Publication Date

1993

Document Type

Dissertation/Thesis

First Advisor

Marcellus, Richard L.

Degree Name

M.S. (Master of Science)

Legacy Department

Department of Industrial Engineering

LCSH

Manufacturing processes; Production standards; Production engineering; Dynamic programming

Abstract

This study applies the existing quantitative models of process learning to investigate the economic trade-off associated with the benefits of gradual process improvement. These models describe an imperfect production process which produces defective parts randomly. The defects are indicative of abnormal variations in the process quality. At the end of production of each lot, if defects are discovered, two different policies are considered. One is to invest a small amount to prevent the occurrence of similar defects in subsequent lots by improving the quality of the production process. The other is to continue production of the next lot in the usual manner without any improvement. A stochastic dynamic programming model is used to determine the optimal policy which gives the minimal expected discounted present cost over an infinite horizon. The effects of lost production time spent in gradual process learning and improvement are scrutinized for investigating the economic trade-off between the benefit of process improvement and the cost of lost production time. The model is investigated numerically.

Comments

Includes bibliographical references (pages [80]-82)

Extent

vi, 90 pages

Language

eng

Publisher

Northern Illinois University

Rights Statement

In Copyright

Rights Statement 2

NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.

Media Type

Text

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