and prognosis. Such studies have shown that the accuracy of LAD is comparable with the accuracy of the best methods used in data analysis so far, usually providing similar results to other binary classification methods (Boros et al., 2000). However, there is still a problem in that classification performance of LAD can vary depending on certain characteristics of the patterns generated in the LAD framework. Therefore, pattern generation is the most important issue in the LAD framework, and has been studied in various ways these days. The conventional pattern generation methods can mainly be divided into (i) enumeration-based approaches and (ii) mathematical approaches. First, most of the early studies on pattern generation used enumeration-based techniques (Boros ISSN 1943-670X

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International Journal of Industrial Engineering, 21(6), 376-383, 2014

A STUDY ON COLLABORATIVE PICK-UP AND DELIVERY ROUTING PROBLEM OF LINE-HAUL VEHICLES IN EXPRESS DELIVERY SERVICES Friska Natalia Ferdinand1, Young Jin Kim3, Hae Kyung Lee2, and Chang Seong Ko2,* 1 Department of Information System University of Multimedia Nusantara Kampus UMN, Scientia Garden, Boulevard Gading Serpong, Tangerang, Indonesia 2

Department of Industrial and Management Engineering Kyungsung University 309 Suyeong-ro, Nam-gu, Busan, 608-736 Busan, South Korea * Corresponding author’s e-mail: [email protected]

3

Department of Systems Management and Engineering Pukyoung National University 45 Yongso-ro, Nam-gu, Busan, 608-737 Busan, South Korea

In the Korean express delivery service market, many companies have been striving to extend their own market share. An express delivery system is defined as a network of customers, service centers and consolidation terminals. Some companies operate line-haul vehicles in milk-run types of pick-up and delivery services among consolidation terminals and service centers with locational disadvantages. The service centers with low sales are kept operating, even if they are unprofitable, to ensure the quality of service. Recently, a collaborative operation is emerging as an alternative to reduce the operating costs of the handicapped centers. This study considers a collaborative service network with pick-up and delivery visits for linehaul vehicles for the purpose of maximizing the incremental profits of collaborating companies. The main idea is to operate only one service center shared by different companies for service centers with low demands and change the visit schedules accordingly. A genetic algorithm-based heuristic is proposed and assessed through a numerical example. Keywords: express delivery services; collaborative pick-up and delivery; line-haul vehicle; milk-run, genetic algorithm (Received on November 29, 2013; Accepted on October 20, 2014) 1. INTRODUCTION Pick-up and delivery problems (PDPs) are aimed at designing a vehicle route starting and ending at a common depot in order to satisfy pick-up and delivery requests in each location. In a traditional pick-up and delivery problem, each customer usually receives a delivery originating from a common depot and sends a pick-up quantity to the same depot. Most of the express delivery service centers in Korea are directly linked to a consolidation terminal. However, service centers located in rural areas with low utilization may not be directly linked to a consolidation terminal (Ferdinand et al., 2013). These remote service centers with low sales are mostly operated, even though unprofitable, in order to ensure the quality of service. There has thus been a growing need to develop an operational scheme to ensure a higher level of service as well as profitability. It has been claimed that a collaborative operation among several companies may provide an opportunity to increase profitability as well as to ensure the quality of service. There exist various types of collaboration in express delivery services and such an example includes sharing of vehicles, consolidation terminals, and other facilities. This study considers the collaboration among companies sharing service centers and line-haul vehicles. Visit schedules are also determined accordingly to enhance profitability of collaborating companies. Service centers located in rural areas with low utilization may not be profitable, and thus only one company will operate a service center and vehicles in each location along the route (so-called, ‘monopoly of service center’). Other companies will use the service center and vehicles at a predetermined price. All the routes should provide pick-up and delivery services, and all the vehicles should return to the depot at the end of each route. The objective of this study is to construct a network design for profitable tour problem (PTP) with collaborative pick-up and delivery visits that maximizes the incremental profit based on the maxmin criterion.

ISSN 1943-670X

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International Journal of Industrial Engineering,21(6),384-395, 2014

OPTIMIZATION OF WIND TURBINE PLACEMENT LAYOUT ON NON-FLAT TERRAINS Tzu-Liang (Bill) Tseng1, Carlos A. Garcia Rosales1, and Yongjin (James) Kwon2,* 1

Department of Industrial, Manufacturing and Systems Engineering The University of Texas at El Paso 500 W, University Ave. El Paso, TX 79968, USA 2

Department of Industrial Engineering Ajou University Suwon, 443-749, Republic of Korea * Corresponding author’s e-mail: [email protected] To date, wind power has become popular due to climate change, greenhouse gases and diminishing fossil fuel. Although wind turbine technology for electricity is already mature, industry is looking to achieve the best utilization of the wind energy in order to fulfill the electrical needs for cities at a very affordable cost. In this paper, a method entitled Cluster Identification Algorithm (CIA) and an optimization approach called a Multi-Objective Genetic Algorithm (MOGA) has been developed. The main objective is to maximize the power and the efficiency, while minimize the cost caused by the size and quantity of wind turbines installed on non-flat terrains (i.e., a terrain with different heights). The fitness functions evaluate different population sizes and generation numbers to find the best options. Necessary assumptions are made in terms of wind directions, turbine capacities, and turbine quantities. Furthermore, this study considers how the downstream decay model from the wind energy theory describes a relationship between the wind turbines positioned ahead and the subsequent ones. Finally, a model that relates the layout of wind farm with an optimal combination of efficiency, power and cost is suggested. A case study that addresses the three dimensional terrain optimization problems using the combination of CIA and MOGA algorithms is presented, which validates the proposed approach. The methodology is expected to help solving other similar problems that occur in the renewable energy sectors. Keywords: wind turbine; cluster identification algorithm (CIA); multi-objective genetic algorithm (MOGA); optimization of wind farm layout; wind energy (Received on November 29, 2013; Accepted on June 10, 2014) 1. INTRODUCTION Currently, wind energy is receiving considerable attention as an emission-free, low cost alternative to fossil fuel. It has a wide range of applications such as battery charging, mobile power generator, or auxiliary power sources for ships, houses and buildings. In terms of a large, grid-connected array of turbines, it is becoming an increasingly important source of commercial electricity. In this paper, an optimization methodology encompassing Cluster Identification Algorithm (CIA) and Multi-Objective Genetic Algorithm (MOGA) are developed to optimize the wind farm layout on non-flat terrain. The optimization of layout is a multi-faceted problem, such that (1) maximizing the efficiency, which can be heavily affected by the aerodynamic losses; (2) maximizing the wind power generation; and (3) minimizing the cost of installation, which is affected by the size and quantity of wind turbines. At the same time, other important variables, including different terrain heights, wind directions, wind speed over a period of one year, and terrain size, are taken into consideration. The terrain is analyzed with the use of Cluster Identification Algorithm (CIA) because it is possible to determine a cluster of positions. After that, a subset of positions that is the most suitable can be selected from the total land area. Another important fact is that the wind turbine capacities and characteristics are not the same. Physical and performance characteristics like the rotor area and the turbine height should be analyzed simultaneously. Based on the extensive review of closely related literature, it is difficult to locate the proper methodology for optimal wind turbine placement problems that comprehensively considers the aforementioned issues [Lei 2006, Kusiak and Zheng 2010, Kusiak and Song 2010], which has been the motivation of this research. In this context, this paper presents the development of optimization algorithms and the computational results of the real-world case.

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International Journal of Industrial Engineering, 21(6), 396-407, 2014

AGENT-BASED PRODUCTION SIMULATION OF TFT-LCD FAB DRIVEN BY MATERIAL HANDLING REQUESTS Moonsoo Shin1, Taebeum Ryu1, and Kwangyeol Ryu2,* 1

Department of Industrial and Management Engineering Hanbat National University Daejeon, Korea 2

Department of Industrial Engineering Pusan National University Busan, Korea * Corresponding author’s e-mail: [email protected] Thin film transistor-liquid crystal display (TFT-LCD) fabs are highly capital-intensive. Therefore, to ensure that a fab remains globally competitive, production must take place at full capacity, with extensive utilization of resources, and must employ just-in-time principles that require on-time delivery with minimum work-in-process (WIP). However, limited space and lack of material handling capacity act as constraints that hamper on-time delivery to processing equipment. Therefore, to build an efficient production management system, a material handling model should be incorporated into the system. This paper proposes a simulation model applying an agent-based collaboration mechanism for a TFT-LCD fab, which is driven by material handling requests. Every manufacturing resource, including equipment for processing and material handling as well as WIP, is represented as an individual agent. The agent simulates operational behaviors of associated equipment or WIP. This paper also proposes an event graph-based behavior model for the agent. Keywords: TFT-LCD fab; production management; production simulation; material handling simulation; agent (Received on December 1, 2013; Accepted on November 30, 2014) 1. INTRODUCTION The thin film transistor-liquid crystal display (TFT-LCD) industry is naturally capital-intensive, with a typical fab requiring an investment of a few billion dollars. A cutting-edge TFT-LCD fab contains highly expensive processing equipment performing complicated manufacturing operations and large material handling equipment connecting this processing equipment (Chang et al., 2009). Because idle equipment and more work-in-process (WIP) than necessary lead to high operational costs, production must take place at full capacity, with extensive utilization of resources, and employ just-intime principles that require on-time delivery with minimum WIP to ensure that the fab remains globally competitive (Acharya, 2011). Thus, optimal management of production capacity is critical, and consequently, efficient production planning and scheduling pose great challenges to the TFT-LCD industry. Two alternative approaches are usually employed for production planning and scheduling in TFT-LCD fabs (Ko et al., 2010): 1) optimization and 2) simulation. An optimization approach aims to find an optimal solution, which is represented as a combination of resources and products within a given time frame, and typically applies linear programming (LP) methods (Chung et al., 2006, Chung and Jang, 2009, Leu et al., 2010). It is difficult for a mathematical model to sufficiently reflect dynamic field constraints, and it is challenging (albeit possible) to reformulate the mathematical model in response to environmental changes. On the other hand, a simulation approach continuously searches for an optimal solution by alternating decision variables, such as step target, equipment arrangement, and dispatching rules, according to the given processing status (Choi and You, 2006). Thus, a simulation approach is more suited to a dynamic environment than an optimization approach. However, existing approaches to production simulation for TFT-LCD fabs restrictively implement material handling processes; consequently, they have certain limitations in their prediction power (Shin et al., 2011). This paper proposes a material handling request-driven simulation model for production management of a TFT-LCD fab, aiming to implement dynamic material handling behavior. In particular, an agent-based collaboration mechanism is applied to production simulation that provides a production manager with the capability of performing “what-if” analysis on production management problems such as production planning and scheduling. Agent-based approaches have been widely adopted to ensure collaborative decision-making (Lee et al., 2013). Every manufacturing resource, including process and material handling equipment as well as WIP, is represented as an individual agent, and material handling request-driven collaboration among these agents implements dynamic WIP routing. The remainder of this paper is organized as follows. ISSN 1943-670X

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International Journal of Industrial Engineering, 21(6), 408-420, 2014

LOWER AND UPPER BOUNDS FOR MILITARY DEPLOYMENT PLANNING CONSIDERING COMBAT Ivan K. Singgih1 and Gyu M. Lee1,* 1

Department of Industrial Engineering Pusan National University Busan, Korea * Corresponding author’s e-mail:[email protected] In the military deployment planning problem (DPP), troops and cargoes are transported from source nodes to destination nodes, while considering various constraints, such as the supply availability, demand satisfaction constraints, and availability of required multimodal transportation assets. The enemies may exist at several locations to block the transportation of troops and cargoes to the destinations. In order to arrive at the destinations, the troops need to have combats with the enemies, which cause loss of troops. To satisfy the demands, additional troops may be necessary to be transported. Usage of various transportation modes leads to the introduction of subnodes and subarcs in the graphical representation. A mixed integer programming (MIP) formulation is proposed, which is classified as a fractional programming. A solution method which calculates the lower and upper bounds is developed. Then, the gap between the lower and upper bounds is calculated. The computational results are provided and analyzed. Keywords: military deployment planning problem; multimodal transportation (Received on December 1, 2013; Accepted on September 26, 2014) 1. INTRODUCTION Military DPP is dealing with transportation of troops and cargoes from the sources to destinations using transportation assets to satisfy the demand requirements at the destinations. The transportation assets in a single mode or multi-modes can be used. Practically, the usage of multimodal transportation assets is needed in some geographical location which cannot be traveled only by transportation assets of a single mode. The usage of multimodal transportation assets requires the unloading of troops and cargoes from transportation assets of a mode and loading of troops and cargoes to transportation assets of another mode. Each unit of troops or cargoes is required to be transported to the destinations before a certain due date, in order to support military activities in peace or war situations. Late deliveries are not preferred, so penalties are charged for late deliveries. However, the enemy troops exist between some nodes and block the transportation of the troops and cargoes. To transport the troops and cargoes between nodes where the enemies exist, the troops need to have combats with the enemies. Each combat reduces the size of the troops and the enemies. The costs related with transportation, transfer, and inventory of troops and cargoes, procurement and inventory of transportation assets, number of troops loss, and penalties of late deliveries are minimized in the objective function. Each part of the objective function is associated with a certain weight. Several constraints, which are the availability of supplies and flow balance of troops, cargoes, and transportation assets, must be satisfied. The multimodal transportation assets used to transport the troops and cargoes are shown in Figure 1. Some studies on DPP using multimodal transportation assets have been conducted. A multimodal DPP for military purposes was formulated by Singgih and Lee (2013) who introduced a graphical representation of subnodes and subarcs, which are used to express the nodes and arcs while considering the usage of multimodal transportation assets. They formulated the problem as an MIP, obtained the solutions using LINGO and analyze the characteristic of the problem using sensitivity analysis. A large-scale multicommodity, multi-modal network flow problem with time windows is solved by Haghani and Oh (1996). A heuristic which exploits an inherent network structure of the problem with a set of constraints and an interactive fix-and-run heuristic are proposed to solve a very complex problem in disaster relief management. A new large-scale analytical model was developed by Akgun and Tansel (2007) and solved using CPLEX. The usage of relaxation and restriction methods enables the model to find the solution in a shorter time. The studies on the multicommodity freight flows over a multimode network were reviewed by Crainic and Laporte (1997). Lanchester combat model is a set of differential equation models that describe change in the force levels that describe the combat process (Caldwell et al., 2000). Lanchester differential equation models are able to provide insight into the dynamics of the combat and provide more information to address more critical operational problems. Proposed by F. W. Lanchester in 1914, the Lanchester combat models are used in various researches. Kay (2005) explained and gave examples ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 421-435, 2014

