Function‐based adaptive exponentially weighted moving average dispersion control chart

Abstract

AbstractIn this study, a new process dispersion monitoring control chart is proposed based on a function‐based adaptation to select the smoothing constant value, named as a function‐based adaptive exponentially weighted moving average (EWMA) dispersion control chart. It is suggested to track shift ranges first expected in process dispersion by opting for smoothing constant computation with the help of a function. The shift magnitude assessment is made by an unbiased estimator that determines the smoothing constant value through the proposed function. The enhanced efficiency of the proposed chart can be assessed in terms of smaller run‐length profiles, which are determined through Monte Carlo simulations. The proposed chart is compared with the existing adaptive EWMA dispersion chart, and it turned out to perform substantially efficiently in detecting all kinds of decreasing and increasing process dispersion shift magnitudes. Moreover, a real‐life dataset application is explained in the example section to elaborate on the ease of implementation in the real‐life scenario.