Adaptive Forecast-Based Monitoring for Dynamic Systems

Abstract

Several forecast-based monitoring methods have been developed for autocorrelated data. One effective method is to use the forecasts based on the exponentially weighted moving average (EWMA). However, during the transition period of dynamic systems, the forecast-based monitoring procedure becomes inadequate due to its use of constant time series model parameters. In this article we present an adaptive forecast-based monitoring approach that performs well on dynamic systems. We examine two competing procedures: the adaptive time series model and the adaptive EWMA. We use a plastic extrusion process with first-order dynamics to illustrate the application of these two procedures, and we also evaluate the performance of the two procedures via simulation.

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