-Seminar

COMPUTER AIDED ENGINEERING

A SEMINAR REPORT

Submitted by ASWATHY SETHU Partial fulfilment for the award of the degree of

Master of Technology

DEPARTMENT OF PRODUCTION ENGINEERING GOVERNMENT ENGINEERING COLLEGE THRISSUR December 2011 Computer Aided Engineering

GOVERNMENT ENGINEERING COLLEGE THRISSUR DEPARTMENT OF PRODUCTION ENGINEERING

2011

BONAFIDE CERTIFICATE Certified that this is the report of the seminar titled ―COMPUTER AIDED ENGINEERING‖ Presented by Ms. Aswathy Sethu Of first semester M.Tech in partial fulfillment of the requirement for the award of the degree of Master of Technology in Production Engineering (Manufacturing Systems Management) of the University of Calicut

Staff-in-charge Prof. MANJITH KUMAR Associate Professor Department of Production Engineering Government Engineering College Thrissur Prof. P.V. Mary C Kurien Professor and Head Department of Production Engineering Government Engineering College Thrissur

Computer Aided Engineering

ABSTRACT

COMPUTER AIDED ENGINEERING

Computer aided engineering (CAE) is an analysis performed at the computer terminal using a CAD system. It includes computer-aided design (CAD), computer-aided analysis (CAA), computer-integrated manufacturing (CIM), computer-aided manufacturing (CAM), material requirements planning (MRP), and computer-aided planning (CAP). Its purpose is mainly to analyze the different materials, products, their performance and quality, such as durability, stability, etc. It has many advantages like improved safety and product quality, reduced product cost, customer satisfaction, etc. and so it has many applications like used to analyze the properties of material, commercial and flight simulations, etc. It has 3 phases: pre-processing, analysis solver, postprocessing of results.

CAE is mainly of 3 types: finite element analysis (FEA), computational fluid dynamics (CFD), and Boundary Element Analysis (BEA). FEA is used to conduct static and dynamic analysis. CFD is used to optimize components for efficient fluid flow and heat transfer. BEA is used to predict noise characteristics on various systems.

One of the real world examples is MEMS that is micro electro mechanical systems. It has the size of a grain of salt or the eye of a needle.

ACKNOWLEDGEMENT Computer Aided Engineering

I take this opportunity to thank the Lord ALMIGHTY for being my driving force and for his immense blessings towards the successful presentation completion of my seminar.

I wish to express my deepest gratitude to Dr. K. Vijayakumar, Principal of Government Engineering College, Thrissur and Prof. P.V.Gopinadhan, H.O.D of Production Department, Prof. Manjeet, who is my guide. I am deeply indebted to him for the timey help and meticulous guidance that he provided to help with my seminar. I take this opportunity to sincerely thank my guide for his guidance and encouragement in carrying out this seminar.

I would also like to express my profound gratitude to Dr. Haris Naduthodi, Ms. Mary C Kurian and Mr. Sunil D T, Prof. Parameshvaran, Mr. Satish for their constant and valuable suggestions while doing the seminar work.

Last but not least I would like to extend my special thanks to my beloved family members and friends for their inspiration and help during the course of this seminar research.

Thrissur 16-12- 2011

Computer Aided Engineering

ASWATHY SETHU

TABLE OF CONTENTS CHAPTER NO.

TITLE

PAGE NO.

Abstract

iii

Acknowledgement

iv

1. INTRODUCTION 2. CONCEPT AND DEFINITION 3. GOALS OF COMPUTER AIDED ENGINEERING 4. PHASES OF CAE 5. CONCEPT OF CAE DEVELOPMENT IN A CAR MANUFACTURING COMPANY 6. BENEFITS OF CAE 7. APPLICATIONS OF CAE 8. MEMS 9. CONCLUSION

