Project

2012

Final Project IEG 230: Advanced System Simulation Dr. Seifedine Kadry 22/05/12 Ahmad Al- Rasheedi Abdullah Al- Khamees Fayez Jarrad

AUM

Table of contents

1. Introduction

2. Problem Statement

3. Modeling the system

4. Results

5. Suggestions for improvement

6. Comparing improved results

7. Conclusion

Introduction: This project is based on a real life problem that will be simulated and improved using Arena. This example looks at a single cashier that that has 100 customers a day. Customers enter the grocery store, and then wait in a queue in front of the cashier to buy their goods, which is the checkout. They leave the store, and the process is repeated by 100 customers.

Problem Statement: There are two problems that the grocery store faces. The first is the long waiting time of customer, and the second is the theft and vandalism that they have been facing. These issues will be tackled and improved using simulation of the system.

Modeling the system:

In the create process, we used a uniform distribution from 1 to 8, because numbers are randomly distributed between 1 to 8 minutes. Entity type will be named customer, as they are the arriving entity.

The assign module was used to save the arrival time.

This record was used to calculate the average interarrival time between customers.

In the checkout, we have used a seize delay release logic as there is wait time. Also, the service time was a probability in the original excel sheet, therefore a discrete delay type was used. With each probability a variable was assigned to it as it was in the excel sheet.

This record has a time interval type that calculates the total time per customer.

The dispose process is used to show each customer’s exit.

Pictures were used to identify each process in a visual representation. If the process is idle it is represented using an empty desk. When the process is busy the desk is occupied, and each customer is identified using moving people.

Run Setup:

The case study has simulated only 100 customers, therefore to do this in Arena we had to add a terminating condition that stops the simulation when it reaches 100 customers. This condition is called “Dispose.NumberOut == 100”.

Results:

As you can see above, the waiting time is equal to 1.5550, approximately 1.6 minutes, similar to the original example. Also, the average interarrival time and the time customer spends in the system are 4.3864 and 5.0150 minutes respectively. This is very similar to the 4.24 and 4.83 minutes that are shown in case study 3. Furthermore, the service time of the process is 3.4600 minutes similar to the 3.20 minutes in the excel sheet.

Suggestion for improvement: Our suggestions will decrease the waiting time of this system and try to it more secure. The first improvement will introduce a dispatcher to the system that helps decrease waiting time. This done by notifying that if the queue exceeds the 2 customers, an employee opens a stand by cashier to lower the load on the other cashier, thus decreasing waiting time of the system. Another improvement is adding a security after the checkout to decrease any theft or vandalism that can happen within the grocery store.

A Seize process is added to hold the customer for the routine security check.

The delay process shows the duration a customer is being checked by the security. We decided the check to have a random variable between 1 and 2 minutes.

This process lets go of the customer in the security check to allow him to exit the grocery store.

The dispatcher is an administrate operative that is responsible for allocating resources, should demand increase.

The process holds the extra cashier until the condition is met, which is the checkout is more than 2. Also, there is another hold process block that has a different condition. This condition dismisses the on-call cashier if the queue is equal to zero.

The alter block either adds or dismisses the extra cashier depending on the hold process's condition.

Comparing improved results:

Type

Average Waiting

Average

Time Customer

Average Service

Time

Interarrival Time

Spends in The

Time

System Excel Sheet

1.63 minutes

4.24 minutes

4.83 minutes

3.20 minutes

Prototype 1

1.55 minutes

4.3864 minutes

5.0150 minutes

3.4600 minutes

Improved

0.781 minutes

4.6419 minutes

5.5330 minutes

3.180 minutes

System

We will compare the improved system with prototype 1. As we can see in the table, there is a decrease of approximately 50% waiting time, from 1.55 to 0.781 minutes. The service time in the system has decreased by 0.3 minutes, from 3.46 to 3.180. However, there is an increase in both the interarrival time and time spent in the system, 4.6419 and 5.5330 respectively. We think that this increase in time is necessary to have added security to grocery store against theft or vandalism.

Conclusion:

In conclusion, this project is based on a real life problem that can happen to a local grocery store. There are two problems that the grocery store faces. The first is the long waiting time of customer, and the second is the theft and vandalism that they have been facing. We used arena to improve the system by adding a security after the checkout and a dispatcher that would call another employee to help the cashier when the queue exceeds 2 customers. Although there is an increase in both the interarrival and time spent in system, we think that it is necessary to have added security to grocery store against theft or vandalism. Also, there is a decrease of approximately 50% waiting time, from 1.55 to 0.781 minutes, and service time in the system has decreased by 0.3 minutes, from 3.46 to 3.180.