Efficient Control Charts for Monitoring Process CV Using Auxiliary Information

Coefficient of variation (CV) control charts are a suitable choice for the monitoring of variation in cases when the process standard deviation is proportional to the process mean. This study is aimed at enhancing the detection ability of usual CV chart by incorporating the use of auxiliary information. In recent years, researchers investigated the use of auxiliary information for improving the sensitivity of location and dispersion charts. However, no study has investigated the CV control charts in presence of auxiliary information. In this study, I propose and investigate a set of auxiliary information based charts for efficient monitoring of process CV by considering a variety of CV estimators. The auxiliary information is used in terms of regression, ratio and hybrid forms. A real life example concerning the monitoring of air quality is also presented to illustrate the application of proposed charts.