Exponentially Weighted Moving Average Chart for Skewed Distribution

Abstract

Exponentially weighted moving average (EWMA) control chart can be designed to quickly detect small shifts in the mean of a sequence of independent normal observations. But this chart cannot perform well for skewed distribution. The main goal of this article is to suggest an EWMA control chart method that can be used to monitoring small shifts in a skewed distribution. Weighted variance method is introduced to construct a kind of EWMA chart for skewed distribution and the optimization design of this chart is given by using average run length as a performance assessment criteria. Pair of asymmetry control limits could be evaluated by sample dates in skewed distribution. The advantage of this method in detecting little drift for skewed distribution was illustrated by comparing with others control charts.

A study on the effects of a skewed distribution on the EWMA and MA charts

“…An EWMA control approach was suggested by Hai-yu [8] to monitor small shifts when the underlying distribution is skewed. Amhemad [9] investigated the impacts of non-normality on control charts.…”