Publication Date

1992

Document Type

Dissertation/Thesis

First Advisor

Marcellus, Richard L.

Degree Name

M.S. (Master of Science)

Department

Department of Industrial Engineering

LCSH

Process control||Bayesian statistical decision theory||Sampling (Statistics)

Abstract

This study compares Cumulative Sum charts and Bayesian process control based on statistical quantities and minimal expected cost. The production process model and the procedure for the design of the two models is examined. Following the theoretical development, a numerical analysis is performed for both models. In the analysis, the optimal policies are determined and the sensitivity of the policies to changes in the model parameters is explored. Comparison between the two models is also made to see their relative performance. The results of the numerical study indicate that Cumulative Sum charts and Bayesian process control are about the same in detecting a lack of control and that optimal Cumulative Sum charts and optimal Bayesian process control are equally effective based on the minimum expected cost criterion.

Comments

Includes bibliographical references (pages 62-63)

Extent

viii, 106 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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