The coefficient of variation (CV) is an important quality characteristic when the process variance is a function of the process mean for a production process. In this paper, we develop an auxiliary information–based (AIB) estimator for estimating the squared CV, along with its approximated mean and variance. This estimator is then used to devise new one‐sided EWMA charts for monitoring the increases or decreases in the squared CV of a normal process, named the AIB‐EWMA CV charts. In addition, the sensitivities of these control charts are also enhanced with the fast initial response feature. The Monte Carlo simulation method is used to compute the run length characteristics of the proposed CV charts. Based on detailed run length comparisons, it is found that the proposed AIB‐EWMA CV charts are uniformly and substantially better than the existing EWMA CV charts when detecting different kinds of upward/downward shifts in the squared CV. The proposed charts are also applied to a real dataset to support the proposed theory.

中文翻译：

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增强的EWMA图表，用于监视过程变异系数

当过程差异是生产过程的过程平均值的函数时，变异系数（CV）是重要的质量特征。在本文中，我们开发了一种基于辅助信息的（AIB）估计器，用于估计平方CV及其近似均值和方差。然后，此估算器用于设计新的单面EWMA图，以监视正常过程的平方CV的增加或减少，称为AIB-EWMA CV图。此外，这些控制图的敏感性也通过快速的初始响应功能得到了增强。蒙特卡罗模拟方法用于计算所提出的CV图的游程长度特征。根据详细的行程比较，我们发现，在检测平方CV中不同类型的上/下移位时，建议的AIB-EWMA CV图均匀且显着优于现有EWMA CV图。拟议的图表还应用于实际数据集以支持拟议的理论。