Computer Aided Engineering

1. INTRODUCTION

The future success of a manufacturing enterprise is likely to be determined by the speed and efficiency with which it incorporates new technologies into its operations. The process which is currently used to engineer, or re-engineer, manufacturing systems is often ad hoc. Computerized tools are used on a very limited basis. Given the costs and resources involved in the construction and operation of manufacturing systems, the engineering process must be made more scientific. Powerful new computing environments for engineering manufacturing systems could help achieve that objective. Today, Computer Aided Engineering (CAE) technology contributes decisively to shortening and optimizing product development cycles in many fields of industry and research. Computer aided analysis and simulation enables our customers to assess and test the behaviour of future components, products and processes by subjecting them to a range of computer simulated physical conditions. This leads to savings in both the time and money which would have been spent on cost-intensive test runs without any loss in quality and opens up new possibilities for innovation. Computer aided engineering (CAE) retrieves description and geometry from a computer aided manufacturing (CAD) database. Computer aided engineering (CAE) is an analysis performed at the computer terminal using a CAD system. Thus software tools that have been developed to support the activities in computer analysis are considered CAE tools. CAE tools are being used, for example, to analyze the robustness and performance of components and assemblies. The term encompasses simulation, validation, and optimization of products and manufacturing tools. In the future, CAE systems will be major providers of information to help support design teams in decision making. In regard to information networks, CAE systems are individually considered a single node on a total information network and each node may interact with other nodes on the network. CAE systems can provide support to businesses. This is achieved by the use of reference architectures and their ability to place information views on the business process. Reference architecture is the basis from which information model, especially product and manufacturing models. The term CAE has also been used by some in the past to describe the use of computer technology within engineering in a broader sense than just engineering analysis. Computer Aided Engineering

2. CONCEPT AND DEFINITION 2.1 ORIGIN OF CAE: Historically, engineers analyzed designs by building and testing physical prototypes, performing calculations by hand or with some computing aid such as a slide rule. They frequently used tabulated mathematical functions, approximation methods, and data accumulated from previous experience and physical testing to simplify their analyses. Some analyses were so time-consuming that, when done at all, they could be completed only for one simplified example. This frequently led to under- and over-designed systems. The first case resulted in systems that did not work properly or failed outright. In the second case, the systems were more expensive than necessary or too heavy to meet their goals. Physical prototypes were (and remain) very costly and time-consuming to build and test—and they often have to be recreated as designs are changed. The advent of analog and digital computers provided engineers with systems capable of analyzing designs much more quickly and allowed them to undertake analyses that were previously impractical to attempt. However, early computer systems were too slow and limited in capacity (memory, storage, I/O speed) to handle extremely large or complex mechanical systems. While they provided a base for new, more extensive design evaluations, many of the historical problems remained and new problems arose. These included limited access to expensive, high powered computing systems and difficulties describing the physical form of designs in a way that computers could work with them efficiently. Therefore, many early analysis programs used unrealistically simplified, schematic-like descriptions of the physical system. It was impossible to describe any but the simplest system’s geometry within the computing environment. Then came the creation of CAD/ CAM systems by the aerospace industry in the early 1960s to assist with the massive design and documentation tasks associated with producing airplanes. By the late 1970s, these codes were being distributed to other industries. CAD/CAM systems have been used primarily for detail design and drafting along with the generation of numerical control instructions for manufacturing. Gradually, more CAE functions are being added to CAD/CAM systems. A trend toward open architecture with flexible geometry interfaces is stimulating the addition of more analysis and manufacturing functions. Modelling with CAD/CAM systems has become fairly sophisticated. Most popular commercial systems support 2D and 3D wireframe, surface models, and solid models.

Computer Aided Engineering

Rendered surface models differ from solid models in that the latter have full information about the interior of the object. 2.2 DEFINITON OF CAE: Computer aided engineering (CAE) is an analysis performed at the computer terminal using a CAD system. It includes computer-aided design (CAD), computer-aided analysis (CAA), computer-integrated manufacturing (CIM), computer-aided manufacturing (CAM), material requirements planning (MRP), and computer-aided planning (CAP). CAE mainly depends on CAD. It is usually used in every industry such as aerospace, automobile industry.

