Monitoring of Proportional-Integral Controlled Processes using a Bayesian Time Series Analysis Method
Article first published online: 19 JUL 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Quality and Reliability Engineering International
Volume 30, Issue 8, pages 1341–1351, December 2014
How to Cite
2014), Monitoring of Proportional-Integral Controlled Processes using a Bayesian Time Series Analysis Method, Qual. Reliab. Engng. Int., 30, 1341–1351, doi: 10.1002/qre.1555(
- Issue published online: 21 NOV 2014
- Article first published online: 19 JUL 2013
- Manuscript Accepted: 16 JUN 2013
- Manuscript Revised: 13 MAY 2013
- Manuscript Received: 19 APR 2013
- feedback control;
- Bayesian analysis;
- time series modeling
Recently, there has been interest in applying statistical process monitoring methods to processes controlled with feedback controllers in order to eliminate assignable causes and achieve reduced overall variability. In this paper, we propose a Bayesian change-point method to monitor processes regulated with proportional-integral controllers. The approach is based on fitting an exponential rise model to the control input actions in response to a step shift and employs a change-point method to detect the change. Simulation studies show that the proposed method has better run-length performance in detecting step shifts in controlled processes than Shewhart chart on individuals and special-cause chart on residuals of time series model. Copyright © 2013 John Wiley & Sons, Ltd.