MBPCA application for fault detection in NMOS fabrication
Autor: | Sivan Lachman-Shalem, E.N. Shauly, N. Haimovitch, Daniel R. Lewin |
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Rok vydání: | 2002 |
Předmět: |
Multivariate statistics
Engineering business.industry Univariate Condensed Matter Physics Industrial and Manufacturing Engineering Fault detection and isolation Electronic Optical and Magnetic Materials Identification (information) Principal component analysis Electronic engineering Isolation (database systems) Electrical and Electronic Engineering business Energy (signal processing) NMOS logic |
Zdroj: | IEEE Transactions on Semiconductor Manufacturing. 15:60-70 |
ISSN: | 0894-6507 |
DOI: | 10.1109/66.983445 |
Popis: | This paper describes the application of model-based principal component analysis (MBPCA) to the identification and isolation of faults in NMOS manufacture. In MBPCA, multivariate statistics are applied to the analysis of the portion of the data variance that is unexplained by models based on material and energy balances carried out on the unit operations used in manufacture. It is demonstrated that the failure detection and isolation performance achievable using the model-based procedure exceeds that of commonly used univariate SPC or conventional PCA approaches. |
Databáze: | OpenAIRE |
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