The typical industrial enterprise has, to a large degree, been slow in accepting and implementing statistical principles in an overall program designed to improve the efficiency of the enterprise and its included functions. Where statistical principles are used, they are for the most part limited to purely mechanical functions involving specific machinery applications.
This thesis proposes that the limited use of statistical principles in purely mechanical applications makes use of only a small portion of the potential benefits available through more effective use of the principles involved in the science called Statistical Quality Control. This thesis proposes that through a systematic training program, beginning with use of control chart techniques in day to day operations, the responsible individuals comprising the four business functions, Specification, Production, Inspection, and Sales, may be made to realize the importance of the statistical term capability~of-process. Once the four functions are familiar with the true meaning of capability-of-process, this thesis proposes that the four functions will be better equipped to operate inter-functionally and intra-functionally in a controlled manner. The obvious advantage in operating within an overall capability-of-process framework lies in the ability of the users of such a system to attain realistic goals whether they be in the form of specifications or otherwise. Also of importance is the ability to know within predictable limits what may be expected from processes. This thesis proposes that processes must be defined in a broad sense to include the human, or, the organizational aspects involved in the enterprise.
For illustrative purposes, a typical production foundry-machine shop complex was used for research data supporting the thesis. The research data results from a six year association of the researcher with the example enterprise. / Master of Science
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/33797 |
Date | 28 June 2006 |
Creators | Carter, William Daniel |
Contributors | Industrial and Systems Engineering, Smith, Roger D., Gilbreath, Sidney G. III, Torgersen, Paul E. |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Thesis, Text |
Format | 192 leaves, application/pdf, application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Relation | OCLC# 20395182, LD5655.V855_1967.C373.pdf |
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