A robust approach to dynamic statistical process control

Abstract

Statistical process control (SPC) techniques are well established across a wide range of industries. In particular, the plotting of key steady state (product) variables with their statistical limits against time (Shewart charting) is a common approach for monitoring the normality of production. There has been increased interest in SPC applied to the monitoring of dynamic processes. This paper is concerned with extending Shewart charting techniques to the quality monitoring of variables driven by uncertain dynamic processes, which has particular application in the process industries where it is desirable, to monitor process variables online as well as the final product. The robust approach to dynamic statistical process control proposed in this paper is based on work on guaranteed cost filtering for linear systems and is intended to provide a basis for both a wider application of SPC monitoring and also motivate unstructured fault detection.