Monitoring disturbances in process dispersion using control chart is mostly based on the assumption that the quality characteristic follows normal distribution, which is not the case in many real-life situations. This paper proposes a set of new dispersion charts based on the homogeneously weighted moving average (HWMA) scheme, for efficient detection of shifts in process standard deviation (σ). These charts are based on a variety of σ estimators and are investigated for normal as well as heavy tailed symmetric and skewed distributions. The shift detection ability of the charts is evaluated using different run length characteristics, such as average run length (ARL), extra quadratic loss (EQL), and relative ARL measures. The performance of the proposed HWMA control charts is also compared with the existing EWMA dispersion charts, using different design parameters. Furthermore, an illustrative example is presented to monitor the vapor pressure in a distillation process.

中文翻译：

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应用于蒸馏过程的高效均匀加权分散控制图

使用控制图监控过程分散中的干扰主要基于质量特性遵循正态分布的假设，这在许多实际情况中并非如此。本文提出了一组基于均匀加权移动平均 (HWMA) 方案的新离散图表，用于有效检测过程标准偏差 (σ) 的变化。这些图表基于各种 σ 估计量，并针对正态分布和重尾对称分布和偏态分布进行了研究。图表的偏移检测能力使用不同的运行长度特征进行评估，例如平均运行长度 (ARL)、额外二次损失 (EQL) 和相对 ARL 度量。建议的 HWMA 控制图的性能也与现有的 EWMA 分散图进行了比较，使用不同的设计参数。此外，还提供了一个示例来监测蒸馏过程中的蒸汽压力。