Abstract

A simulation based decision support system is developed for AT&T Microelectronics in Orlando. This system uses simulation modeling to capture the complex nature of semiconductor test operations. Simulation, however, is not a tool for optimization by itself. Numerous executions of the simulation model must generally be performed to narrow in on a set of proper decision parameters. As a means of alleviating this shortcoming, artificial neural networks are used in conjunction with simulation modeling to aid management in the decision making process. The integration of simulation and neural networks in a comprehensive decision support system, in effect, learns the reverse of the simulation process. That is, given a set of goals defined for performance measures, the decision support system suggests proper values for decision parameters to achieve those goals.

Graduation Date

1994

Semester

Spring

Advisor

Mollaghasemi, Mansooreh

Degree

Master of Science (M.S.)

College

College of Engineering

Department

Industrial Engineering and Mangement Systems

Degree Program

Industrial Engineering

Format

PDF

Language

English

Rights

Written permission granted by copyright holder to the University of Central Florida Libraries to digitize and distribute for nonprofit, educational purposes.

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Identifier

DP0011935

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