ANALYSIS OF SUPPLY CHAIN NETWORK BY RULES OF ORIGIN IN FTA ENVIRONMENT Taesang Byun1, Jisoo Oh2, and Bongju Jeong2,* 1

Sales Planning Team Nexen Tire Inc. Bangbae-dong 796-27, Seoul, Korea 2

Department of Information and Industrial Engineering Yonsei University 50 Yonsei-ro 120-749, Seoul, Korea * Corresponding author’s e-mail: [email protected]

This paper presents a supply chain in Free Trade Agreements (FTA) environments governed by rules of origin and analyzes it using profit analysis and supply chain planning. The proposed supply chains follow the rules of origin as wholly obtained, substantially transformation, and third country processing criteria. These supply chain can be used to take nontariff benefits according to the rules of origin. In order to evaluate the validity of the proposed supply chain, we construct profit models and show optimal sales prices can maximize net profits. The profit model encompasses the structure of supply chain which enables decision-makers to make a strategic decision on evaluation and selection of efficient FTA. Using the output of profit models, global supply chain planning models are built to maximize profit and customer needs. A case study for a textile company in Korea is provided for illustrating how the proposed supply chain models work. Keywords: FTA; rules of origin; supply chain management; profit analysis; supply chain planning (Received on December 16, 2013; Accepted on October 20, 2014) 1. INTRODUCTION In recent global market, Free Trade Agreements (FTA) are rapidly increasing to maximize the international trade profits among countries. By joining FTA, each country expects to explore and acquire new market for export, promote industrial restructuring, and improve the relevant systems. Moreover, the trade tariff concession results in the economic effects of inflow of oversea capital and technologies. Relaxing the tariff barriers and extensive application of rules of origin expedites the adoption of FTA and improve the multi-national production environments. This is because in employing the rules of origin, different tariff rates are applied and resolved with regard to boundary of origins. Therefore, there is a strong motivation for global companies to construct a framework for FTA supply chain and then take advantage of it. In this research, we propose supply chain networks according to the rules of origin in FTA environment. We investigate a profit structure of company and find optimal selling price in FTA supply chain. Then companies can decide overseas production for their profit maximization and establish supply chain planning on multinational production activities. In this paper, we pursue the profit maximization of each company involved in FTA supply chain and try to simplify it for further analysis. The case study shows how a Korean textile company can take advantage of non-tariff concession in FTA environment. Although many previous literatures are found in addressing the various issues of FTA environment, which are mostly its economic impacts, few studies have been performed in view of supply chain network. Not surprisingly, some researchers are interested in competitiveness gains in FTA (Weiermair and Supapol (1993), Courchene (2003), and Seyoum (2007)). Regarding the rules of origin, many researchers considered the benefit of usage of it in FTA environments to maximize the profit of companies (Estevadeordal and Suominen (2004), Bhavish et al. (2007), Scott et al. (2007), and Drusilla et al. (2008)). In terms of pricing policy, Zhang (2001) formulated the model for profit maximization to choose the location of a delivery center considering customer demand and the selling price of a product and Manzini et al.(2006) developed mathematical programming models for the design of a multi-stage distribution system to be flexible and maximum profit. Hong and Lee (2013) and Lee (2013) suggested the price and guaranteed lead time of a supplier that offers a fixed guaranteed lead time for a product. Savaskan et al. (2004) defined the model relationship between producer, retailer, and third party in recycling environment and developed a profit model for each member. On the other hand, Zhou et al. (2007) tried to guarantee the profits of all supply chain members using the profit model in consideration of order quantity and selling price.

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INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 1-10, 2015 APPLICATION OF INTEGRATED SUSTAINABILITY ASSESSMENT: CASE STUDY OF A SCREW DESIGN Zahari Taha 1, H. A. Salaam2,*, S. Y. Phoon1, T.M.Y.S. Tuan Ya3 and Mohd Razali Mohamad4 1

Faculty of Manufacturing Engineering 2 Faculty of Mechanical Engineering Universiti Malaysia Pahang Pekan, Pahang 26600, Malaysia * Corresponding author’s e-mail: [email protected] 3

Department of Mechanical Engineering Universiti Teknologi PETRONAS Bandar Sri Iskandar Tronoh, Perak 31750, Malaysia

4

Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya, Durian Tunggal, 76100, Malaysia Sustainability can be referred to as meeting the needs of the present generation without compromising the ability of future generations to meet their own needs. For politicians, it is an attempt to shape the social; sustain the economy and preserved the environment for future generations. Balancing these three criteria is a difficult task since it involves different output measurements t. The aim of this paper is to present a new approach of evaluating sustainability at the product design stage. There are three criteria involved in this study which is manufacturing costs, carbon emission release into the air and ergonomic assessment. Analytic hierarchy process (AHP) is used to generalize the outputs of the three criteria which is then ranked accordingly. The highest score is selected as the best solution. In this paper, a simple screw design is presented as a case study. Keywords: sustainable assessment; multi-criteria decision method (MCDM); analytic hierarchy process (AHP); screw. (Received on November 30, 2013; Accepted on October 20, 2014) 1. INTRODUCTION The United Nations Department of Economic and Social Affairs/Population Division projected that the world population will increase from 6.1 billion in the year 2000 to 8.9 billion by the year 2050 (United Nations 2004). With this huge number of human population, the need for consumer products will increase. Many consumers purchase multi-functional products according to their individual preferences (Thummala, 2011). In order to fulfill consumer demand for products, manufacturing companies can consider four (4) ways to do it. The first way is by expanding their production lines or factory areas. By doing this, they can buy more equipment and hire more workers to increase their productivity. Besides that they can explore new business by adding more new products in the production line to increase the company profits. The second way is by increasing the number of workers and machines without expanding the factory building. By doing this, the productivity can be increased; but with a minimal cost compared to expanding the factory. The third way is by giving the operator opportunity to work overtime or changing the operation time to a 24 hours production line system with two or three shifts. By doing this, it will give the operators a chance to increase their income for a better living. Lastly, they can outsource the manufacturing of some components. The difficulty with this is in ensuring the exact quality needed by the customers and the capability of the third party company in delivering those components on time to the customers. However which way they want to do it they need to consider manufacturing, environmental and social costs. Theoretically, expanding the factory will increase productivity, but the investment cost is too high and it can lead to serious environmental problems since more and more land must be used. On the other hand, failure to expand can lead to serious society problems such as poverty which can further lead to criminal activities. On the other hand allowing workers to work overtime will cause them to have less resting time thus affecting productivity and their health. To protect the environment for the future generation, many countries around the world have introduced more stringent environmental legislations. As a result; manufacturing companies especially in Malaysia are forced to abide by these new

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 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 11-22, 2015 International Journal of Industrial Engineering, 21(1), 99-111, 2014 International Journal of Industrial Engineering, 21(1), 99-111, 2014

GLOBAL SEARCH OF GENETIC ALGORITHM ENHANCED BY MULTI-BASIN DYNAMIC NEIGHBOR SAMPLING Misuk Kim1 and Gyu-Sik Han2,* 1

Department of Industrial Engineering Seoul National University 1 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Republic of Korea

2

Division of Business Administration Chonbuk National University 567 Baekje-daero, Deokjin-Gu, Jeonju-si, Jeollabuk-do 561-756, Republic of Korea * Corresponding author’s e-mail: [email protected] We propose a pioneering enhanced genetic algorithm to find a global optimal solution without derivatives information. A new neighbor sampling method driven by a multi-basin dynamics framework is used to efficiently divert from one existing local optimum to another. The method investigates the rectangular-box regions constructed by dividing the interval of each axis in the search domain based on information of the constructed multi-basins, and then finds a better local optimum. This neighbor sampling and the local search are repeated alternately throughout the entire search domain until no better neighboring local optima could be found. We improve the quality of solutions by applying genetic algorithm with the resulting point as an initial population generator. We fulfill two kinds of simulations, benchmark problems and a financial application, to verify the effectiveness of our proposed approach, and compare the performance of our proposed method with that of direct search, genetic algorithm, particle swarm optimization, and multi-starts. Keywords: genetic algorithm, global optimal solution, multi-basin dynamic neighbor sampling, heston model (Received on November 27, 2013; Accepted on September 02, 2014) 1. INTRODUCTION Many practical scientific, engineering, management, and finance problems can apply to global optimization problems [Armstrong (1978), Conn et.al. (1997), Cont and Tankov (2004), Goldstein and Gigerenzer (2009), Lee (2005), Modrak (2012), Shanthi and Sarah (2011)]. From the complexity point of view, the global optimization problems belong to the hard problem class, with the assumption that the computational time and cost required to solve them increase exponentially with the input size of the problem. In spite of these difficulties, various heuristic algorithms have been developed to reduce computational time and cost in resolving them. The classical smooth methods are optimization techniques that need objective functions that behave smoothly because the methods use the gradient, the Hessian, or both information types. Mathematically, the methods are well established, and some smooth optimization problems are resolved fast. However, the derivative information is not given in most real-world optimization problems, which are large and complicated. Thus, more time and cost are required to find solutions. Stochastic heuristics such as genetic algorithm, direct search, simulated annealing, particle swarm optimization, and clustering method are other popular methods that proved to work well for many problems that are completely impossible to solve using classical methods [Gilli et.al. (2011), Kirkpatrick et.al. (1983), Michaelwicz and Fogel (2004), Törn (1986), Wang et.al. (2013)]. The performances of these previous studies depend on where the heuristic algorithms are applied to which problem or what the initial estimate for its optimization is. One of the main drawbacks of these stochastic heuristics is that too much computing time and cost are used to locate a local (or improved local) optimal solution, but not a global one. In this paper, we propose a novel enhanced genetic algorithm that incorporates and extends the basic framework from Lee (2007), which is a deterministic methodology for global optimization to reduce the disadvantages of stochastic heuristics. The method utilizes multi-basin dynamic neighbor sampling to locate an adjacent local optimum by constructing rectangular-box regions that approximate multi-basins of convergence in the search space. By alternating this neighbor sampling and the local search, we try to improve and accelerate the search for better local optima. Then, the resulting point is used as an ancestor of the initial descendant populations to enhance the global search of genetic algorithm. We will also compare the performances of the conventional heuristic global optimization algorithms with that of our proposed method. ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 23-34, 2015

THE IMPACT OF RELATIONSHIP STRATEGIES ON SURVIVABILITY OF FIRMS INSIDE SUPPLY NETWORKS Mohamad Sofitra12,*, Katsuhiko Takahashi1 and Katsumi Morikawa1 1

Graduate School of Engineering Hiroshima University Higashi-Hiroshima, Japan 739-8527 * Corresponding author’s e-mail: [email protected] 2

Department of Industrial Engineering Universitas Tanjungpura Pontianak, Indonesia

