Abstract
Autocorrelation or nonstationarity may seriously impact the performance of conventional Hotelling's T2 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 T2 control chart applied to the residuals. The average run length performance of the residual-based Hotelling's T2 chart is compared with the observed data-based Hotelling's T2 chart for a group of first-order vector autoregressive models. We show that the new chart in most cases performs well. Copyright © 2013 John Wiley & Sons, Ltd.
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