Joint Monitoring of PID-Controlled Processes

Abstract

Statistical process control (SPC) monitoring of the special causes of a process, along with engineering feedback control such as proportional-integral-derivative (PID) control, is a major tool for on-line quality improvement. In this paper, a strategy to jointly monitor the PID-controlled outputs and the manipulated inputs using bivariate SPC is proposed, and a specific design procedure that takes into account both the controller and the disturbance model is provided. The run length properties of the joint monitoring schemes, using Hotelling's approach and Bonferroni's approach, are systematically investigated. The robustness of the proposed monitoring schemes with respect to disturbance model uncertainty is studied, and a decision rule to select an appropriate monitoring scheme is proposed.

• Autocorrelated Process
• Statistical Process Control
• Time Series

Additional information

Notes on contributors

Fugee Tsung

Dr. Tsung is an Assistant Professor in the Department of Industrial Engineering and Engineering Management. He is also a certified Quality Engineer-in-Training. He is a Member of ASQ. His email address is [email protected].

Jianjun Shi

Dr. Shi is an Assistant Professor in the Department of Industrial and Operations Engineering. He is a Member of ASQ.

C. F. J. Wu

Dr. Wu is H. C. Carver Professor and Chair of Statistics and is a Professor of Industrial and Operations Engineering. He is a Senior Member of ASQ.