A relationship strategy, which engages firms with each other, mainly intends to achieve a firm’s goals. One goal of such firms is to prolong the firm’s survival in the market. At the supply networks (SN) level, the interactions among firms by means of engaging strategies, i.e., cooperation, defection, competition and co-opetition, are complexly interconnected and coevolved. Due to their complexity and dynamic nature, investigations of the outcomes of the coevolution of interconnected relationship strategies are non-trivial tasks. To overcome these difficulties, this paper proposes cellular automata simulation frameworks and adopts a complex adaptive supply networks perspective to develop a model of the coevolution of interconnected relationship strategies in a supply network. We aimed to determine how and under what conditions the survivability of firms inside supply networks is affected by the coevolution of interconnected relationship strategies among them. We constructed experiments using business environment scenarios of a SN as its factors and observed how different interaction policies of firms could produce networks effects that impact the lifespan of firms. We found that a co-operation coupled with a co-opetition policy in a business environment that favors co-operation can promote the lifespan of nodes at both the individual and SN level. Keywords: interconnected relationships strategy; complex adaptive supply network; cellular automata; survivability. (Received on November 29, 2013; Accepted on October 20, 2014) 1. INTRODUCTION Each firm situated in any network needs to build relationships with other firms. A relationship strategy, which engages firms with each other, mainly intends to achieve a firm’s goals. One goal of firms is to prolong its survival in the market. Issues in the buyer-supplier relationship strategy and its impact at individual or dyad level of firms have been studied for over two decades (Choi & Wu, 2009). However, at networks level it recognized that instead a particular relationship strategy (e.g., cooperation, defection, competition and coopetition) exists and being independent from each others, they are complexly interconnected (Ritter, 2000). None of the relationships in a network are built or operate independently of others (Hakansson & Ford, 2002). A small shift in a particular relationship state in a given network could affect the other relationships that are directly connected and then in turn affect the other indirectly connected relationships. This domino effect can result in either a minor or major complication at both the individual and SN level. Moreover, firms and their relationship strategies are very dynamic, similar to living entities that co-evolved over time (Choi, Dooley, & Rungtusanatham, 2001; Pathak et.al., 2007). Therefore, to further our understanding of the complex nature of a SN, we must extend our analysis from individual firms or the dyadic level to the network level. At the network level of analysis, we will attempt to determine how individual strategies (i.e., cooperation, defection, competition and co-opetition) interconnect and coevolve inside the SN and investigate the related emergence network effects. A cooperation relationship between firms is motivated by a common goal (e.g., to solve problems, to improve products and streamline processes, etc.) (Choi, Wu, Ellram, & Koka, 2002) and/or a resource dependency (Ritter (2000); Lee & Leu (2010)). This type of relationship builds upon teamwork by sharing information and resources. Conversely, a defection relationship between firms is provoked by short-term opportunistic behavior (e.g., being lured by better terms of a contract from other firms) (Nair, Narasimhan, & Choi, 2009). A competition relationship between firms is based on the logic of economic risks (e.g., appropriation risk, technology diffusion risk, forward integration by suppliers and/or backward integration by buyers, etc.) that can introduce threats to the core competence of a firm (Choi et al., 2002). Conversely, co-opetition is a strategy employed by firms that simultaneously mixes competitive actions with co-operative activities (Gnyawali & Madhavan, 2001). The motivation for engaging in coISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 35-45, 2015

DRIVERS AND OBSTACLES OF THE REMANUFACTURING INDUSTRY IN CHINA: AN EMPIRICAL STUDY Yacan Wang1,*, Liang Zhang1, Chunhui Zhang1 and Ananda S Jeeva2 1

Department of Economics Beijing Jiaotong University No.3 Shangyuan Residency, Haidian District Beijing 100044, People’s Republic of China * Corresponding author’s email: [email protected] 2

Curtin Business School Curtin University Perth, Australia 6845

Remanufacturing is one of the prioritized sectors that pushes sustainability forward and has been vigorously promoted by two rounds of experimental programs in China. A survey of 7 Chinese remanufacturing enterprises involving 190 respondents is used to empirically identify the current situation and explore influential factors of the remanufacturing industry in China. The results of principal component factor analysis indicate that enterprise strategy factors as well as policy and technical factors are the major drivers of the remanufacturing industry with the largest contribution rate of 21.424% and 20.486% respectively. The policy, economic factors and industry environmental factors are major barriers with the largest contribution rate of 29.361% and 19.690% respectively. This is the first empirical study to explore the influencing factors of the remanufacturing industry in China. The results provide preliminary reference for government and industry to further develop mechanism to promote remanufacturing practice in China. Keywords: remanufacturing industry; drivers; barriers; empirical study; China (Received on November 29, 2013; Accepted on August 10, 2014) 1. INTRODUCTION The current challenges in scarce resources and polluted environment in China have spurred the circular economy as a new key to China’s economic growth (Zhu & Geng, 2009). Remanufacturing, as a pillar of circular economy, is pushed forward by a series of policies by the Chinese government. In 2005, the State Council issued Several Options of the State Council on Speeding up the Development of Circular Economy, which included remanufacturing as an important component of circular economy. In 2008, the National Development and Reform Commission (NDRC) launched experimental auto-part remanufacturing programs in 14 selected firms. In 2009, the Ministry of Industry and Information Technology (MIIT) also launched the first block of experimental machinery and electronic products remanufacturing programs in 35 selected firms and industry agglomeration areas. In 2011, NDRC issued Information on Further Improving the Work on Experimental Remanufacturing Programs, which aimed to further expand the category and coverage of remanufacturing products. These experimental programs have generated some professional remanufacturing firms. Data from China Association of Automobile Manufacturing showed that by the end of 2010, China had already built a remanufacturing capacity of 0.63 million pc/set including engines, gear boxes, steering booster, dynamos, etc., and 12 million retreaded tires. However, remanufacturing is still in an infancy stage in China, encumbered by various obstacles. The Chinese government has not established an independent and robust legal system specific to the remanufacturing industry (Wang, 2010). Furthermore, there is no clear direction for the growth of the remanufacturing industry (Zhang et al, 2011). Most of the studies on remanufacturing in China focus on research and development (R&D) of technology and products. Extant literature that qualitatively analyzes the drivers and barriers of remanufacturing are limited, and empirical studies are rare. Although Zhang et al. (2011) propose different development paths based on the features of the resources input in different phases of automobile remanufacturing development, the current situation and influential factors have not been tested empirically. Hammond et al. (1998) explore the influential factors of the automobile remanufacturing industry in the USA by carrying out a series of empirical investigations. Seitz (2007) has empirically examined the influencing factors of remanufacturing by interviewing a number of Original Equipment Manufacturers (OEM). Nevertheless, owing to the different development level and overall environment of remanufacturing, the influential factors of remanufacturing industry ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 46-61, 2015

AN INTEGRATED FRAMEWORK- FOR DESIGNING A STRATEGIC GREEN SUPPLY CHAIN WITH AN APPLICATION TO THE AUTOMOTIVE INDUSTRY S. Maryam Masoumi K1; Salwa Hanim Abdul-Rashid1,*, Ezutah Udoncy Olugu1; Raja Ariffin Raja Ghazilla1 1

Centre for Product Design and Manufacturing (CPDM), Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia *Corresponding author’s e-mail: [email protected]

In today’s global business, several organizations have realized that green supply chain practices provide them with competitive benefits. In this respect, a strategically oriented view of environmental management is critical to supply chain managers. Regarding the importance of this issue, an attempt has been made to develop an integrated framework for designing a Strategic Green Supply Chain (SGSC). Firstly, by reviewing the literature, a causal relationship model is developed. This model presents the main factors affecting the decisions for prioritizing green strategies and initiatives. Secondly, based on this model, a decision-making tool using the Analytic Network Process (ANP) is provided. This tool assists companies to prioritize the environmental strategies and related initiatives in different operational areas of their supply chain. Finally, in order to provide part of the data required in this tool, a performance measurement system is developed to evaluate the strategic environmental performance of the supply chain. Keywords: strategic green supply chain; green supply chain design; analytical network process; environmental strategy; environmental performance measurement (Received on November 30, 2013; Accepted on January 2, 2015) 1. INTRODUCTION In recent years, increased pressure from various stakeholders, such as regulators, customers, competitors, community groups, global communities, and non-governmental organizations (NGOs), have motivated companies to initiate environmental management practices not only at the firm level, but also throughout the entire supply chain (Corbett and Klassen 2006, Gonzalez-Benito and Gonzalez-Benito 2006). This shift from the implementation of green initiatives at the firm level towards the whole supply chain, requires a broader development of environmental management from the initial sources of raw material to the end-user customers in both the forward and reverse supply chain (Linton et al. 2007). Previous studies have introduced a long list of green initiatives associated with various operational areas of supply chains (Thierry et al. 1995, Zsidisin and Hendrick 1998, Rao and Holt 2005, Zhu et al. 2005). The highly competitive nature of the business environment requires the companies to carefully consider the outcomes of these green initiatives, focusing on only those that are strategic to their operational and business performance. In fact, making the wrong choice of green initiatives can lead to wasted cost and effort, and may even reduce competitive advantages (Porter and Kramer 2006). In this respect, supply chain managers have to consider only the green supply chain initiatives (GSCIs) that are strategic to their business performance. In other words, there is a need to make informed decisions in terms of selecting practices that would potentially deliver better value and competitiveness. Adopting the concept of strategic social responsibility defined by Porter and Karmer (2006), the term Strategic Green Supply Chain (SGSC) in this paper refers to a green supply chain (GSC) that strategically selects and manages green initiatives to generate sustainable competitive advantage when implemented throughout the entire chain. The term ‘strategic’ reflects the proactive approach as opposed to a responsive approach taken in initiating GSCIs. According to the theory of the Natural-Resource-Based-View (NRBV) developed by Hart (1995), and Hart et al. (2003), there are three distinct kinds of green strategy – pollution prevention, product stewardship, and clean technology. Each of these green strategies has its own drivers, which enable it to provide the organizations with a specific competitive advantage. In an attempt to decide which green strategy is more suitable for a firm’s business, it has to consider several determining factors. In this study, an integrated framework is developed to assist the organizations to design a SGSC that provides them with a framework for selecting the most suitable green strategy for their supply chain and aligning all of their green initiatives with the selected strategy. This framework will provide the insight into the strategic importance of green initiatives for a company and assist the managers to strategically manage their green supply chain improvement programmes. The strategic importance of green strategies to an enterprise will be determined by evaluating the role of these initiatives in meeting the requirements of ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 62-79, 2015

SELECTING AN OPTIMAL SET OF KEYWORDS FOR SEARCH ENGINE ADVERTISING Minhoe Hur1, Songwon Han1, Hongtae Kim1, and Sungzoon Cho1,* 1

Department of Industrial Engineering Seoul National University, Seoul, Korea *Corresponding author’s e-mail: [email protected] Online advertisers who want their website to be shown in the web search pages need to bid for relevant keywords. Selecting such keywords in advertising is challenging because they need to find relevant keywords of different click volumes and costs. Recent works focused on merely generating a list of words by using semantic or statistical methodologies. However, limited previous studies do not guarantee that those keywords will be used by customers and subsequently provide large traffic volume with lower costs. In this study, we propose a novel approach of generating relevant keywords by combining search log mining and proximity-based approach. Subsequently the optimal set of keywords with a higher volume while minimizing costs was determined. Experiment results show that our method generate an optimal set of keywords that are not only accurate, but also attract more click volume with less cost. Keywords: search engine advertising; ad keywords; query logs; knapsack problem; genetic algorithm (Received on November 30, 2013; Accepted on December 29, 2014) 1. INTRODUCTION Search engine advertising is a widely used business model in the online search engine system (Chen et al., 2008, Shih et al., 2013). In this model, advertisers who want their ads to be displayed in the search results page bid on keywords that are related to the context of ads (Chen Y. et al., 2008). The ads can be displayed when the corresponding keywords are searched and their bid prices are higher than the minimum threshold (Chen et al., 2008). It is demonstrated that this business model offers a much better return on investment for advertisers, because those ads are presented to the target users who consciously made search queries using relevant keywords (Szymanski et al., 2006). Figure 1 shows the example of search engine advertising where advertisements are displayed on the result page followed by a query. To bid on keywords, advertisers need to choose which keywords would be associated by considering their ads that will be displayed (Ravi et al., 2010). In general, there are three criteria widely known that apply to good keywords. First, advertisers need to select relevant keywords that relate to their advertisement closely so that many potential customers would query those keywords to find their product or services (Kim et al., 2012). It is the most important step for reducing the gap between keywords selected by advertisers and their potential customers (Oritz-Cordova and Jansen, 2012). Secondly, choosing keywords that attract larger volume of clicks toward their advertisements among relevant keywords will be more desirable (Ravi et al., 2010). As keywords have their own click volume in the search engine, selecting them to increase the number of clicks on their ads as possible is one of the critical elements in search engine marketing. Finally, when comparing a group of keywords that are relevant and popular, identifying and selecting keywords that are cheaper than others will be also desirable to implement, more efficient and an effective marketing campaign with limited budgets. However, selecting keywords manually by considering such criteria is a challenging and time-consuming task for advertisers (Abhisher and Hosanagar, 2007). For one, it is difficult to determine which keywords are relevant to the target ads. Though advertisers generally have a good understanding over their ads, their desire is to select keywords that would not only represent their ads well but also be used by potential customers who would ultimately be interested in the products or services they offer. Moreover keywords have volatile click volumes and cost-per-click influenced by user search behavior in search engine for a long time. Therefore it is not easy to grow influx of customers into their websites while reducing costs at once. To overcome the raised problems, many studies have been proposed and they can be divided into two categories: (1) Generating related keywords by developing certain automatic methods for generating related keywords so that advertisers would find suitable keywords more easily and (2) Selecting an optimal set of keywords to maximize the objective values such as click volume or ad effects with budget constraints. Though such efforts work well in their own experiments, they have several limitations to be widely applied in real problems. First, some studies have no guarantee that the keywords would actually be queried by users. Generated keywords should be familiar to not only advertisers but also potential customers so ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 80-92, 2015

