Monitoring of Proportional-Integral Controlled Processes using a Bayesian Time Series Analysis Method

Authors

  • O. Arda Vanli

    Corresponding author
    1. Department of Industrial Engineering, High Performance Materials Institute, Florida A&M University, Florida State University, Tallahassee, FL, USA
    • Correspondence to: Omer Arda Vanli, Department of Industrial Engineering, High Performance Materials Institute, Florida A&M University, Florida State University, Tallahassee, FL, 32310–6046, USA.

      E-mail: oavanli@eng.fsu.edu

    Search for more papers by this author

Abstract

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.

Ancillary