Abstract
Monitoring the coefficient of variation (CV) is of interest when there is a constant proportion between the varying standard deviation and the varying mean in the process. In a multivariate process, monitoring the multivariate CV (MCV) is useful to assess the relative variability of the process. With the aim to improve the existing MCV charts’ performance, this paper develops two one-sided cumulative sum (CUSUM) charts for monitoring the MCV. Based on the Markov chain model, some run length (RL) measures are evaluated and used to show the superiority of the proposed charts over the competing MCV charts under the deterministic shift. Moreover, when the shift size is unknown in practice, the performance of the proposed CUSUM MCV charts is evaluated. Finally, an example is provided to show the implementation of the proposed CUSUM MCV charts.
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