A STUDY ON THE EFFECT OF IRRADIATION ANGLE OF LIGHT ON DEFECT DETECTION IN VISUAL INSPECTION Ryosuke Nakajima1,*, Keisuke Shida2, and Toshiyuki Matsumoto1 1

Department of Industrial and Engineering Aoyama Gakuin University Kanagawa, Japan * Corresponding author’s e-mail: [email protected] 2

Department of Administration Engineering Keio University Kanagawa, Japan

This study focuses on the difference in the visibility of defects according to the irradiation angle of the light in visual inspection using fluorescent light, and also considers the relationship between the irradiation angle and the defect detection. In the experiment, the irradiation angle of light is considered as the experimental factors. The visibility of defects that are different according to the irradiation angle of the light are reproduced using a tablet PC, and the effect of inspection movement on the defect detection is evaluated. As the result, it is observed that the inspection oversights occurs by the irradiation angle of light. Also, it is observed that the angle formed by the visual line and the inspection surface becomes not perpendicular, the defects detection also becomes more difficult. Based on the above observation, new inspection method is proposed instead of the conventional inspection method. Keywords: visual inspection, peripheral vision, irradiation angle of light, inspection movement (Received on November 30, 2013; Accepted on October 20, 2014) 1. INTRODUCTION In order to prevent defective products from being overlooked, product inspection has been given as much attention as processing and assembling in the manufacturing industries. There are two types of inspections, functional inspection and appearance inspection. In functional inspection, the effectiveness of the products are inspected, whereas in appearance inspection, small visual defects like scratches, stains, surface dents and unevenness of the coating color are inspected. Advancements have been made in functional inspection automation because it is easy to determine whether a product is working (Hashimoto et al., 2009). On the other hand, in appearance inspection, it is not easy to establish standards to determine whether a product is defective, because there are many types of defects. In addition, the categorization of a product as non-defective or defective is affected by the size and depth of the defect. Moreover, some products have recently become more detailed and smaller and the type of production has shifted to high-mix, low-volume production. Thus, it is difficult to develop technologies that can discover small defects and create algorithms that identify different types of defects with high precision. Therefore, appearance inspection depends on visual inspection using human senses (Kitagawa, 2001) (Kubo et al., 2009) (Chang et al., 2009). It is common in visual inspection to overlook the defects on defective products. This problem must be solved in manufacturing industries. Generally, visual inspection is performed under a fluorescent light, and the inspectors check for various defects by irradiating the light on the inspection surface. The defects that are frequently overlooked have a common features, including a difference in the visibility of the defects according to the irradiation angle of the light (Hirose et al., 2003) (Morita et al., 2013). Furthermore, the irradiation angle of the light that allows a defect to be visible differs with the condition and type of defect. Therefore, it is necessary to change the irradiation angle of the light by moving the product in order to detect various defects. Moreover, the inspection movements of the inspector should change according to the irradiation angle, since the visibility of a defect is determined by the virtual angle between the irradiation angle of the light and the inspection surface. Although it is clear that the light should be installed in the appropriate position, the effect of the relation between the irradiation angle of the light and the inspection movement on defect detection has not been clarified, and no one has determined the appropriate position for the light to be installed. Therefore, rather than being installed in a consistent position, the light is installed at either the upper front or upper rear of the object to be inspected.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 93-101, 2015

HEURISTIC RULES BASED ON A PROBABILISTIC MODEL AND A GENETIC ALGORITHM FOR RELOCATING INBOUND CONTAINERS WITH UNCERTAIN PICKUP TIMES Xun Tong1, Youn Ju Woo2, Dong-Won Jang2, Kap Hwan Kim2,* 1

Department of Logistics and Maritime Studies The Hong Kong Polytechnic University Hung Hom, Hong Kong 2

Department of Industrial Engineering Pusan National University Busan, Korea *Corresponding author’s e-mail: [email protected] Because dwell times of inbound containers are uncertain and trucks request containers in a random order, there are many rehandling operations for containers on the top of the pickup containers. By analyzing dwell time data of various groups of inbound containers, it is possible to derive a probability distribution of each group of containers. Assuming that dwell times of each group of inbound containers follow a specific probability distribution, this paper discusses how to determine the locations for rehandled inbound containers during the pickup process. The aim of this study was to minimize the total expected number of rehandling steps for retrieving all the inbound containers from a bay. Two heuristic rules were suggested: a heuristic rule obtained from a genetic algorithm, and a heuristic rule considering the confirmed and potential rehandlings based on statistical models. A simulation study was performed to compare the performance of the two heuristic rules. Keywords: container terminal; relocation; simulation; statistics; storage location (Received on December 01, 2013; Accepted on August 10, 2014) 1. INTRODUCTION Efficient operation of container yards is an important issue for the operation of container terminals (Ma and Kim, 2012; Jeong et al., 2012). One of major operational inefficiencies in container terminals comes from rehandling operations for inbound containers. Inbound containers may be picked up after discharging only if required administrative procedures including customs clearance are finished. But, the pickup time of a container from a port container terminal is determined by the corresponding consignee or the shipping liner considering various factors such as delivery request for the container from the consignee, the storage charge for the container in the terminal, and the free-of-charge period. However, from the viewpoint of the terminal operator, the pickup time of an inbound container is uncertain. Data on inbound containers were collected from a container terminal in Busan, which has the 1,050m quay, 11 quay cranes, 30 rubber tiered gantry cranes (RTGCs), and the total area of 446,250m2. The terminal handled 260,761 inbound containers during 2012. The average duration of stay of an inbound container at the terminal was 5.7 days. Figure 1 illustrates the average dwell times of inbound containers picked up by different groups of trucking companies, which were obtained from the data. Ryu (1998) reported the results of time study for various operations by RTGCs. According to the study, the average cycle time for a pickup operation, which is performed by an RTGC in the yard for transferring an inbound container to a road truck, was 84 seconds. The average cycle time for a rehandling operation by an RTGC within the same bay was 74 seconds. There are 20~40 bays in a block. An RTGC can access all the bays in a block or even bays in neighboring blocks. But, an RTGC holding a container does not usually move from one bay to another and so this study focused on the rehandling operation within one bay. Because of uncertainty of the dwell time (Kim and Kim, 2010), which is the duration of stay of a container at the yard, the rehandling is a serious problem during the pickup operation of inbound containers. Thus, in studies of container terminals, it is important to minimize the total expected number of relocations during the pickup process. Instead of assuming that the pickup order of containers is completely unknown, when some attributes of containers are analyzed, there is a possibility to reduce the number of relocations by utilizing the results of the analysis. Figure 1 illustrates that the average dwell times of inbound containers, which are picked up by trucks from different groups of companies, are significantly different from each other. This figure shows that by analyzing data on pickup times and various information which may be useful for reducing the number of rehandles, can be derived. Voyages of vessels, vessel carriers, and shippers may be attributes to be used for the ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 102-116, 2015

ADAPTIVITY OF COMPLEX NETWORK TOPOLOGIES FOR DESIGNING RESILIENT SUPPLY CHAIN NETWORKS Sonia Irshad Mari1, Young Hae Lee1,*, Muhammad Saad Memon1, Young Soo Park2, Minsun Kim2 1

Department of Industrial and Management Engineering Hanyang University Ansan, Gyoenggi-do, Korea *Corresponding Author’s email: [email protected] 2

Korea National Industrial Convergence Center Korea Institute of Industrial Technology, Korea

Supply chain systems are becoming more complex and dynamic as a result of globalization and the development of information technology. This complexity is characterized by an overwhelming number of relations and their interdependencies, resulting in highly nonlinear and complex dynamic behaviors. Supply chain networks grow and selforganize through complex interactions between their structure and function. The complexity of supply-chain networks creates unavoidable difficulty in prediction making it difficult to manage and control them using a linearized set of models. The aim of this article is to design resilient supply chain network from the perspective of complex network topologies. In this paper, various resilience metrics for supply chains are developed based on a complex network theory, then a resilient supply chain growth algorithm is also developed for designing a resilient supply chain network. An agent-based simulation analysis is carried out to test the developed model based on the resilience metrics. The results of the proposed resilient supply chain growth algorithm are compared with major complex network models. A simulation result shows that a supply chain network can be designed based on complex network theory, especially as a scale-free network. It is also concluded that the proposed model is more suitable than general complex network models for the design of a resilient supply chain network. Keywords: supply chain network, resilient supply chain, disruption, complex network, agent-based simulation (Received on December 1, 2013; Accepted on January 02, 2015) 1. INTRODUCTION The development of information technology and increasing globalization make supply chain systems more dynamic and complex. Today’s supply chain represents a complex network of interrelated entities, which includes many suppliers, manufacturers, retailers, and customers. The concept of considering the supply chain as a supply network has been suggested by many researchers (Surana et al., 2005). It has also been argued that the concepts of complex systems, particularly complex networks, should be incorporated into the design and analysis of supply chains (Choi et al., 2001; Pathak et al., 2007). A supply chain is a complex network with an overwhelming number of interactions and interdependencies among the different entities, processes, and resources. A supply chain network is highly nonlinear, shows complex multi-scale behavior, has a structure spanning several scales, and evolves and self-organizes through a complex interplay of its structure and function. However, the sheer complexity of supply-chain networks, with its inevitable lack of prediction, makes it difficult to manage and control them using the assumptions underlying a linearized set of models (Surana et al., 2005). The concept of the supply chain as a logistics systems has therefore changed from “linear structures” to “complex systems” (Wycisk et al., 2008). Thus, this new supply network concept is more complex than a simple supply chain concept. Supply networks are comprised of the mess and complexity of networks including reverse loops, two-way exchanges, and lateral links. They contain a comprehensive, strategic view of resource management, acquisition, development, and transformation. Recently many researchers work on developing resilient supply chain networks such as (Bhattacharya et al., 2012; Klibi et al., 2012; Kristianto et al., 2014; Zeballosa et al., 2012). Generally, supply networks exhibit complex dynamic behaviors and are highly nonlinear. They grow and selforganize with the help of complex connections between their structure and function. Because of this complexity, it is very difficult to control and manage a supply network. Due to these complexities, supply network requires robustness to cope with disruption risk and they should also be resilient enough to bounce back to its original state after disruption risks (Christopher et al., 2004). Furthermore, the instability in today’s business organizations and changing market environments requires a supply network to be highly agile, dynamic, re-configurable, adaptive, and scalable that should effectively and efficiently respond to satisfy demands. Many researchers have investigated supply networks by various static approaches such as control theory, programming method, and queuing theory. For example, Kristianto et al. (2014) proposed resilient supply chain model by optimizing inventory and transportation routes. Klibi et al. (2012) ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 117-125, 2015

OPTIMAL MAINTENANCE OPERATIONS USING A RFID-BASED MONITORING SYSTEM Sangjun Park1, Ki-sung Hong2, Chulung Lee3,* 1

Graduate School of Information Management and Security Korea University Seoul, Korea 2

Graduate School of Management of Technology Korea University Seoul, Korea

3

School of Industrial Management Engineering and Graduate School of Management of Technology Korea University Seoul, Korea *Corresponding author’s e-mail: [email protected]

A high-technology manufacturing operation requires extremely low levels of raw material shortage due to its critical manufacturing line down recovering cost. It is important to determine the replacement time of a raw material against any line down risk. We propose an RFID monitoring and investment decision system in the context of semiconductor raw material maintenance operation. This paper provides the framework of the RFID monitoring system, the mathematical model to calculate the optimal replenishment time, and the simulation model for the RFID investment decision under different risk attitude with an aggressive new supply notion of “Make to Consume.” The simulation result presents that the frequency of replenishment increases and the value of the RFID monitoring system increases as the manufacturer’s risk factor that reflects the degree of risk aversion reduction. Keywords: rfid; maintenance operation; value of information; risk reverse attitude (Received on December 1, 2013; Accepted on January 10, 2015) 1. INTRODUCTION Improvements in modern information technology have been applied to diverse industries (Emigh 1999). In spite of recent progress, most concerns of enterprises still focus on their daily safety stock (SS) operations management. One of the key purposes of keeping an SS is to have an immediate supply into a manufacturing line to prevent any risk of sales loss or manufacturing line down. However, the traditional SS program based on “Make to Stock” (MTS) often faces a shortage and an overage issue in practice for various reasons, such as a fluctuating order, incorrectly estimated demand information, and a lead time that causes a bullwhip effect (Lee et al. 1997, Kelle and Milne 1999). A high level of SS increases an inventory holding cost, while a low level of SS increases the possibility of a supply shortage and a delivery expedition cost. For this reason, diverse sophisticated supply chain programs have been introduced to decrease the bullwhip effect and the inventory level. The Vender Managed Inventory (VMI) program has been introduced as one supply chain initiative (Forrester, 1958, Cachon and Zipkin 1999). As such, the VMI reduces or even removes the customer SS at a manufacturing site through sharing customer (manufacturer)’s real-time stock information with a vendor. However, it still relies heavily on the accuracy of demand forecasts. In particular, a vender should take additional supplying liabilities and inventory holding costs for a certain inventory level by a VMI agreement compared to a traditional Order to Make (OTM) model based on a firm order. This means that venders have to keep additional buffer stocks in their warehouse for timely VMI replenishment in addition to the stored VMI volume at customer manufacturing sites, considering a production and replenishment lead time. Also, the customer should take the liability with respect to consuming a certain level of inventory and risks of keeping dead stocks by the VMI agreement when customers and venders improperly set the SS quantity with incorrect sales forecasting information. In particular, high-technology industries, such as the semiconductor industry, are characterized as having a short product life cycle and fast market changes. Thus, the overage and consumption liability could be a critical burden and risk for both venders and customers. For this reason, there have been a number of studies focusing on improving supply accuracy. The use of Radio Frequency Identification (RFID) is a recent systematic approach that has contributed to the significant growth in sharing ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 126-133, 2015

