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In practice, there are processes where the in-control mean and standarddeviation of a quality characteristic is not stable. In such cases, thecoefficient of variation (CV) is a more appropriate measure for assessingprocess stability. In this paper, we consider the statistical design of RunRules based control charts for monitoring the CV of multivariate data. A Markovchain approach is used to evaluate the statistical performance of the proposedcharts. The computational results show that the Run Rules based chartsoutperform significantly the standard Shewhart control chart. Moreover, bychoosing an appropriate scheme, the Run Rules based charts perform better thanthe Rum Sum control chart for monitoring the multivariate CV. An example in aspring manufacturing process is given to illustrate the implementation of theproposed charts.

Monitoring the Multivariate Coefficient of Variation using Run Rules Type Control Charts