Research Reports from the Department of Operations
Document Type
Dissertation
Publication Date
8-1-1985
Abstract
There are many good techniques, whose developments are based on sound statistical and economic considerations, available for use in the design of Univariate Quality Control (UQC). Despite their familiarities and popularities in UQC, many of these techniques have not been adopted for use in Multivariate Quality Control (MQC). In this dissertation, we have classified the various design techniques used for Shewhart's plan into two parts, viz: 1) the hypothesis testing approach, and 2) the optimization approach. A few good design techniques in the two categories above have been thoroughly modified and extended for the design of MQC plans. Under the Hypothesis Testing Approach: (a) Given the producers' and the consumers' risks and their corresponding quality levels, we have developed techniques for designing MQC plans involving two variables and for drawing the corresponding O-C curves. (b) Various designs based on power function criterion, namely, (i) Knappenburger's technique, and (ii) Rao's average run-length methods have been thoroughly modified and extended for the design of MQC plans. Under the Optimization Approach, the following MQC models have been thoroughly modified and extended for the design of MQC plans: (a) the Duncan's Single Cause model, (b) his Multiple Cause model (c) the Chiu-Taylor's Economic model. Some of the computational algorithms applied to these models have also been thoroughly modified for use in our MQC problems. The performances of the MQC and UQC plans have been compared under each of the design techniques considered. One of the interesting results we have come out with is that the MQC plans are consistently far superior to the UQC plans. The economic models we worked with were also compared. In terms of cost-effectiveness, it came out that the Duncan's Multiple Cause model is better than the Chiu-Taylor's model while the latter is better than the Duncan's Single Cause model.
Keywords
Operations research, Quality control--Statistical methods, Multivariate analysis, Statistical hypothesis testing, Industrial efficiency, Mathematical optimization
Publication Title
Dissertation/Technical Memorandums from the Department of Operations, School of Management, Case Western Reserve University
Issue
Technical memorandum no. 563 ; Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy.
Rights
This work is in the public domain and may be freely downloaded for personal or academic use
Recommended Citation
Jolayemi, Joel K., "Multivariate Quality Control : an Hypothesis Testing and Optimization Approach to Effective Use and Measure of Performance" (1985). Research Reports from the Department of Operations. 329.
https://commons.case.edu/wsom-ops-reports/329