A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where
nᵢ is the sample size for the ith attribute.
cᵢ is the acceptance number for the ith attribute.
m is the number of attributes.
The expected total cost is denoted by C<sub>T</sub> and can be expressed as
C<sub>T</sub> = E (cost of sampling inspection).
E (cost of accepting the lot).
E (cost of rejecting and scrapping the lot).
E (cost of rejecting and screening the lot).
An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C<sub>T</sub>. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems.
In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit. / Master of Science
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/76385 |
Date | January 1973 |
Creators | McCaslin, James Albert, 1948- |
Contributors | Industrial Engineering and Operations Research |
Publisher | Virginia Polytechnic Institute and State University |
Source Sets | Virginia Tech Theses and Dissertation |
Language | English |
Detected Language | English |
Type | Thesis, Text |
Format | xi, 188 leaves, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Relation | OCLC# 38903423 |
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