We propose a new control chart, the autoregressive moving average (ARMA) chart, based on monitoring an ARMA statistic of the original observations. It is shown that the special cause chart (SCC) of Alwan and Roberts and the EWMAST chart of Zhang are special cases of the ARMA chart. Simulation studies show that the ARMA chart is competitive to the optimal exponentially weighted moving average chart for iid observations and better than the SCC and EWMAST charts for autocorrelated observations. We develop an informal procedure to determine the appropriate parameter values of the proposed chart based on two signal-to-noise ratios. Two real examples are discussed to demonstrate the advantages of the new chart.
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