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Proceedings Paper

Parallel abstraction of software architecture and statistical principles for tighter process control
Author(s): Rob Firmin
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Paper Abstract

Process control in the fab today employs a wide range of techniques to gather data, monitor processes and adjust through feed-forward and feed-back. This paper proposes that many substantial benefits could be derived from a broad abstraction of process control statistics algorithms as well as of data collection and distribution, in a manner parallel to how software users benefit from object oriented concepts. The abstracted algorithmic approach is based on statistics fundamentals. The paper first defines abstraction and discusses the benefits of its application to process control. It then defines a statistics experiment to test EWMA as one example of how a popular contemporary process control practice can misbehave when faced with four specific data attributes. The experiment quantifies the limitations of EWMA, and indicates that its performance is greatly enhanced when the more fundamental approach pre-processes its data. EWMA is not being singled out results are generalizable to other methods. The last two sections summarize findings and draw conclusions.

Paper Details

Date Published: 1 July 2003
PDF: 12 pages
Proc. SPIE 5044, Advanced Process Control and Automation, (1 July 2003);
Show Author Affiliations
Rob Firmin, Foliage Software Systems, Inc. (United States)

Published in SPIE Proceedings Vol. 5044:
Advanced Process Control and Automation
Matt Hankinson; Christopher P. Ausschnitt, Editor(s)

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