Model-based Multivariate Monitoring Charts for Autocorrelated Processes

摘要

Autocorrelation or nonstationarity may seriously impact the performance of conventional Hotelling's T~2 charts. We suggest modeling processes with multivariate autoregressive integrated moving average time series models and propose two model-based monitoring charts. One monitors the predicted value and provides information about the need for mean adjustments. The other is a Hotelling's T~2 control chart applied to the residuals. The average run length performance of the residual-based Hotelling's T~2 chart is compared with the observed data-based Hotelling's T~2 chart for a group of first-order vector autoregressive models. We show that the new chart in most cases performs well.