Design of Exponentially Weighted Moving Average Control Charts for Autocorrelated Processes With Model Uncertainty

Residual-based control charts are popular methods for statistical process control of autocorrelated processes. To implement these methods, a time series model of the process is required. The model must be estimated from data, in practice, and model estimation errors can cause the actual in-control average run length to differ substantially from the desired value. This article develops a method for designing residual-based exponentially weighted moving average (EWMA) charts under consideration of the uncer tainty in the estimated model parameters. The resulting EWMA control limits are widened by an amount that depends on a number of factors, including the level of model uncertainty.