OPTIMAL NUMBER OF WEB SERVER RESOURCES FOR JOB APPLICATIONS Xufeng Zhao1, Syouji Nakamura2,*, and Toshio Nakagawa3 1

Department of Mechanical and Industrial Engineering Qatar University Doha, Qatar 2

Department of Life Management Kinjo Gakuin University Nagoya, Japan *Corresponding author’s e-mail: [email protected] 3

Department of Business Administration Aichi Institute of Technology Toyota, Japan

The main purpose of this paper is to propose optimization problems in which how many number N of web servers should be provided for net jobs with random process times. We consider the first case when a single job with random time S is processed and take up the second case when number n of jobs with successive times are processed. The number n may not be a constant value that could be predefined from the practical point, so that we modify the model in the second case by supposing n to be a random variable. Next, we introduce shortage and excess costs into models to consider both costs suffered before and after failures of server system. We obtain the total expected costs for each model and optimize them analytically. When physical server failure time and job process time are exponentially distributed, optimal numbers that minimize the expected costs are computed numerically. Keywords: web server; random process; multi-jobs; system failure; shortage cost. (Received on December 1, 2013; Accepted on September 15, 2014) 1. INTRODUCTION The web server system is one kind of net service forms in which computers process jobs without considering their physical constitution of computations. This is of great importance in net services due to the merit of efficiency and flexibility. For example, when increased demand in data center is required, and its facilities and resources have approached to the up limit, this web server system can assign all available computing resources by using a flexible technique. So that resources could be shared with multi-users and accessed by authorized devices through nets. Queuing theory (Sundarapandian, 2009) is one study of waiting lines, which is used for predicting queue lengths and waiting times. The queuing models have been widely applied in decision-makings on resources that should be provided, e.g., sequencing jobs that are processed on a single machine (Sarin et al., 1991). However, using the queuing models contains too many algorithms which are time-consuming for the load of the systems, and in general, it would be difficult to predict exactly the process times (Chen and Nakagawa, 2012, 2013) for jobs. Further, most models have paid little attention to failures and reliabilities (Nakagawa, 2008; Lin, 2013) of web server systems in operations. Many studies have addressed the problem of downtime cost after system failure (Nakagawa, 2008), which may be considered to arise from carelessly scheduled plans. By comparing failure time of provided servers with required process time, we pay attention for another case when process times are too far in advance of failure times, which involves a waste of resources, as more jobs might be completed. So that we will introduce shortage and excess costs into models by considering both costs suffered before and after server failures. From such viewpoints, this paper proposes optimization problems in which how many number of web server resources should be provided for net job computations with random process times. That is, we suppose that a web server system with N (N=1,2…) servers are available for random job processes, where N could be optimized to minimize the total expected cost ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 21(6), 134-146, 2015

U-SHAPED ASSEMBLY LINE BALANCING WITH TEMPORARY WORKERS Koichi Nakade1,*, Akiyasu Ito2 and Syed Mithun Ali2 1

Department of Civil Engineering and Systems Management Nagoya Institute of Technology Gokiso-cho, Showa-ku Nagoya, JAPAN 466-8555 *Corresponding author’s e-mail: [email protected]

2

Department of Civil Engineering and Systems Management Nagoya Institute of Technology Gokiso-cho, Showa-ku Nagoya, JAPAN 466-8555

U-shaped assembly lines are useful in an efficient allocation of workers to stations. In assembly lines, temporary workers are placed to correspond to the fluctuation of demand. Sets of feasible tasks for temporary workers are different from those of permanent workers. The tasks which are familiar to permanent workers also vary. For the U-shaped assembly balancing problem under these situations the optimal cycle times for a given number of temporary workers and the optimal number of workers for given cycle time are derived and compared between U-shaped line balancing and straight line balancing. We also discuss the optimal allocation for a single U-shaped line and two U-shaped lines. In several cases, in particular when high throughputs are required, it is shown numerically that the number of temporary workers in optimal allocation for two lines is less than that of optimal allocation for a single line. Keywords: u-shaped line; optimal allocation; mathematical formulation; temporary workers; permanent workers (Received on November 25, 2013; Accepted on Febraury 26, 2015) 1. INTRODUCTION Assembly line balancing is very important because balancing workload among workers leads to the reduction of labor costs and increase of throughput of finished products. Therefore theory and solving method on assembly line balancing have been developed. For example, for mixed models in a straight line, Chutima et al.(2003) have applied a fuzzy genetic algorithm for minimizing production time and Tiacci et al. (2006) have presented a genetic algorithm for assembly line balancing with parallel stations. In Villarreal and Alanis (2011) simulation is used to guide the improvement efforts on the redesign of a traditional line. In assembly line balancing, a U-shaped assembly line is effective in an allocation of workers and tasks to stations, because more types of allocations are available compared with those in straight lines, and appropriate arrangement leads to more throughput. Baybars (1986) has formulated a U-shaped line as a mixed integer program and proposed a heuristic algorithm for solving. Recently, Hazir and Dolgui (2011) have proposed a decomposition algorithm. Chiang et al. (2007) have proposed a formulation of U-shaped assembly line balancing with multiple lines, and have shown that there are the cases that multiple lines can process with a fewer stations than a single line by numerical examples. Temporary workers are sometimes placed in assembly lines, because the system can remain efficient by increasing or decreasing the number of temporary workers corresponding to the fluctuation of demand. Sets of feasible tasks for temporary workers are different from those of permanent workers. The familiar jobs among permanent workers may be also different. In this case, it is important to allocate permanent and temporary workers to stations appropriately by considering their abilities for different types of tasks. Corominas et al. (2008) have considered a straight line balancing with temporary workers. Tasks which temporary workers can process is limited and time necessary for temporary workers to finish their tasks is assumed to be longer than that for permanent workers to do those. In general, however, tasks which permanent workers can complete in standard time are different among those workers, because their skills are different. In this paper, we consider a U-shaped assembly balancing problem with a fixed number of permanent different workers and temporary workers under precedence constraints on tasks. The model is formulated as an optimization integer program for deriving the minimal cycle time for a given number of temporary workers, or deriving the minimal number of temporary workers under given cycle time, and an algorithm is proposed to derive the throughput and an optimal allocation of workers and jobs to stations for all possible numbers of temporary workers. Then we compare the optimal values between U-shaped line balancing and straight line balancing in numerical examples by using software Xpress. In addition, ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 147-158, 2015

A GAME THEORETIC APPROACH FOR THE OPTIMAL INVESTMENT DECISIONS OF GREEN INNOVATION IN A MANUFACTURER-RETAILER SUPPLY CHAIN Sha Xi1 and Chulung Lee2,* 1

Graduate School of Information Management and Security Korea University Seoul, Republic of Korea

2

School of Industrial Management Engineering and Graduate School of Management of Technology Korea University Seoul, Republic of Korea *Corresponding author’s e-mail: [email protected]

With increasing consumers’ awareness of eco-friendly products, Manufactures and Retailers are proactive to invest in green innovation. This paper analyzes a single manufacturer, single retailer supply chain where both participants are engaged in green innovation investment. Consumer demand is dependent on selling price and investment level of green innovation. We consider the effects of consumer environmental awareness, perception difficulty of green products, and degree of goods’ necessity on decision making. According to the relationship between the manufacturer and the retailer, three non-coordinated game (including Manufacturer-Stackelberg, Retailer-Stackelberg, and Vertical Nash) and one coordinated supply chain structures are proposed. The pricing and investment level of green innovation are investigated under these four supply chain structures, respectively. A Retail Fixed Markup policy is analyzed when channel members fail to achieve supply chain coordination. The effects of RFM on supply chain performance are evaluated. We numerically compare optimal solutions and profits under the coordination, the Manufacturer-Stackelberg, and the Retail Fixed Markup supply chain structure and provide managerial insights for practitioners. Keywords: green supply chain management; consumer environmental awareness; product type; game theory (Received on November 30, 2013; Accepted on February 26, 2015) 1. INTRODUCTION As the escalating deterioration of environment in past decades, Green Supply Chain Management has attracted increasing attention from entrepreneurs and researchers. Public pressure, such as consumer demand for eco-friendly products, first put companies on to the thinking of greening. Nowadays, companies are proactive to invest in green innovation and regard it as a potential competitive advantage rather than a burden. Porter (1995) explained the fundamentals of greening as a competitive strategy for business practitioners and reported green investment may increase resource productivity and save cost. People are more aware of environmental problems and willing to behave eco-friendly. According to the report of Cone communications (2013), 71% of Americans take environmental factors into consideration and 45% of consumers actively gathered environmental information about their objective products. In a meta-analysis on 83 research papers, Tully and Winer (2013) found more than 60% consumers are willing to pay a positive premium for socially responsible products and, on average, those consumers are willing to pay 17.3% more for these products. The increasing consumer demand of eco-friendly products drives companies engaging in green innovation to differentiate its product (Amacher et al., 2004; Ibanez and Grolleau, 2008, Borchardt et al., 2012). Land Rover, one of the world’s most luxurious and stylish 4x4s, has launched Ranger Rover Evoque which is regarded as the lightest, most fuel efficient Ranger Rover to meet requirements for lower CO2 emissions and fuel economy. LG has produced a water efficient washing machine which saves 50L or more per load and uses less detergent. Meanwhile, retailers are also engaged in investment of green innovation recently. Home Depot, an American home improvement products retailer, conducts business in an environmentally responsible manner. Home Depot leads in reducing greenhouse gas emissions and selecting manufacturer of eco-friendly products. For explanation of properties and functions of eco-friendly products, Home Depot also provides leaflets, product labeling, and in-store communication, which help consumers to know eco-friendly well. Most of companies decide optimal investment decisions of green innovation without considering their manufacturer’s or retailer’s decisions. With requirements of operational efficiency and environmental protection, companies have tried to improve the entire supply chains’ performance rather than a single supply chain member’s. Beamon(1999) discussed the ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 159-170, 2015

DYNAMIC PRICING WITH CUSTOMER PURCHASE POSTPONEMENT Kimitoshi Sato Graduate School of Finance, Accounting & Law Waseda University Japan *Corresponding author’s e-mail: [email protected] We consider a dynamic pricing model for a firm that sells perishable products to customers who have the potential to postpone the purchase decision to reduce their perceived risk. The firm has a competitor in the market and knows that the competitor adopts a static pricing strategy. We assume that the customer arrivals follow a stochastic differential equation with delay and establish a continuous-time model so as to maximize the expected profit. When the probability distribution of the customers’ reservation value is exponential and its parameter is constant in time, a closed-form optimal pricing policy is obtained. Then, we show the impact of the competitor's pricing policy on the optimal price sample path through a martingale approach. Moreover, we show that the purchasing postponement reduces the firm’s total expected profit. Keywords: revenue management; dynamic pricing; stochastic delay equation (Received on November 28, 2013; Accepted on February 26, 2015) 1. INTRODUCTION We consider a dynamic pricing policy of a firm that faces the problem of selling a fixed stock of products over a finite horizon in a competitive market and knows that the competitor adopts a static pricing strategy. Such a situation can be found everywhere. Examples include high-speed rail versus low-cost carriers, suite versus regular hotel rooms, national versus store brands, department versus Internet shops, etc. Since the static pricing policy provides a simple and clear price to customers, some companies (especially firms offering the high-quality product) place importance on this advantage. In this paper, we investigate how the customer behavior of delayed purchases impacts on the pricing strategy of the firm. Causes of delay in customer decision-making include the difficulty of selecting the product and perceived risk. Some nonpurchase customers will return to a shop or web site at intervals. Thus, the number of the present arrival customers is affected by some of the previous arrival customers. Pricing without considering such behavior may affect the total revenue of the firm. Recently, various authors have considered a pricing policy with strategic customer behavior in the management science literature (Levin et al. 2009, Liu and Zhang, 2013). The strategic customer behavior is that customers compare the current purchasing opportunity to potential future opportunities and decide whether to purchase immediately or to wait. These papers model customer's purchase timing so as to maximize their individual consumer surpluses. The strategic customers take future price expectations into account in their purchase decisions. Unlike previous works, we consider the number of customers to postpone purchases at an aggregate level, rather than at the individual customer level. Proportions of customers who postpone the purchase vary depending only on the time of arrival. In other words, the earlier the arrival, the more delay in purchasing the product. To take into account of such customer behavior, we model the problem as a stochastic control problem that is driven by a stochastic differential equation with delay. Larssen and Risebro (2003) and Elsanosi et al. (2001) consider the applications of the stochastic control problem with delay in harvesting problem, and consumption and portfolio optimization problems, respectively. Bauer and Rieder (2005) provide conditions that enable us to reduce the stochastic control problem with delay to the problem that is easier to solve. By using conditions, we show that our problem can be reduced to the similar model of Sato and Sawaki (2013), which does not take into account of the delay. Then, we obtain a closed-form optimal pricing policy when the probability distribution of the reservation value is exponential. Xu and Hopp (2006) apply martingale theory to investigate the trend of optimal price sample paths in a dynamic pricing model for exponential demand case. Xu and Hopp (2009) consider the dynamic pricing in continuous-time in which the customer arrivals follow a non-homogeneous Poisson process. They show that the trend of optimal price increases (decreases) when customer’s willingness-to-pay increases (decreases) in time. We also apply martingale theory to study how the competitor's pricing strategy and customers' delay behavior effect optimal price path when customer’s willingness-to-pay is constant in time.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 171-182, 2015

