An Optimal Filter Design Approach to Statistical Process Control

Abstract

Many control charts can be viewed as charting the output of a linear filter applied to process data, with an alarm sounded when the filter output falls outside a set of control limits. We generalize this concept by considering a linear filter in its most general time-invariant form. We provide a strategy for optimizing the filter coefficients in order to minimize the out-of-control ARL, while constraining the in-control ARL to some desired value. The optimal linear filters exhibit a number of interesting characteristics, in particular when the process data are autocorrelated. In many situations, they also substantially outperform an optimally designed exponentially weighted moving average (EWMA) control chart.

• Autocorrelation
• Control Charts
• Linear Filtering
• Markov Chain Method
• Statistical Process Control

Additional information

Notes on contributors

Daniel W. Apley

Dr. Apley is an Associate Professor in the Department of Industrial Engineering and Management Sciences. His email address is [email protected].

Chang-Ho Chin

Dr. Chin is an Assistant Professor in the School of Mechanical and Industrial Systems Engineering. His email address is [email protected].