Monitoring of coefficient of variation with function‐based adaptive exponentially weighted moving average control chart

Abstract

AbstractIn this paper, a new adaptive control chart is presented to study the relative process variability, which is called the coefficient of variation (CV). The CV study is the monitoring of a process with an unstable mean value over time. So, a function‐based adaptive exponentially weighted moving average (FAEWMA) CV control chart is proposed to detect the infrequent changes in the process CV, named as “FAEWMA CV” control chart. The function is suggested to adapt the smoothing constant (SC) of the plotting statistic as per arising process shift size in CV. The efficiency is examined through the run‐length values, which are computed through the Monte Carlo (MC) simulation method. The FAEWMA CV chart outperformed the existing AEWMA CV charts. A real‐life example is studied to explain implementation details in the example section.