Monitoring multi-stage sequential manufacturing processes: a Bayesian approach

Author

Rao, Suraj ; Strojwas, Andrzej ; Lehoczky, John ; Schervish, Mark

Author_Institution

Dept. of Stat., Carnegie Mellon Univ., Pittsburgh, PA, USA

fYear

1995

fDate

17-19 Sep 1995

Firstpage

182

Lastpage

186

Abstract

We have developed a process monitoring system, in a Bayesian framework, which is designed to be used for monitoring VLSI and other multi-stage manufacturing processes. For a single-step process, the Bayesian monitor is at least as good as the Shewhart-CUSUM charts for detecting changes in the distribution of the in-lines collected from the step. For a multi-stage process, however, the Bayesian monitor can significantly reduce the detection time by using in-line correlation information from earlier stages

Keywords

Bayes methods; Monte Carlo methods; integrated circuit manufacture; monitoring; process control; Bayesian framework; CMOS fabrication; Monte Carlo simulation; Shewhart-CUSUM charts; VLSI manufacturing; in-line correlation information; in-line distribution; multi-stage sequential manufacturing processes; process monitoring system; Additive noise; Bayesian methods; Computerized monitoring; Condition monitoring; Control charts; Manufacturing processes; Predictive models; Semiconductor device modeling; Statistics; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Semiconductor Manufacturing, 1995., IEEE/UCS/SEMI International Symposium on

Conference_Location

Austin, TX

Print_ISBN

0-7803-2928-7

Type

conf

DOI

10.1109/ISSM.1995.524386

Filename

524386