A regression control chart for autocorrelated processes

Abstract

In this study, we present a new regression control chart which is able to detect the mean shift in a production process. This chart is designed for autocorrelated process observations having a linearly increasing trend. Existing approaches may individually cope with autocorrelated and trending data. The proposed chart requires the identification of trend stationary first order autoregressive (trend AR(1)) model as a suitable time series model for process observations. For a wide range of possible shifts and autocorrelation coefficients, performance of the proposed chart is evaluated by simulation experiments. Average correct signal rate and average run length are used as performance criteria.

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