Minimum control charts

Standard control charts are very sensitive to estimation effects and/or deviations from normality. Hence a program has been carried out to remedy these problems. This is quite adequate in most circumstances, but not in all. In the present paper, the remaining complication is attacked: what to do if a nonparametric approach is indicated, but too few control observations are available for the estimation step? It is shown that grouping the observations during the monitoring phase works well. Surprisingly, rather than using the group averages, it is definitely preferable to compare the minimum for each group to a suitably chosen upper control limit. (And in the two-sided case, also the maximum to an analogous lower control limit.) This ‘minimum control chart’ is demonstrated to be quite attractive: it is easy to explain and to implement. Moreover, while it is truly nonparametric, its power of detection is comparable to that of the customary, normality assuming, charts based on averages.