Fuzzy inference system for semiconductor manufacturing processes

Raymond L. Chen; Costas J. Spanos

doi:10.1117/12.211810

13 June 1995 Fuzzy inference system for semiconductor manufacturing processes

Raymond L. Chen, Costas J. Spanos

Proceedings Volume 2493, Applications of Fuzzy Logic Technology II; (1995) https://doi.org/10.1117/12.211810
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Raymond L. Chen and Costas J. Spanos "Fuzzy inference system for semiconductor manufacturing processes", Proc. SPIE 2493, Applications of Fuzzy Logic Technology II, (13 June 1995); https://doi.org/10.1117/12.211810

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