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Proceedings Paper

Dynamic Statistical Process Control
Author(s): Rahman Azari; Fred Khorasani; Cynthia Bickerstaff
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Paper Abstract

Although some control techniques such as Shewhart and CUSUM Control Charts are not new, their application in industry for process control is relatively new. In recent years manufacturing industries have begun to discover and appreciate the power and efficiency of statistical process control techniques. These charts have been successfully used in some areas and have created confusion in others. The confusion is normally due to incorrect application of the methods and lack of sufficient understanding of the theory and assumptions underlying these charts. One of the important assumptions in using Shewhart and CUSUM charts is that the individual measurements are statistically independent. In many industrial situations this assumption is not valid. Namely, the measurements are correlated. As a result the application of the above techniques ends in incorrect conclusions and hence, confusion. The purpose of this paper is to discuss appropriate methods for dealing with these situations. Time series modeling will be discussed. It will be shown how the correlations in data can be used for more precisely predicting and controlling a process.

Paper Details

Date Published: 1 January 1988
PDF: 12 pages
Proc. SPIE 0921, Integrated Circuit Metrology, Inspection, and Process Control II, (1 January 1988); doi: 10.1117/12.968373
Show Author Affiliations
Rahman Azari, University of California Davis (United States)
Fred Khorasani, Intel Corporation (United States)
Cynthia Bickerstaff, Intel Corporafion (United States)

Published in SPIE Proceedings Vol. 0921:
Integrated Circuit Metrology, Inspection, and Process Control II
Kevin M. Monahan, Editor(s)

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