Graduation Semester and Year

2008

Language

English

Document Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Engineering

First Advisor

Gergely Záruba

Abstract

The temporal behavior of conveyor systems can be modeled using discrete event (DE) simulations. DE modeling provides a quick and cost effective method for analyzing complex problems as different scenarios can be tested rapidly without affecting the day to day activities of production systems. A simulation model coupled with decision optimization on routing choices enables the evaluation of different decision strategies.In the General Motors paint shop at Arlington, Texas, the complex conveyor system moving cars to the paint booths has been observed to mix up same color batches of cars coming from the body shop. At the paint booth, every time two consecutive cars have a different color the paint head needs to be cleaned and primed with the new color; the cost of such paint head changes accumulates to a significant expense annually. By observing the decision making process on the conveyor system it was apparent that better routing decisions could be made, thus reducing the resource wastage.In this work a discrete event based simulation model is developed for the General Motors paint shop conveyor system. The simulation model interacts with a decision optimizer at four critical points in the system trying to regroup batches of different color cars. Simulation results of the current decision making policies are compared to that of the proposed optimized policies, showing that significantly better performance can be achieved in terms of number of paint head changes.

Disciplines

Computer Sciences | Physical Sciences and Mathematics

Comments

Degree granted by The University of Texas at Arlington

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