Flow diagram for a computer aided engineering

Computer-aided design (CAD), also known as computer-aided design and drafting (CADD) ,[1] is the use of computer technology for the process of design and designdocumentation. Computer Aided Drafting describes the process of drafting with a computer. CADD software provides the user with input-tools for the purpose of streamlining design processes; drafting, documentation, and manufacturing processes. CADD output is often in the form of electronic files for print or machining operations. CADD software uses either vector based graphics to depict the objects of traditional drafting, or may also produce raster graphics showing the overall appearance of designed objects. Computer Integrated Manufacturing (CIM) encompasses the entire range of product development and manufacturing activities with all the functions being carried out Computer Aided Engineering

with the help of dedicated software packages. The data required for various functions are passed from one application software to another in a seamless manner. For example, the product data is created during design. This data has to be transferred from the modelling software to manufacturing software without any loss of data. CIM uses a common database wherever feasible and communication technologies to integrate design, manufacturing and associated business functions that combine the automated segments of a factory or a manufacturing facility. CIM reduces the human component of manufacturing and thereby relieves the process of its slow, expensive and error-prone component. CIM stands for a holistic and methodological approach to the activities of the manufacturing enterprise in order to achieve vast improvement in its performance. This methodological approach is applied to all activities from the design of the product to customer support in an integrated way, using various methods, means and techniques in order to achieve production improvement, cost reduction, fulfillment of scheduled delivery dates, quality improvement and total flexibility in the manufacturing system. CIM requires all those associated with a company to involve totally in the process of product development and manufacture. In such a holistic approach, economic, social and human aspects have the same importance as technical aspects. CIM also encompasses the whole lot of enabling technologies including total quality management, business process reengineering, concurrent engineering, workflow automation, enterprise resource planning and flexible manufacturing. Material

requirements

planning

(MRP) is

a

production

planning

and inventory control system used to manage manufacturing processes. Most MRP systems are software-based, while it is possible to conduct MRP by hand as well. The basic function of MRP system includes inventory control, bill of material processing and elementary scheduling. MRP helps organizations to maintain low inventory levels. It is used to plan manufacturing, purchasing and delivering activities. "Manufacturing organizations, whatever their products, face the same daily practical problem - that customers want products to be available in a shorter time than it takes to make them. This means that some level of planning is required." Companies need to control the types and quantities of materials they purchase, plan which products are to be produced and in what quantities and ensure that they are able to meet current and future customer demand, all at the lowest possible cost. Making a bad decision in any of these areas will make the company lose money.

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Computer-aided process planning (CAPP) is the use of computer technology to aid in the process planning of a part or product, in manufacturing. CAPP is the link between CAD and CAM in that it provides for the planning of the process to be used in producing a designed part. Process planning is concerned with determining the sequence of individual manufacturing operations needed to produce a given part or product. The resulting operation sequence is documented on a form typically referred to as a route sheet containing a listing of the production operations and associated machine tools for a workpart or assembly. Process planning in manufacturing also refers to the planning of use of blanks, spare parts, packaging material, user instructions (manuals) etc. Process planning translates design information into the process steps and instructions to efficiently and effectively manufacture products. As the design process is supported by many computer-aided tools, computer-aided process planning (CAPP) has evolved to simplify and improve process planning and achieve more effective use of manufacturing resources.

3. GOALS OF COMPUTER AIDED ENGINEERING The goals of computer-aided engineering (CAE) are: • improved product quality • improved safety • reduced engineering time, achieved through fewer design iterations • improved product functionality and usability • reduced number of prototypes, ultimately leading to their elimination in many cases • reduced product cost.

These goals has helped computer aided engineering to achieve various heights like:  CAE can be used to perform variety tests like car crash the test simulation  Can be used for Commercial and military flight simulations  It is also used to analyze properties of different types material used in production application of computerized methods during the design of technical systems  It increases production efficiency and quality through better designs  It is also a Tool for decision making-what the product is going to look like, its performance characteristics, what improvements need to be made?  CAD analysis on be done on the computer screen Computer Aided Engineering

 There is no need to build products’ prototypes  Results of analysis is essential and can be saved for future of the product  Customer satisfaction is priority and can be achieved through CAE  CAE has to be compliant with many U.S. and international standards and so the product real-world performance and safety is achieved  It also provide the customers with a concept before building expensive prototypes and pre-production units and hence customer satisfaction can be achieved.

