A nonparametric EWMA chart with auxiliary information for process mean

In this paper, a new nonparametric exponentially weighted moving average (EWMA) sign chart is constructed with the help of an auxiliary-information-based (AIB) estimator of the process mean, named AIB-EWMA sign chart. The run length characteristics of the proposed control chart are computed using the Markov chain method. Using the bivariate Plackett's distribution, the average run length profiles of the AIB-EWMA sign chart are compared with those of the EWMA sign chart. It turns out that the AIB-EWMA sign chart performs uniformly and substantially better than the EWMA sign chart when detecting different sizes of shift in the process mean.