Chart for Monitoring Univariate Autocorrelated Processes

I N recent years, statistical process control (SPC) for autocorrelated processes has received a great deal of attention, due in part to the increasing prevalence of autocorrelation in process inspection data. With improvements in measurement and data collection technology, processes can be sampled at higher rates, which often leads to data autocorrelation. It is well known that the run length properties of common SPC methods like CUSUM and X charts are strongly affected by data autocorrelation, and the in-control average run length (ARL) can be much shorter than intended if the autocorrelation is positive (Johnson and Bagshaw (1974) and Vasilopoulos and Stamboulis (1978)).