Double sampling control charts for monitoring the coefficient of variation

Abstract

The coefficient of variation (CV) is effective in monitoring the normalized measure of dispersion. It is extensively applied in the situations where the mean and standard deviation are not constant for all time. In this paper, the double sampling control chart is proposed to monitor the CV (abbreviated as DS-γ). Two optimization algorithms of the DS-γ chart are developed, i.e., to minimize (i) the average number of observations to signal (ANOS) when the shift size to be known a priori and (ii) the expected average number of observations to signal (EANOS) when the shift size is unknown. The proposed chart's performance is then compared with the standard CV chart. The results show the proposed DS-γ chart significantly outperforms the standard CV chart in the detection of all ranges of shifts in the CV.

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