Control charts are very popular quality tools used to detect and control industrial process deviations in statistical process control. The current paper presents a new triple exponentially weighted moving average (TEWMA) control chart for monitoring the process dispersion (named as $S^2$‐TEWMA chart), based on a three‐parameter logarithmic transformation of the sample variance. A performance evaluation of the proposed chart is conducted, through Monte‐Carlo simulations, in terms of the average run length and the standard deviation of the run length. A comparison study with the $S^2$‐EWMA, CUSUM‐ $S^2$, CS‐EWMA and $S^2$‐HEWMA charts indicates that the $S^2$‐TEWMA chart is more efficient, than the competing ones, in detecting small shifts in the process variability. Finally, two illustrative examples are provided to explain the application of the $S^2$‐TEWMA control chart.

中文翻译：

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新的S2-TEWMA控制图可监控过程分散

控制图是非常流行的质量工具，用于检测和控制统计过程控制中的工业过程偏差。当前论文提出了一种新的三重指数加权移动平均值（TEWMA）控制图，用于监控过程分散（命名为${\mathrm{小号}}^{\mathrm{2个}}$‐TEWMA图表），基于样本方差的三参数对数转换。通过蒙特卡罗模拟，对建议图表的性能进行了评估，包括平均游程长度和游程长度的标准偏差。与${\mathrm{小号}}^{\mathrm{2个}}$‐EWMA，CUSUM‐ ${\mathrm{小号}}^{\mathrm{2个}}$，CS‐EWMA和 ${\mathrm{小号}}^{\mathrm{2个}}$‐HEWMA图表表明 ${\mathrm{小号}}^{\mathrm{2个}}$‐TEWMA图表在检测过程可变性的微小变化方面比竞争图表更为有效。最后，提供了两个说明性示例来解释该应用程序的应用。${\mathrm{小号}}^{\mathrm{2个}}$‐TEWMA控制图。