A NONPARAMETRIC EXPONENTIALLY WEIGHTED MOVING AVERAGE CONTROL SCHEME

A common assumption when evaluating the properties of Exponentially Wei Moving Average (EWMA) control procedures for controlling the process mean is the observations are normal with known variance. In this article we propose a nonparan control procedure that can be used when the underlying distribution is not knov there is not enough information on the variance or shape of the distribution. Its av run length properties are less affected than the corresponding parametric EV procedure when autocorrelation between the observations is present. The pro nonparametric EWMA procedure is based on Wilcoxon signed-rank statistics ranking is within groups. Our simulation results show that the proposed control proc is less efficient than the parametric X —EWMA procedure when the distribution is no and it can be considerably more efficient than the parametric procedure for heavy-distributions. The proposed procedure is insensitive to misspecification of the val and its ARL properties of the control procedure are affected relatively little by cho the weighting parameter A. © 1991, Taylor & Francis Group, LLC. All rights reserved.