Control charts play a vital role in tracing unfavorable changes in the ongoing process parameters to enhance the quality of the output. Attribute charting schemes are commonly utilized for tracing shifts in fraction nonconforming and number of nonconformities per unit in any production process. A double progressive mean charting structure for monitoring Poisson observations (PDPM) is recently proposed by Alevizakos and Koukouvinos¹ for efficient monitoring of the average number of nonconformities in the production unit. Unfortunately, the variance expression used in the charting statistic of the said article needs correction. The focus of this study is to provide correct derivation and expression of the variance of the PDPM statistic.

中文翻译：

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用于监测泊松观测的双渐进平均统计量方差的正确表达

控制图在跟踪正在进行的过程参数的不利变化以提高输出质量方面起着至关重要的作用。属性图表方案通常用于跟踪任何生产过程中不合格部分和每单位不合格数量的变化。Alevizakos 和 Koukouvinos ¹最近提出了一种用于监测泊松观测 (PDPM) 的双渐进平均图表结构，用于有效监测生产单元中的平均不合格数。不幸的是，上述文章的图表统计中使用的方差表达式需要更正。本研究的重点是提供 PDPM 统计量方差的正确推导和表达。