MBPCA application for fault detection in NMOS fabrication

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.