4. PHASES OF CAE CAE applications support a wide range of engineering disciplines or phenomena including: 

Stress and dynamics analysis on components and assemblies using finite element

analysis (FEA) 

Thermal and fluid analysis using computational fluid dynamics (CFD)



Kinematics and dynamic analysis of mechanisms (multi body dynamics)

In general, there are three phases in any computer-aided engineering task: 

Pre-processing – defining the model and environmental factors to be applied to it. It is typically a finite element model, but facet, voxel and thin sheet methods are also used in this phase.



Analysis solver- it is usually performed on high powered computers.



Post-processing of results – it is the last phase in any computer aided engineering task and is done using visualization tools.

This cycle is iterated, often many times, either manually or with the use of commercial optimization software. 4.1 FINITE ELEMENT ANALYSIS: The finite element method (FEM) (its practical application often known as finite element analysis (FEA)) is a numerical technique for finding approximate solutions of partial differential equations (PDE) as well as integral equations. The solution approach is Computer Aided Engineering

based either on eliminating the differential equation completely (steady state problems), or rendering the PDE into an approximating system of ordinary differential equations, which are then numerically integrated using standard techniques such as Euler's method, Runge-Kutta, etc. In solving partial differential equations, the primary challenge is to create an equation that approximates the equation to be studied, but is numerically stable, meaning that errors in the input and intermediate calculations do not accumulate and cause the resulting output to be meaningless. There are many ways of doing this, all with advantages and disadvantages. The finite element method is a good choice for solving partial differential equations over complicated domains (like cars and oil pipelines), when the domain changes (as during a solid state reaction with a moving boundary), when the desired precision varies over the entire domain, or when the solution lacks smoothness. For instance, in a frontal crash simulation it is possible to increase prediction accuracy in "important" areas like the front of the car and reduce it in its rear (thus reducing cost of the simulation). Another example would be in Numerical weather prediction, where it is more important to have accurate predictions over developing highly-nonlinear phenomena (such as tropical cyclones in the atmosphere, or eddies in the ocean) rather than relatively calm areas.

Example for finite element analysis

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APPLICATION OF FINITE ELEMENT ANALYSIS: A variety of specializations under the umbrella of the mechanical engineering discipline (such as aeronautical, biomechanical, and automotive industries) commonly use integrated FEM in design and development of their products. Several modern FEM packages include specific components such as thermal, electromagnetic, fluid, and structural working environments. In a structural simulation, FEM helps tremendously in producing stiffness and strength visualizations and also in minimizing weight, materials, and costs. FEM allows detailed visualization of where structures bend or twist, and indicates the distribution of stresses and displacements. FEM software provides a wide range of simulation options for controlling the complexity of both modelling and analysis of a system. Similarly, the desired level of accuracy required and associated computational time requirements can be managed simultaneously to address most engineering applications. FEM allows entire designs to be constructed, refined, and optimized before the design is manufactured. This powerful design tool has significantly improved both the standard of engineering designs and the methodology of the design process in many industrial applications. The introduction of FEM has substantially decreased the time to take products from concept to the production line. It is primarily through improved initial prototype designs using FEM that testing and development have been accelerated. In summary, benefits of FEM include increased accuracy, enhanced design and better insight into critical design parameters, virtual prototyping, fewer hardware prototypes, a faster and less expensive design cycle, increased productivity, and increased revenue.

4.2 BOUNDARY ELEMENT ANALYSIS: The boundary element method (BEM) is a numerical computational method of solving linear partial differential

equations which have been formulated as integral

equations (i.e. in boundary integralform). It can be applied in many areas of engineering and science including fluid mechanics, acoustics, electro-magnetics, and fracture mechanics. The integral equation may be regarded as an exact solution of the governing partial differential equation. The boundary element method attempts to use the given boundary conditions to fit boundary values into the integral equation, rather than values throughout the space defined by a partial differential equation. Once this is done, in the post-processing stage, the integral equation can then be used again to calculate numerically the solution directly at any desired point in the interior of the solution domain. Computer Aided Engineering

