THE ROBUSTNESS OF THE SYNTHETIC CONTROL CHART TO NON-NORMALITY

Abstract

The Synthetic control chart has recently been introduced as an improvement over the standard Shewhart control chart for detecting changes in the mean of a normally distributed process. The salient features of the Shewhart chart and the Conforming Run Length chart are integrated to produce the Synthetic control chart. In many practical instances, the Synthetic chart is superior to the Shewhart chart in terms of quicker detection of out-of-control status when the process data are normally distributed. The robustness of the Synthetic chart to violations of the normality assumption is the central theme of this study. We find that in-control average run lengths for the Synthetic chart are reasonably close to the normal theory values when there is moderate nonnormality or when the sample size n is large. Additionally, out-of-control average run lengths are comparable to the corresponding normal theory values for a variety of non-normal distributions.