Title :
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
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;
Conference_Titel :
Semiconductor Manufacturing, 1995., IEEE/UCS/SEMI International Symposium on
Conference_Location :
Austin, TX
Print_ISBN :
0-7803-2928-7
DOI :
10.1109/ISSM.1995.524386