INTEGRATION OF SCENARIO PLANNING AND DECISION TREE ANALYSIS FOR NEW PRODUCT DEVELOPMENT: A CASE STUDY OF A SMARTPHONE PROJECT IN TAIWAN Jei-Zheng Wu1, Kuo-Sheng Lina2,*, and Chiao-Ying Wu b1 1

Department of Business Administration, Soochow University 56 Kueiyang St., Sec. 1, Taipei 100, Taiwan, R.O.C. 2 Department of Financial Management, National Defense University 70 Zhongyang N. Rd., Sec. 2, Taipei 112, Taiwan, R.O.C. *Corresponding author’s e-mail: [email protected] Although the demand for smartphones has increased rapidly, the R&D and marketing of smartphones have encountered severe competition in a dynamic environment. Most studies on new product development (NPD) have focused on the traditional net present value method and real options analysis, which lack the flexibility required to model asymmetric multistage decisions and flexible uncertain states. The aim of this study was to integrate scenario planning and decision tree analysis for NPD evaluation. Through such integration, scenarios for modeling uncertainties can be generated systematically. This study presents a case study of a Taiwanese original equipment manufacturing company for validating the proposed model. Compared to the performance of realized decisions, the proposed analysis is more robust and minimizes risk if the R&D resource allocation is appropriate. Two-way sensitivity analysis facilitates balancing the probability of R&D success with the R&D cost of an R&D project becoming profitable. Keywords: decision tree analysis; scenario planning; new product development project; influence diagram; discounted cash flow (Received on December 1, 2013; Accepted on February 26, 2015) 1. INTRODUCTION Over the past decade, the mobile phone market has exhibited a substantial increase in demand; sales have increased from a relatively small number of phones in the 1990s to 140 million today. The integration of communication, entertainment, and business functions with the availability of simple and fashionable designs has contributed to the increasing use of mobile communication products. New product development (NPD) projects for mobile phones often encounter resource or budgetary limitations, resulting in limited choices of project investments. Moreover, NPD involves high risk and uncertainties. When new product investments are financially evaluated, the most common questions are whether projects are worth investing in and how all uncertainties can be factored into the evaluation, including the uncertainty in the temporal variation of the product value after launch. The net present value (NPV) method, also known as the discounted cash flow (DCF) method, is commonly used for budgeting capital and evaluating investment in R&D projects. The traditional NPV method involves applying the risk-free rate and risk-adjusted discount rate for discounting future expected cash flows, including financial benefits and expenditure, to derive the NPV (Brandão and Dyer 2005). A project is considered investment worthy only if the NPV is positive. Although the NPV method is simple and intuitive, its applications are limited because of the unrealistic assumptions of (1) reversible investment and (2) nondeferrable decisions. According to the reversible investment assumption, an investment can be undone and incurred expenditure can be recovered (Dixit and Pindyck 1995). Furthermore, the nondeferrable decision assumption requires the R&D investment decision to be made immediately. Because it entails using only one scenario (the so-called now-or-never scenario) for decision-making, the NPV method evaluates one-stage decisions without considering contingencies or changes that reflect future uncertainties (Trigeorgis and Mason 1987). In practice, information on the reversibility, uncertainty, and timing of decisions is critical for managers in making R&D investment decisions at the strategic level (Dixit and Pindyck 1995). An R&D project entails at least four stages: (1) initialization, (2) outcome, (3) commercialization, and (4) market outcome (Faulkner 1996). In responding to future uncertainties, managers require flexibility to adjust their actions by using “real options,” such as deferring decisions, altering the operation scale, abandoning or switching the project, focusing on growth, and engaging in multiple interactions (Trigeorgis 1993). Real option analysis is complementary to the NPV method, in that the total project value can be formulated as the sum of the NPV, adjusted option value, and abandonment value (van Putten and MacMillan 2004). Considering the real option of exercising the right to manage real assets without obligation to proceed with actions when anticipating uncertainties, R&D project investment is based on a multistage, sequential decision-making process (Ford and Sobek 2005). ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(1), 183-194, 2015

 

TRADE-INS STRATEGY FOR A DURABLE GOODS FIRM FACING STRATEGIC CONSUMERS Jen-Ming Chen1,* and Yu-Ting Hsu2 1,2

Department of Industrial Management

National Central University 300 Jhongda Road, Jhongli City, Taoyuan County, Taiwan, 32001 *Corresponding author’s e-mail: [email protected] Trade-ins rebate from the manufacturer to the consumers is a commonly used device by a durable goods firm to price discriminate between new and replacement buyers. It creates segment effect by offering different prices to different groups of customers. This study deals with such an effect by considering three trade-ins policies facing the firm, i.e., no trade-ins, trade-ins to replacement consumers with high quality used goods, and trade-ins to all replacement consumers. This study determines the optimal pricing and/or trade-in rebate, and examines the strategic choice among the three options facing the firm. We develop analytic models that incorporate key features of durable goods into model formulation, namely the deterioration rate and the quality variation of the used goods. Our research findings include: the strategic choice among the three options depends critically on the two features and the price of new goods, and the trade-ins-to-all policy outperforms the others when the deterioration rate is high and/or new goods price is high. Keyword: trade-Ins; rebate; Deterioration; Utility Assessment; Stationary Equilibrium (Received on December 3, 2013; Accepted on February 26, 2015)  1. INTRODUCTION An original equipment manufacturer often faces two distinct types of consumers in the market: replacement buyers and new buyers. Especially in a durable good market, the replacement purchases represent a significant portion of the total sales. In highly saturated markets like refrigerators and electric water heaters, the percentage of replacement purchases is between 60% and 80% of the annual sales in the United States (Fernandez, 2001). In the automobile industry, approximately half of all new car sales involve a trade-in (Zhu, Chen, & Dasgupta, 2008; Kim et al., 2011). To increase sales and purchasing frequency by the customers, the firm usually adopts a price discrimination approach by offering the replacement buyers a special trade-in rebate that is referred to the firm’s decision of accepting a used good as partial payment for a new good. The replacement customers will pay less for the new goods by redeemed rebates. In the cellphone industry, Apple offers replacement customers a trade-in rebate up to $345 for an iPhone 4S and up to $356 for an iPhone 5 (www.apple.com). Such a manufacturer-to-consumer rebate stimulates new goods sales. This study deals with such a prevalent practice in durable goods markets. We propose analytic models for decisionmaking of optimal trade-in rebates facing the durable goods producer, especially when the replacement buyers act strategically, that is, their replacement decision depends on the quality condition of the goods after a certain period of use. We analyze and compare three benchmark scenarios, that is the no trade-ins, the trade-ins to consumers with high quality used goods (denoted by trade-ins-to-high), and the trade-ins to all consumers with high and low quality used goods (denoted by trade-ins-to-all). This study especially focuses on investigating the impacts of the two trade-ins policies on the behaviors and actions the buyers may take, as well as the potential benefit the firm may gain among the three options. Our research findings suggest that the strategic choice on trade-ins policies facing the firm depends critically on the deterioration rate (or durability in a reversed measure), quality variation of the used goods, and the new goods price. We also show that as the deterioration or quality variation increases, the magnitude of trade-in rebates increases. There are mainly two research streams that deal with trade-in rebates in durable goods markets: (i) models from economics and marketing literature and (ii) models from operations literature. We provide reviews of both streams. Waldman (2003) identified some critical issues facing the durable goods producers, including durability choice and information asymmetric problem. This study is related to the former one but does not deal with the second that was one of the major research concerns in Rao, Narasimhan, and John (2009). They showed that trade-in programs mitigate the lemon problem or equivalently information asymmetric problem in markets with adverse selection, and hence increase the firm’s profit. ISSN 1943-670X

   

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 195-212, 2015

Improving In-plant Logistics: A Case Study of a Washing Machine Manufacturing Facility Cagdas Ucar1 and Tuncay Bayrak2,* 1

Yildiz Technical University Department of Industrial Engineering Istanbul, Turkey 2

Department of Business Information Systems Western New England University Springfield, MA, 01119, USA *Corresponding Author’s E-mail:[email protected] This study presents a case study on the enhancement of in-plant logistics at a discrete manufacturing plant using lean manufacturing/logistics principles. Two independent application scenarios are presented. In the first application, we improve the operation of a supermarket (small internal warehouse) from the ergonomics point of view by (1) placing heavy boxes on waist-level shelves, and (2) applying rolling racks/trolleys to release the physical load on the workers. In the second application, the logistic processes related to a new supermarket are fundamentally re-designed. Key Words: In-plant logistics, supermarket, milkrun, ergonomics, fatigue, just-in- time production. (Received on September 20, 2013; Accepted on Septemeber 13, 2014) 1. INTRODUCTION Logistics activities, regardless of whether it is in manufacturing or service business, have become an important business function as they are seen to contribute to the competitiveness of the enterprise. In such a competitive environment, logistics activities are one of the most important factors for companies in delivering products and services in a timely and competitive manner. In other words, the logistics service quality emerges as an important element of being able to compete. Logistics can be seen as in-plant logistics and out-of-plant logistics. In-plant logistics or internal logistics covers the activities between the arrival of raw materials and the full output of the product. Out-of plant logistics or external logistics covers the remaining activities. In recent years, the importance of in-plant logistics has increased as it is of great importance for running production smoothly. In-plant logistics implies the co-ordination of activities within the plant. One would agree that the elements of the in-plant logistics need to be integrated with the external logistics. For manufacturers, managing the in-plant logistics is as important as managing the external logistics to improve the efficiency of production activities. Running in-plant logistics in the best way is of great importance for businesses that adopted just-in-time and lean manufacturing philosophies to continue functioning without problems. This study reports on the experiences of redesigning in-plant logistics operations of a washing machine manufacturing facility. How to improve in-plant logistics, within the framework of just-in-time production and lean manufacturing philosophies, is investigated from different perspectives such as ergonomics, time spent, and distance traveled. Two real-life examples are presented in terms of how in-plant logistics activities can be improved using milkrun and supermarket approaches. The first application deals with logistics activities in terms of ergonomics. In the second application, problems with internal logistic activities are identified, and solutions are provided to minimize the time spent, and distance traveled by the employees. 2. LITERATURE REVIEW Logistics management can be defined as that “part of supply chain management that plans, implements, and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption in order to meet customers' requirements” (CSCMP, 2012). Kample et al., (2011) suggest logistics is both a fundamental business activity and the underlying phenomenon that drives most other business processes. While in-plant logistics plays a vital role in achieving the ideal balance of process efficiency and labor productivity, unoptimized in-plant logistics may present a considerable challenge for companies in all sectors of consumer goods and result in poor operation management, human error, and some other problems. Thus, optimized inplant logistics is a prerequisite for the economic operation of the factory. As pointed out by Jiang (2005), in-plant ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2) , 213-222, 2015

Toll Fraud Detection of Voip Services via an Ensemble of Novelty Detection Algorithms Pilsung Kang1, Kyungil Kim2, and Namwook Cho2,* 1

2

School of Industrial Management Engineering Korea University Seoul, Korea

Department of Industrial & Information Systems Engineering Seoul National University of Science and Technology Seoul, Korea * Corresponding author’s e-mail: [email protected]

