Guaranteed in-control control chart performance with cautious parameter learning

Abstract

Parameter estimation has a large impact on control chart performance. Recently, widened control limits have been suggested to guarantee an acceptable in-control behavior. However, the consequence is a reduced ability to detect a real change in the process. In order to overcome this undesired effect, we explore an alternative design based on a delayed updating of parameter estimates. We consider an application to the Shewhart X, EWMA, and CUSUM control charts for the process mean. This approach is simple to implement, reduces the variation of the in-control average run lengths, and significantly improves the out-of-control performance.

Keywords:

• control limits
• estimation effects
• recursive estimation
• statistical process control
• statistical process monitoring

Acknowledgments

The authors thank the referees for their suggestions, which greatly improved the article. In addition, they thank prof. William H. Woodall for many helpful comments on the original manuscript.

Additional information

Funding

The research was partially supported by University of Padua Grant BIRD169985.

Notes on contributors

Giovanna Capizzi

Giovanna Capizzi is an Associate Professor of Statistics at the Department of Statistical Sciences, University of Padua, Italy. She holds a Ph.D. in Statistics from Padua University. Her publications have appeared in referred journals including Environmetrics, IIE Transactions, Journal of Quality Technology, Technometrics, Statistics and Computing. Her current research is focused on change-point models, statistical process monitoring, and quality control.

Guido Masarotto

Guido Masarotto is a Professor of Statistics at the Department of Statistical Sciences, University of Padua, Italy. His current research includes statistical process monitoring and statistical computing. His research has been published in various scientific journals including Biometrika, Biostatistics, Statistics and Computing, Annals of Applied Statistics, IIE Transactions, Journal of Quality Technology, and Technometrics.