MBPCA application for fault detection in NMOS fabrication

Author

Lachman-Shalem, Sivan ; Haimovitch, Nir ; Shauly, Eitan N. ; Lewin, Daniel R.

Author_Institution

Dept. of Chem. Eng., Technion-Israel Inst. of Technol., Haifa, Israel

Volume

15

Issue

1

fYear

2002

fDate

2/1/2002 12:00:00 AM

Firstpage

60

Lastpage

70

Abstract

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

Keywords

MOS integrated circuits; fault diagnosis; integrated circuit manufacture; principal component analysis; MBPCA application; NMOS fabrication; data variance; fault detection; fault identification; fault isolation; model-based principal component analysis; model-based procedure; multivariate statistics; unit operations; Fabrication; Fault detection; Fault diagnosis; MOS devices; Monitoring; Network-on-a-chip; Ovens; Principal component analysis; Statistical analysis; Virtual manufacturing;

fLanguage

English

Journal_Title

Semiconductor Manufacturing, IEEE Transactions on

Publisher

ieee

ISSN

0894-6507

Type

jour

DOI

10.1109/66.983445

Filename

983445