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Proceedings Paper

Fuzzy inference system for semiconductor manufacturing processes
Author(s): Raymond L. Chen; Costas J. Spanos
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Paper Abstract

A systematic approach is presented for modeling qualitative properties in semiconductor manufacturing processes. This approach is based on the fuzzy logic theory, and on the statistical analysis of categorical data. A fuzzy inference system can be designed and created by training data obtained either from human expert knowledge, or automatically extracted from statistically designed experiments. Before being used to design the fuzzy system, the data extracted from the designed experiments can be processed and filtered with the help of linear and logistic regression analysis. After the establishment of the initial inference system, the fuzzy membership functions can be tuned adaptively to accommodate process changes.

Paper Details

Date Published: 13 June 1995
PDF: 14 pages
Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); doi: 10.1117/12.211810
Show Author Affiliations
Raymond L. Chen, Univ. of California/Berkeley (United States)
Costas J. Spanos, Univ. of California/Berkeley (United States)


Published in SPIE Proceedings Vol. 2493:
Applications of Fuzzy Logic Technology II
Bruno Bosacchi; James C. Bezdek, Editor(s)

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