BEM is applicable to problems for which Green's functions can be calculated. These usually involve fields in linear homogeneous media. This places considerable restrictions on the range and generality of problems to which boundary elements can usefully be applied. Nonlinearities can be included in the formulation, although they will generally introduce volume integrals which then require the volume to be discretised before solution can be attempted, removing one of the most often cited advantages of BEM The boundary element method is often more efficient than other methods, including finite elements, in terms of computational resources for problems where there is a small surface/volume ratio [1]. Conceptually, it works by constructing a "mesh" over the modelled surface. However, for many problems boundary element methods are significantly less efficient than volume-discretisation methods. Boundary element formulations typically give rise to fully populated matrices. This means that the storage requirements and computational time will tend to grow according to the square of the problem size. By contrast, finite element matrices are typically banded (elements are only locally connected) and the storage requirements for the system matrices typically grow quite linearly with the problem size. Compression techniques (e.g. multipole expansions or adaptive cross approximation/hierarchical matrices) can be used to ameliorate these problems, though at the cost of added complexity and with a success-rate that depends heavily on the nature of the problem being solved and the geometry involved.

4.3 COMPUTATIONAL FLUID DYNAMICS: Computational fluid dynamics, usually abbreviated as CFD, is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows. Computers are used to perform the calculations required to simulate the interaction of liquids and gases with surfaces defined by boundary conditions. With high-speed supercomputers, better solutions can be achieved. Ongoing research yields software that improves the accuracy and speed of complex simulation scenarios such as transonic or turbulent flows. Initial validation of such software is performed using a wind tunnel with the final validation coming in full-scale testing, e.g. flight tests. The fundamental basis of almost all CFD problems are the Navier–Stokes equations, which define any singlephase fluid flow. These equations can be simplified by removing terms describing viscosity to yield the Euler equations. Further simplification, by removing terms describing vorticity

Computer Aided Engineering

yields the full potential equations. Finally, these equations can be linearized to yield the linearized potential equations. In this approach, these procedures are followed: 

During preprocessing 

The geometry (physical bounds) of the problem is defined.



The volume occupied by the fluid is divided into discrete cells (the mesh). The mesh may be uniform or non uniform.



The physical modeling is defined – for example, the equations of motions + enthalpy + radiation + species conservation



Boundary conditions are defined. This involves specifying the fluid behaviour and properties at the boundaries of the problem. For transient problems, the initial conditions are also defined.



The simulation is started and the equations are solved iteratively as a steady-state or transient.



Finally a postprocessor is used for the analysis and visualization of the resulting solution.

4.4 KINEMATIC AND DYNAMIC ANALYSIS: "Motion study" is a catch-all term for simulating and analyzing the movement of mechanical assemblies and mechanisms. Traditionally, motion studies have been divided into two categories: kinematics and dynamics. Kinematics is the study of motion without regard to forces that cause it; dynamics is the study of motions that result from forces. Other closely related terms for the same types of studies are multibody dynamics, mechanical system simulation, and even virtual prototyping. Kinematic analysis is a simpler task than dynamic analysis and is adequate for many applications involving moving parts. Kinematic simulations show the physical positions of all the parts in an assembly with respect to the time as it goes through a cycle. This technology is useful for simulating steady-state motion (with no acceleration), as well as for evaluating motion for interference purposes, such as assembly sequences of complex mechanical system. Many basic kinematic packages, however, go a step further by providing "reaction forces," forces that result from the motion. Dynamic simulation is more complex because the problem needs to be further defined and more data is needed to account for the forces. But dynamics are often required to accurately simulate the actual motion of a mechanical system. Generally, kinematic simulations help Computer Aided Engineering

