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Proceedings Paper

Characterization Of Process Variability Using Robust Data Summaries
Author(s): Michael S. Mahaney; G. Rex Bryce
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Paper Abstract

A data summation method is described that employs summary statistics that are relatively insensitive ("robust") to the presence of spurious observations ("outliers"). The method is quick; it is accurate both with and without outliers present; and it is simple for users to understand. It is then shown that these summary statistics can be used to construct variance component estimators, key tools in process improvement and control. The estimators presented are simpler than the conventional variance component estimators and have significantly smaller data storage requirements.

Paper Details

Date Published: 1 January 1988
PDF: 10 pages
Proc. SPIE 0921, Integrated Circuit Metrology, Inspection, and Process Control II, (1 January 1988); doi: 10.1117/12.968375
Show Author Affiliations
Michael S. Mahaney, Intel Corporation (United States)
G. Rex Bryce, Intel Corporation (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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