Author

Payman Jula

Date of Award

8-1996

Degree Name

Master of Science

Department

Industrial and Entrepreneurial Engineering and Engineering Management

Department

Industrial and Manufacturing Engineering

First Advisor

Dr. Azim Houshyar

Second Advisor

Frank Severance

Third Advisor

Richard E. Munsterman

Fourth Advisor

Anil Sawhney

Access Setting

Masters Thesis-Open Access

Abstract

Although there have been many improvements in simulation technology over the past few years, it still suffers from many limitations. Simulation methods are usually time consuming and hence not suitable for the interactive decision making processes.

In this project, applications of Artificial Neural Networks (ANNs) to simulate manufacturing systems have been studied. The backpropagation Multiple Layer Perceptrons (MLPs) have been applied to simulate manufacturing systems. Some guidelines for developing appropriate ANNs have been presented. The results of ANN approach have been compared to those of conventional simulation methods.

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