A new approach to detecting the process changes for multistage systems

• Published in: Expert systems with applications Vol. 62; pp. 293 - 301
• Main Authors: Pan, Jeh-Nan, Li, Chung-I, Wu, Jhe-Jia
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.11.2016
• Subjects: Control charts; Expert systems; Guidelines; Mathematical models; Monitoring; Multistage; Multistage manufacturing system; Overall run length; Oxides; Phase II monitoring; Regression; Residual CUSUM control chart; Residual EWMA control chart; Multistage manufacturing system; Residual CUSUM control chart; Residual EWMA control chart; Overall run length; Phase II monitoring
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2016.06.037

•We provide a new approach to detecting the process changes for multistage systems.•The new multistage residual control charts are based on multiple regression models.•The proposed charts are suitable for monitoring the autocorrelated processes.•The proposed charts can improve the detecting ability in the Phase II monitoring.•A numerical example further demonstrate the usefulness of our proposed charts. The study aims to develop a new control chart model suitable for monitoring the process quality of multistage manufacturing systems. Considering both the auto-correlated process outputs and the correlation occurring between neighboring stages in a multistage manufacturing system, we first propose a new multiple linear regression model to describe their relationship. Then, the multistage residual EWMA and CUSUM control charts are used to monitor the overall process quality of multistage systems. Moreover, an overall run length (ORL) concept is adopted to compare the detecting performance for various multistage residual control charts. Finally, a numerical example with oxide thickness measurements of a three-stage silicon wafer manufacturing process is given to demonstrate the usefulness of our proposed multistage residual control charts in the Phase II monitoring. A computerized algorithm can also be written based on our proposed scheme for the multistage residual EWMA/CUSUM control charts and it may be further converted to an expert and intelligent system. Hopefully, the results of this study can provide a better alternative for detecting process change and serve as a useful guideline for quality practitioners when monitoring and controlling the process quality of multistage systems with auto-correlated data.