Communications fraud has been dramatically increasing with the development of communication technologies and the increasing use of global communications, resulting in substantial losses to telecommunication industry. Due to the widespread deployment of voice over internet protocol (VoIP), the fraud of VoIP has been one of major concerns of the communications industry. In this paper, we develop toll fraud detection systems based on an ensemble of novelty detection algorithms using call detail records (CDRs). Initially, based on actual CDRs collected from a Korean VoIP service provider for a month, candidate explanatory variables are created using historical fraud patterns. Then, a total of five novelty detection algorithms are trained for each week to identify toll frauds during the following week. Subsequently, fraud detection performance improvements are attempted by selecting significant explanatory variables using genetic algorithm (GA) and constructing an ensemble of novelty detection models. Experimental results show that the proposed framework is practically effective in that most of the toll frauds can be detected with high recall and precision rates. It is also found that the variable selection using GA enables us to build not only more accurate but also more efficient fraud detection models. Finally, an ensemble of novelty detection models further boosts the fraud detection ability especially when the fraud rate is relatively low. Keywords: toll fraud detection; novelty detection; genetic algorithm (GA); ensemble; VoIP service; call detail records (CDRs). (Received on November 29, 2013; Accepted on July 09, 2014) 1. INTRODUCTION Communications fraud has been dramatically increasing with the development of communication technologies and the increasing use of global communications, resulting in substantial losses to telecommunication industry (Kou, 2004). Moreover, due to the widespread deployment of the Voice over Internet Protocol (VoIP), the fraud of VoIP has been one of major concerns of the communications industry. VoIP is more vulnerable to fraud attacks so its potential loss is greater than traditional telecommunication technologies. According to the survey conducted by Communications Fraud Control Association (CFCA, 2009), global fraud losses in 2009 are estimated to be in the range of $72 - $80 billion (USD), which is up 34% from 2005. The top two fraud loss categories, which constitute nearly 50 percent of the total loss, can be considered as toll fraud. Toll fraud is defined as an unauthorized use of one’s telecommunications system by an unauthorized party (Avaya, 2010), which often results in substantial additional charges for telecommunications services. Figure 1 shows a typical toll fraud pattern. While normal traffic is activated from the normal user groups and transmitted through a VoIP service provider and an internet telephony service provider (ITSP), toll fraud attacks result from an illegal use of unauthorized subscriber information and/or the compromise of vulnerable telecommunication systems such as PBX and voicemail systems. In telecommunication industry, most fraud analysis applications have been relying on rule-based systems (Rosset, 1999). In the rule-based systems, fraud patterns are pre-defined by a set of multiple conditions, and an alert is raised whenever any of the rules is met. Rosset et al. (1999) suggested a rule-discovery framework for fraud detection in a traditional telecommunications environment. Ruiz-Agundez et al. (2010) proposed a fraud detection framework for VoIP services consisting of a rule engine built over a prior knowledge base. However, relying on the knowledge of domain experts, rule-based approaches can hardly provide an early warning effectively; they are vulnerable to unknown and abnormal fraud patterns (Kim, 2013). ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 223-242, 2015

A Multi Depot Simultaneous Pickup and Delivery Problem with Balanced Allocation of Routes to Drivers Morteza Koulaeian1, Hany Seidgar1, Morteza Kiani1 and Hamed Fazlollahtabar2,* 1 Department of Industrial Engineering Mazandaran University of Science and Technology Babol, Iran 2

Faculty of Management and Technology Mazandaran University of Science and Technology Babol, Iran *Corresponding author’s e-mail: [email protected] In this paper, a new mathematical model is developed for a multi-depot vehicle routing problem with simultaneous pickup and delivery. A non-homogenous fleet of vehicles and a number of drivers with different levels of capabilities are employed to service customers with pickup and delivery demands. The capability of drivers is considered to have a balanced distribution of travels. The objective is to minimize the total cost of routing, penalties for overworking of drivers and fix costs of drivers’ employment. Due to the problem’s NP-hard nature, two meta-heuristic approaches based on Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA) are employed to solve the generated problems. The parameter tuning is conducted by Taguchi experimental design method. The obtained results show the high performance of the proposed ICA in the quality of the solutions and computational time. Keywords: vehicle routing problem (VRP); multi depot simultaneously pickup and delivery; imperialist competitive algorithm (ICA). (Received on January 09, 2014; Accepted on October 19, 2014) 1. INTRODUCTION Pickup and Delivery problem (PDP) is one of the main classes of the Vehicle Routing problem (VRP) in which a set of routes is designed in order to meet customers’ pickup and delivery demands. In Simultaneous Pickup and Delivery problem (SPDP) a fleet of vehicles originating from a distribution center should deliver some goods to customers and at the same time collect back their excess stuff. This problem arises especially in the reverse logistics context where companies are increasingly faced with the task of managing the reverse flow of finished goods or raw-materials (Subramanian et al., 2010). Min (1989) was the first researcher to introduce vehicle routing problem with simultaneous pickup and delivery (VRPSPD) for minimizing the total travel time of the route by considering the vehicle capacity as the problem constraint. Dethloff (2001), and Tang and Galvano (2006) then, contributed on mathematical reformulations. Berbeglia et al., (2007) also introduced a general framework to model static pickup and delivery problems. Jin and Kachitvichyanukul (2009) generalized the three existing formulation and reformulated the VRPSPD as a direct extension of basic VRP. In solution technique areas, Moshivio (1998) studied PDP with divisible demands, in which each customer can be served by more than one vehicle, and presented greedy constructive algorithms based on tour partitioning. Salhi and Nagy (1999) proposed four insertion-based heuristics, in which partial routes are constructed for some customers in basic steps and then the remaining customers will be inserted to the existing routes. Dell 'Amico et al., (2006) presented an exact method for solving VRPSPD based on column generation, dynamic programming, and branch and price algorithm. Bianchessi and Righini (2007) proposed a number of heuristic algorithms to solve this problem approximately in a small amount of computing time. Emmanouil et al., (2009) proposed a hybrid solution approach incorporating the rationale of two well-known metaheuristics namely tabu search and guided local search. Mingyong and Erbao (2010) proposed an improved differential evolution algorithm (IDE) for a general mixed integer programming model of VRPSPD with time windows. Hsiao-Fan Wang and Ying-Yen Chen (2012) presented a co-evolution genetic algorithm with variants of the cheapest insertion method for this kind of problem. Ran Liu et al. (2013) propose a genetic algorithm based on a permutation chromosome, a split procedure and local search for VRPSPD in home health care problem. They also propose a tabu search method based on route assignment attributes of patients, an augmented cost function and route re-optimization. Tao Zhang et al., (2012) develop a new scatter search and a generic genetic algorithm approach for the stochastic travel-time VRPSPD. Goksal et al., (2013) proposed a particle swarm optimization in which a local search is performed by variable neighborhood descent algorithm for VRPSPD. The reviewed papers so far were single depot problems but there are studies considering multi-depot vehicle routing problem (MDVRP) in which there exist more than one distribution center. Here, some

International Journal of Industrial Engineering, 22(2), 243-251, 2015

A Branch-and-Price Approach for the Team Orienteering Problem with Time Windows Hyunchul Tae and Byung-In Kim* Department of Industrial and Management Engineering, Pohang University of Science of Technology (POSTECH) Pohang, Korea * Corresponding author’s e-mail: [email protected] Given a set of vertices, each of which has its own prize and time window, the team orienteering problem with time windows (TOPTW) is a problem of finding a set of vehicle routes with the maximum total prize that satisfies vehicle time limit and vertex time window constraints. Many heuristic algorithms have solved the TOPTW; to our knowledge, however, no exact algorithm that can solve this problem optimally has yet been identified. This study proposes an exact algorithm based on the branch-and-price approach to solve the TOPTW. This algorithm can find optimal solutions for many TOPTW benchmark instances. We also apply the proposed algorithm to the team orienteering problem (TOP), which is a time window constraint relaxed version of the TOPTW. Unlike the TOPTW, a couple of exact algorithms have solved the TOP. The proposed algorithm can find more number of optimal solutions to TOP benchmark instances. Keywords: team orienteering problem with time windows; branch and price; exact algorithm; column generation (Received on October 2, 2014; Accepted on February 20, 2015)

1. INTRODUCTION Given a weighted digraph , , where , , is a set of vertices and is a set of arcs between the vertices, ,…, may be visited by a set of identical vehicles ,…, that departs from the a set of customers . A vehicle ∈ collects a prize by visiting ∈ . A vehicle ∈ takes travel origin and ends at the sink time , to traverse , ∈ and service time to serve ∈ . A vehicle ∈ can visit ∈ only between its time window , and should wait until if it arrives before . The total working time of each vehicle should be less than or 0, , and a complete graph for simplicity. The team orienteering equal to the time limit . We assume that problem with time windows (TOPTW) is an issue that involves finding a set of vehicle routes with a maximum total prize that satisfies vehicle time limit and vertex time window constraints. The TOPTW can be formulated as a set partitioning problem as a route if the customers in can be visited by one vehicle. Let Φ be as [TOPTW]. We regard a subset of customers ⊆ a set of all possible routes. [TOPTW] max

(1) ∈

Subject to ,

1, ∀

⊆

(2)

∈

(3) ∈

∈ 0,1 , ∀

∈Φ

(4)

∑ ∈ ∈ Φ, where , is 1 if includes ∈ and 0 otherwise. A , represents the prize of a route binary decision variable is 1 if ∈ Φ is selected and 0 otherwise. The objective function (1) maximizes the total prize. Constraints (2) prohibit a customer from being visited more than once. Constraint (3) ensures that vehicles can be used at most. Constraints (4) restrict to be binary. ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 252-266, 2015

An Inhomogeneous Multi-Attribute Decision Making Method and Application to IT/IS Outsourcing Provider Selection Rui Qiang1 and Debiao Li2 1,2

School of Economics and Management Fuzhou University Fuzhou, China

Corresponding author’s e-mail: [email protected] Selecting a suitable outsourcing provider is one of the most critical activities in supply chain management. In this paper, a new fuzzy linear programming method is proposed to select outsourcing providers by formulating it as a fuzzy inhomogeneous multi-attribute decision making (MADM) problems with fuzzy truth degrees and incomplete weight information. In this method, the decision maker’s preferences are represented as trapezoidal fuzzy numbers (TrFNs), which obtained through pair-wise comparisons of alternatives. Based on the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the fuzzy consistency and inconsistency indices are defined by the relative closeness degrees in TrFNs. The attribute weights are estimated by solving the proposed fuzzy linear programming. And then the selection ranking is determined by the comprehensive relative closeness degree of each alternative to the FPIS. An industrial IT outsourcing provider selection example is analyzed to demonstrate the implementation process of this method. Keywords: outsourcing provider; multi-attribute decision making; production operation; fuzzy linear programming; supply chain management (Received on August 08, 2013; Accepted on January 01, 2015) 1. INTRODUCTION In the ever-increasing business competitiveness of today, outsourcing has become a main stream practice in global business operations (Cai et al., 2013). Information systems outsourcing is modeled as one-period two-party non-cooperative games to analyze the outsourcing arrangement by considering a variety of interesting characteristics, including duration, evolving technologies, difficulty to assess, and vender fees (Elitzur and Wensley,1999, Elitzur et al., 2012). Many organizations also attempt to enhance their competitiveness, reduce costs, increase their focus on internal resources and core activities, and sustain competitive advantage by Information technology/ information system (IT/IS) outsourcing (Yang and Huang, 2010). The selection of a good provider is a difficult task. Some providers that meet some selection criteria may fail in some other criteria. Therefore, selecting the outsourcing providers may be ascribed to a multi-attribute decision making (MADM) problems. Currently, some integrated decision-making methods have been proposed for solving the problems of selecting outsourcing providers. Compared to the sequential decision making based on one-dimension rules, integrated decision-making methods yield more integrative and normative solutions based on multi-attributes (Jansen et al., 2012). For example, Chou et al. (2006) developed a fuzzy multi-criteria decision model approach to evaluating IT/IS investments. Chen and Wang (2009) developed the fuzzy Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for the strategic decision of optimizing partners’ choice in IT/IS outsourcing projects. Lin et al. Combining the DEMATEL, ANP, and zero-one goal programming (ZOGP), Tsai et al. (2010) developed a MCDM approach for sourcing strategy mix decision in IT projects. From a policy-maker’s perspective, Tjader et al. (2010) researched the offshore outsourcing decision-making. (2010) proposed a novel hybrid multi-criteria decision-making (MCDM) approach for outsourcing vendor selection combining a case study for a semiconductor company in Taiwan. Chen et al. (2011) presented the fuzzy Preference Ranking Organization Method for Enrichment Evaluation (fuzzy PROMETHEE) to evaluate four potential suppliers using seven criteria and four decision makers using a realistic case study. Ho et al. (2012) integrated the quality function deployment (QFD), fuzzy set theory, and analytic hierarchy process (AHP) approach, to evaluate and select the optimal third-party logistics service providers (3PLs). Fan et al. (2012) utilized an extended DEMATEL method to identify risk factors of IT outsourcing using interdependent information. Buyukozkan and Cifci (2012) proposed a novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate green suppliers.

ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 267-276, 2015

Multi-Criteria Model For Selection of Collection System in Reverse Logistics: A Case for End of Life Electronic Products Md Rezaul Hasan Shumon1,*, Shamsuddin Ahmed2 1

Department of Industrial and Production Engineering Shahjalal University of Science and Technology Sylhet-3114, Bangladesh *Corresponding author’s e-mail: [email protected] 2

Department of Mechanical Engineering University of Malaya, Kuala Lumpur, Malaysia

The purpose of this paper is to propose a multi-criteria model for end-of-life electronic products collection system selection in a reverse supply chain. The proposed models first determines the pertinent criteria for collection system selection by conducting questionnaire survey and then uses analytic hierarchy process (AHP) rating method to evaluate the priorities of the criteria and alternatives, respectively. Finally, global weights of the criteria and evaluation score of the alternatives are combined to get the final ranking of the collection systems. The analysis result demonstrates the relative importance of the criteria for evaluating the collection methods, and a real application that shows the preference of collections system(s) to be selected. The use of this newly proposed model indicates that, decision makers can use it to determine the most appropriate collection system(s) from available options in the considering territory. Furthermore, it would be able to make the decision process more systematic and reduce the considerable efforts needed by using the criteria weights created in this model. Keywords: reverse logistics; multi-criteria analysis; end-of-life electronic products; analytical hierarchy process; decision making (Received on January 3, 2014; Accepted on October 05, 2014) 1. INTRODUCTION Electronic waste (e-waste) management has gained a significant attention to researchers and policy makers around the world as their ‘through-away’ impact is hazardous to the physical environment. The advancing technology and shortened product life cycle makes e-waste one of the fastest growing waste streams, creating significant risks to human health and the environment (Yeh & Xu, 2013). Use of the reverse supply chain approach is one way of minimizing the environmental impact of e-wastes entitled as end-of-life (EOL) electronic products (Quariguasi Frota Neto, Walther, Bloemhof, van Nunen, & Spengler, 2009). Reverse supply chain is a process by which a manufacturer systematically accepts the previously shipped products or parts from the point of consumption for possible reuse, remanufacturing, recycling, or disposal (Tsai & Hung, 2009). This process provides with advantage of recycling of material resources, development of newer technologies and creation of income-oriented job opportunities (Shumon, 2011). Initially, the significance of this research was based on a problem confronting in Malaysia, a Southeast Asian country, where companies and organizations are in doubt which system they should use for e-waste collection. However, this problem is faced by other countries around the world as well. Collection of e-wastes is the first activity to trigger the reverse supply chain as part of product recovery activities. In this regard, several approaches have been applied by different countries like individual manufacturer’s buy-back program, municipality’s collection program, and NGO and government initiatives (Chung, Lau, & Zhang, 2011; Qu, Zhu, Sarkis, Geng, & Zhong, 2013). It is understandable that no single collection system can ensure the maximum collection of e-wastes, because it largely depends on the geographical, social and economic conditions of the country under consideration. Some systems are well established in developed countries but may not be economically feasible in other developing countries. Some systems are economically feasible but are not well accepted by stakeholders. This resulted use of inappropriate methods or systems, which ultimately lead to a lower collection rate and higher investment or operating cost. Such system(s) cannot meet the financial objectives with respect to the investment made. Thus, there is a need for systematic approach of selecting appropriate collection system(s) by identifying and prioritizing the pertinent criteria and evaluating the tradeoffs between strategic, economic, operational and social performance aspects. The model presented by this research would be a useful decision making aid for the companies and organizations in any territory to rank and select the effective and suitable method(s) for their concerned areas. Hao, Jinhui, Xuefeng, and Xiaohua (2007) investigated on the collection method of domestic e-waste in urban China by applying case study methods. They analyzed the four alternative collection modes currently exist in Beijing and proposed a few other modes. The existing modes are door to door collection, Take-back in related business(second hand market), Collection in recycling spot, Collection for donation and the proposed modes are i) government to formal recycler ii) enterprise to formal recycler iii) collectors-formal recyclers. The use of multi-criteria decision analysis ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 277- 291, 2015

A Fuzzy Expert System for Supporting Returned Products Strategies H.Hosseininasab1, M.Dehghanbaghi2,* 1,2

Department of Industrial Engineering Yazd University Yazd, Iran *Corresponding author’s e-mail: [email protected] A key strategic consideration in the recovery system of any product is to make proper decisions on reverse manufacturing alternatives including both recovery and disposal options. The nature of such decisions is complex due to the uncertainty existing in the quality of the product returns and lack of information about the product. Consequently, the need of correct diagnosis of recovery/ disposal options for the returned products necessitates the development of a comprehensive model considering all technical and non-technical parameters. Although human experts with the aid of practical experience may handle such complex problems, this procedure is time consuming and may lead to imprecise decisions. This study presents a fuzzy rule-based system to provide a correct decision mechanism for ranking the recovery/disposal strategies by knowledge acquisition through a simple reverse supply chain with a collection center for each particular returned product. The proposed system has applications with a focus on brown goods, although the system may be applied to other similar kinds of products through some changes. To achieve the objective of this study, the proposed model is used to analyze a case of mobile phone, ending up in coherent results. Keywords: Fuzzy expert system, Product returns, Return strategies (Received on January 15, 2014; Accepted on December 22, 2014)

1. INTRODUCTION In addition to the effects of ever-changing technologies, the rapid changes in the natural environment, the enforcements by governments and the proven profitable engagement of recovery and reuse activities have influenced the way most companies perform their business in increasing the rate of reusing returned products. The implementation of extended producer responsibility in the light of new governmental policies, together with the growing public interest in environmental issues, will cause Original Equipment Manufacturers (OEMs) to take care of their products after they have been discarded by the consumer (Krikke et al., 1998). In this regard, product recovery management (PRM), proposed by Thierry et al. (1995), serves to recover much of the economic and ecological value of products by reducing the quantity of wastes. There are four recovery and disposition categories for product returns including reuse/resell, product upgrade, material recovery and waste management. Each category includes recovery/disposal alternatives. Table 1 presents the alternatives for each category together with their explanations. Thus, we have 8 different recovery/ disposal activities when a product is returned back to the chain: reusing, reselling, repairing, remanufacturing, refurbishing, cannibalization, recycling and disposal. Every returned products/parts should pass one/more of these activities to be back to the second market or to be disposed. One of the key strategic issues in product recovery management is to find a proper option for recovery or disposal activities, as each of these activities bears its own costs. As stated by Behret and Korugan, (2009), uncertainties in the quality, quantity and timing of the product return flow make it hard to select the best disposition alternative decisions. Large variations in the quality of returns are a major factor for uncertainties in the time, cost and rate of the recovery process (Liu et al., 2012). Thus, it seems necessary to provide a strategic decision model for exploring the detailed quality of returned products before making the recovery decisions. This paper aims at providing a comprehensive expert system through defining the factors mostly affecting the ranking of the above-mentioned recovery options for product returns. The proposed model analyzes the properties of returned products to find the best recovery option(s) in an accurate way. Although there are numerous studies in fuzzy decision making as in Chan et al. (2003), Liu et al. (2013), Ozdaban et al. (2010), Tsai (2011) and Olugu et al. (2012), based on our findings, there are just a few pieces of research in which expert and fuzzy rule-based decision systems are applied in reverse logistic issues. They are mainly focused on performance measurement, disassembly process, life cycle and recovery management (Singh et al., 2003; Meimei et al., 2004; Fernandez et al., 2008; Jayant, 012). There are also few published research studies that provide clear policies for managing and clustering of returned products. Thus, we review those studies that are the most relevant to the research we conduct. ISSN 1943-670X

INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22 (2), 292-300 ,2015

Landfill Location with Expansion Possibilities in Developing Countries Pablo Manyoma1,*, Juan P. Orejuela 1, Patricia Torres2, Luis F. Marmolejo2, and Carlos J. Vidal1 1

School of Industrial Engineering, Universidad del Valle, Santiago de Cali, Colombia *Corresponding author’s e-mail: [email protected] 2

School of Natural Resources and Environment Engineering Universidad del Valle Santiago de Cali, Colombia

Municipal Solid Waste Management (MSWM) has become one of the main challenges of urban areas in the world. For developing countries, this situation is of greater severity due to disordered population growth, rapid industrialization, and deficiency in regulations, among other factors. One component of MSWM is the final disposal, where landfills are the most commonly used technologies for this purpose. According to a body of research, landfill location should meet the needs of all stakeholders, thus we propose a model based on multi-objective programming considering several decisions such as landfill opening, when they should be opened, and especially a common situation in our countries: the kind of expansion capacity that should be used. We present an example that reflects the conflict of two objectives: cost and environmental risk. The results show the allocation of each municipality to each landfill and the amount of municipal solid waste to be sent, among other variables. Keywords: capacity expansion; landfill location; multi-objective programming; municipal solid waste management; undesirable facilities. (Received on January 7, 2014; Accepted on January 25, 2015) 1. INTRODUCTION Waste has increasingly become a major environmental concern for modern society, due to population growth, the high level of urbanization, and the mass consumption of different products (Eriksson and Bisaillon, 2011). For this reason, one of the greatest challenges in urban areas worldwide, especially in developing countries’ cities, is the Municipal Solid Waste Management - MSWM. Even if a combination of this management technique is utilized and policies of waste reduction and reuse are applied, the existence of sanitary landfills is necessary for any MSWM system (Moeinaddini et al., 2010). Particularly in Latin America and the Caribbean countries, waste disposal has become a serious problem and it is currently a critical concern. Even though some of these countries have a legal framework for waste control, very few possess the infrastructure and human resources to enforce regulations, especially those related to recycling and disposal. In these countries, landfills are the main alternative used to dispose of solid waste (Zamorano et al., 2009). During the last years, an important change in the use of regional solutions for solid waste management has been observed. A growing number of municipalities in the region have been associated in communities in order to achieve significant scale economies and better enforcement of regulatory standards (OPS-BID-AIDIS, 2010). Nowadays, landfills are seen as engineering projects that consider the whole management cycle: planning, design, operation, control, closure, and post-closure. There is a vital step in the first planning stage: site location. The problem of identifying the best location must be based on many different criteria. Issues such as political stability, the existing infrastructure in regions, and the availability of a trained workforce are critical on a ‘macro level’ when making such decisions. Once a set of feasible regions have been identified for locating a new facility, selecting the ultimate location takes place on a ‘micro level’ (Gehrlein and Pasic, 2009). Identifying and selecting a suitable site for a landfill is one of the most outstanding tasks. Here, it must be considered the collection and processing of information that relate to environmental, socioeconomic and operational aspects such as the distance to the site, local environmental conditions, the existing patterns of land use, site access, and the potential uses of the landfill after being completed, among many others features. That is why the location of landfills is a complex problem (O’Leary and Tchobanoglous, 2002; Geneletti, 2010). During the past 20 years, many authors around the world have applied different approaches to address the landfill location problem. Erkut and Moran (1991), Hokkanen and Salminen (1997), and Banias et al. (2010), among others, have ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING

International Journal of Industrial Engineering, 22(2), 301-313, 2015

Establishing a Conceptual Model for Assessing Project Management Maturity in Industrial Companies Seweryn Spalek Faculty of Organization and Managementㅁ Silesian University of Technology Gliwice, Poland Corresponding author’s e-mail address: [email protected]

The number of projects undertaken by companies nowadays is significant. Therefore, there is a need to establish processes in the company supporting and increasing project management efficacy. In order to achieve this, the companies need to know how good they are at organizational project management, taking into consideration different perspectives. Knowing their strengths and weaknesses, they are able to improve their activities in challenging areas. In view of the critical literature review and interviews with chosen companies, the article proposes a conceptual model for assessing project management maturity in industrial companies. The model is based on four assessment areas. Three of them (human resources, methods & tools, and environment) represent the traditional approach to maturity measurement, whilst the fourth, knowledge management, represents a new approach to the topic. The model was tested in over 100 companies in the machinery industry to verify its practical application and establish valid results of implementation, which have not been previously explored. Keywords: project management, model, assessment, maturity, industry, knowledge management. (Received on November 15, 2011; Accepted on March 16, 2015)

1. INTRODUCTION The need for models that could be implemented in industry is recognized by authors of publications in different areas of expertise (Bernardo, Angel, & Eloisa, 2011; Jasemi, Kimiagari, & Memariani, 2011; Kamrani, Adat, & Azimi, 2011; Metikurke & Shekar, 2011). The importance of new product development from a different perspective was recognized, for example, by Adams-Bigelow et al. (2006) and measured by Metikurke & Shekar (2011) and Kahn, Barczak, & Moss (2006). New product development is a laborious endeavour that must be managed properly. Therefore, industrial companies are interested in having an efficient tool to measure how good they are when it comes to project management. That assessment must be done in different areas, including the set of best practices as the reference. Moreover, Kwak (2000) noticed that there is an influence on the company’s project management maturity level and the key performance indicators of projects. Furthermore, Spalek (2014a, 2014b), based on his studies in the industrial companies, shows that increasing the maturity level potentially reduces the costs and time of ongoing and new projects. In fact, industrial companies are managing an increasing number of projects every year (Aubry et al., 2010). Besides the typical operational representatives in the project-oriented environment like the IT and construction sectors, companies in other industries have increasingly embraced newer project management methods (Cho & Moon, 2006; Grant & Pennypacker, 2006; Liu, Ma, & Li, 2004; McBride, Henderson-Sellers, & Zowghi, 2004; C. T. Wang, Wang, Chu, & Chao, 2001). A good example is the machinery sector, which is very focused on the efficient development of new products that are then used by other industries. The products of machinery industry are divided into those of general purpose, heavyindustry machines and their elements and components, totalling more than 200 products (ISIC, 2008). Therefore, companies in the machinery industry are a kind of backbone of the entire economy and are located all over the world. However, the most significant production comes from the EU (European Union), ASEAN+6 (Japan, Korea, Singapore, Indonesia, Malaysia, Philippines, Thailand, China (including Hong Kong), Brunei, Cambodia, Laos, Burma, Vietnam, India, Australia, New Zealand) and NAFTA & UNASUR (Canada, Mexico, USA, Argentina, Bolivia, Brasilia, Chile, Columbia, Ecuador, Guyana, Paraguay, Peru, Surinam, Uruguay, Venezuela) areas (Kimura & Obashi, 2010). The main customers of products of the machinery industry are companies from the following industries: construction, agriculture, mining, steelworks, food and textiles.

ISSN 1943-670X

 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING