Performance of function-based AEWMA coefficient of variation control chart with measurement errors

Abstract

A new coefficient of variation (CV) functionally adaptive exponentially weighted moving average control chart is presented by considering the influence of the measurement error (ME) and named the "FAEWMA-ME-CV" control chart. The linear covariate model and the multiple measurements method are used to present the control chart. The designed function is efficient to detect the infrequent process changes in the form of parametric shifts in the process CV. The proficiency of the design is evaluated by analyzing the run-length values which are determined by the Monte Carlo simulation runs shown for the various parametric settings in extensive tables. The analysis depicts that the presence of the ME plays a significant role in the performance of a control chart. Moreover, a real-life dataset explained the application of the proposed FAEWMA-ME-CV chart to support the argument.