evaluate form, while dynamic simulations assists in analyzing function. Traditionally, kinematics and dynamics have followed the classic analysis software method of pre processing (preparing the data), solving (running the solution algorithms, which involve the solution of simultaneous equations), and post processing (analyzing the results). Even though today's programs are much more interactive, most programs follow this basic process since it is a logical way to solve the problem. Most solvers are available as independent software programs. The basic output of motion studies are numerous, including animation, detecting interference, trace functions, basic motion data, and plots and graphs. Animated motions are the classic output of simple kinematic analyses. Initially, the designer uses simple animation as a visual evaluation of motion to see if it is what is desired. More sophisticated animations can show motion from critical angles or even inside of parts, a definite advantage over building and running a physical prototype. The ability to detect and fix interferences without switching between software is one of the primary benefits of integrating motion simulation and CAD. Most systems provide colour feedback, for example, by turning to red parts that experience interferences. More useful, however, are systems that turn the interference volume into a separate piece of geometry, which can then be used to modify the parts to eliminate the interference. Trace functions provide additional information about motion. The motion of a joint or a particular point on a part can be plotted in 3D as a line or surface. Or, the system can leave copies of the geometry at specified intervals. Such functions can provide an envelope of movement that can be used to design housings or ensure clearances. Motion data, such as forces, accelerations, velocities, and the exact locations of joints or points on geometry can usually be extracted, although such capabilities are more applicable to dynamic simulations rather than kinematic studies. Some systems allow users to attach instruments to their models to simplify specifying what results they want to see. Most packages provide a plethora of plotting and graphing functions. Plots and graphs are most commonly used because values vary over time and are more meaningful than a single value at any given time. An especially useful capability for studying design alternatives is to plot the results of two different simulations on the same graph. Such data can also help designers determine the size of motors, actuators, springs, and other mechanism components. Forces that result from motion are of particular interest because they can be used as loads (or, at least, to calculate them) for structural analysis of individual members. Typically, the highest load for a cycle is used to perform a linear static finite element analysis (FEA) of critical individual components Computer Aided Engineering

of a mechanism. Integration of solid modelling, motion simulation, and FEA software can greatly streamline this process—especially important when studying design alternatives, where many analyses are required.

5. CONCEPT OF CAE DEVELOPMENT IN A CAR MANUFACTURING COMPANY The example for the usage of computer aided engineering is taken from Stadco automotives, a car manufacturing company. Stadco is the UK's largest Tier 1 supplier of BIW pressings and assemblies and the only one with a full product design capability from styling and concept development through to production design, launch support and production facility implementation. Stadco has operations in the UK, Germany, Russia and now, India. Stadco has also delivered a number of projects in India, North America, South America and Europe. Stadco Automotive Pvt. was formed in 2008 and will offer Engineering services, BIW prototyping and BIW manufacture through a phased move into the Indian market. Stadco established its Indian technical centre in Chennai in 2008, supporting both international OEM's and domestic Indian automotive manufacturers.

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The process in the manufacture of car consists of many process like concept of CAD development, CAD design, PDM and DMU development, Durability simulation, NVH simulation, Vehicle crash development. 5.1 CONCEPT OF CAD DEVELOPMENT: Stadco integrates Concept CAD development for a quick cost effective method, by which to establish proposals / ideas for evaluation. Stadco's concept team is best used in parallel to complement detailed sketches and illustrations. It has the benefit of 3D and is dimensionally accurate. Realistic visuals at this early stage enable the design process to move forward quickly to satisfactory conclusions by using an integrated team approach.

5.2 CAD DESIGN: Stadco has been in the forefront of CAD design for decades. Our experienced design team uses cutting edge technology to realise design benefits for our customers. Our team's experience covers a range of different CAD systems so they can deliver excellently engineered products in the appropriate format for our customers. This also allows us to utilise the best software for any given design. The engineering design team can use parametric modeling solutions. The parametric modelers are aware of the characteristics of components and the interactions between them. By maintaining relationships between elements a model can quickly be manipulated, allowing variant or face-lifts of vehicles to be achieved in very competitive time scales.

5.3 PDM AND DMU DEVELOPMENT: DMU, Digital mock-up is one of the most powerful engineering tools currently available. Through using part information stored within Computer Aided Design Computer Aided Engineering

packages, prototype builds can be simulated. The Stadco programme teams have access to projection facilities to allow life-size screening during design reviews. This ensures the core team can simultaneously view areas of concern. In addition Stadco uses secure remote computer conferencing to allow international multi-site project teams to collaborate whilst viewing the same packaging data. Discussions are aided by using clash detection routines and dynamic sectioning options. DMU technology is a powerful tool to detect problem areas long before any metal parts are formed. This reduces the number of prototypes required and maximises the benefit of using builds to trial assembly processes and not to trial designs.

5.4 DURABILITY SIMULATION: Stadco's specialists in durability can design and develop structures with the ability to meet a combination of abuse loads (strength) and cyclic loads (fatigue). In the case of abuse loads these are well understood, however the cyclic loads generally require measured road load data. Stadco's relationship with the top testing houses across the world gives us the capability to capture real road load data to cover all our customers' requirements, however unique.

5.5 NVH SIMULATION: Noise, Vibration, and Harshness (NVH) is of strategic importance in delivering the brand values and in meeting customers increasing level of expectations for quality and vehicle comfort. Stadco understands the process of converting the brand values into objective vehicle targets, which in turn are cascaded down to sub-system and component level. This gives the fundamental requirement for engineering NVH character of the vehicle. The NVH Computer Aided Engineering

performance of the vehicle covers many different operating conditions and spans a wide frequency range. In order to design for these numerous conditions, a large number of simulation and test activities are undertaken to address performance at both the vehicle and component levels. Stadco has powerful, dedicated cluster hardware enabling numerous simulations to be undertaken quickly, often around the clock. This ensures calculation of performance levels and the timely generation of optimum solutions.

5.6 VEHICLE CRASH DEVELOPMENT: Vehicle safety targets are primarily driven by legislation and the legal requirements which must be met in order to sell vehicles in a particular market. These are also complemented by the OEM internal company standards, and external factors such as consumer group and insurance testing, competitor vehicles, etc.

6. BENEFITS OF CAE The benefits of CAE are: •

Reduced product development cost and time, with improved product quality and durability.

•

Designs can be evaluated and refined using computer simulations

 CAE helps engineering teams manage risk and understand the performance implications of their designs

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7. APPLICATION OF CAE

In area of piping plant design in civil engineering In roadway design, most surveying function Used in many specialized analysis, for circuit design, VLSI device design, and simulation Used in Mechanical event simulation (MES) Control systems analysis Simulation of manufacturing processes like casting, molding and die press forming Optimization of the product or process

8. MEMS MEMS is micro electro mechanical system. Micro Electro Mechanical Systems (MEMS) are micromachines the size of a grain of salt or the eye of a needle that integrate mechanical elements, sensors, actuators and electronics on a common silicon substrate. These devices can replace bulky actuators

and sensors with micro scale

equivalents that can be produced in large quantities by fabrication process used in integrated circuit photolithography. This reduces cost, bulk weight and power consumption while increasing performance, production volume and functionality by orders of magnitude. The applications of MEMS are:  optical switches within telecommunication and networking systems,  accelerometers in automotive airbags, inkjets in desktop printers and  sensors in medical testing equipment.

9. CONCLUSION CAE is an analysis entirely done on computer using CAD systems. Its purpose is to analyze different materials, products, their performance and quality such as durability, stability, endurance and/or reactivity to any possible factor that can affect the performance of the material, part, and/or the product A typical CAE process comprises of pre-processing, Computer Aided Engineering

solving, and post-processing steps. In the pre-processing phase, engineers model the geometry and the physical properties of the design, as well as the environment in the form of applied loads or constraints. Next, the model is solved using an appropriate mathematical formulation of the underlying physics. In the post-processing phase, the results are presented to the engineer for review. The analysis of CAE consists of mainly 4 methods like finite element analysis, computational fluid dynamics, boundary element analysis, kinematic and dynamic analysis. It has many advantages like its cost saving and ensures customer satisfaction and improves the speed, efficiency and the quality of many products ranging from simple parts to vehicles, airplanes etc. Designs can be evaluated and refined using computer simulations. Its applications include control systems analysis, simulation of manufacturing processes like casting, moulding and die press forming, Optimization of the product or process and mems.

REFERENCES 

CAD/CAM/CIM by P.Radhakrishnan, 3rd edition, New Age International publications



Fundamentals of computer aided engineering, by B.Raphael and I.F.C. Smith, Wiley publishers



http://www.roushind.com/html/cae.html



http://www.computeraidedengineering.com



http://www.fea-online.com



http://www.marc.com



http://www.optem.com



http://www.ece.curtin.edu.au



http://kernow.curtin.edu.au/cae.html



www.stadco.co.in

Computer Aided Engineering

Computer Aided Engineering