Monitoring process variability with individual measurements following elliptically contoured distributions

An exponentially weighted moving average (EWMA) control chart of squared distance is developed by means of a double EWMA approach to monitor process dispersion with individual measurements distributed within the class of elliptically symmetric distributions. Several examples highlighting possible extensions of the control chart to multivariate processes are provided. In particular, for multivariate normal processes, an investigation on the detection power of the chart is carried out through Monte Carlo studies. The results show that the proposed control chart performs well, especially when a process has a small or moderate shift.