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Double sampling control charts for monitoring the coefficient of variation

机译:用于监测变异系数的双采样控制图

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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.
机译:变异系数(CV)在监测正常化的分散措施方面是有效的。它广泛应用于均线平均值和标准偏差不是恒定的情况。本文提出了双采样控制图来监视CV(缩写为DS-γ)。开发了DS-γ图表的两个优化算法,即最小化(i)当换档尺寸是先验的换档和(ii)信号的预期平均观察次数时,最小化(i)对信号(ANOS)的平均观察次数。 (EANOS)当换档大小未知时。然后将所提出的图表的性能与标准的CV图进行比较。结果表明,所提出的DS-γ图表显着优于标准的CV图表在检测CV中的所有转变范围内。

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