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The Generally Weighted Moving Average Control Chart for Detecting Small Shifts in the Process Mean

机译:用于检测过程均值中微小变化的一般加权移动平均控制图

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摘要

A generalization of the exponentially weighted moving average (EWMA) control chart is proposed and analyzed. The generalized control chart we have proposed is called the generally weighted moving average (GWMA) control chart. The GWMA control chart, with time-varying control limits to detect start-up shifts more sensitively, performs better in detecting small shifts of the process mean. We use simulation to evaluate the average run length (ARL) properties of the EWMA control chart and GWMA control chart. An extensive comparison reveals that the GWMA control chart is more sensitive than the EWMA control chart for detecting small shifts in the mean of a process. To enhance the detection ability of the GWMA control chart, we submit the composite Shewhart-GWMA scheme to monitor process mean. The composite Shewhart-GWMA control chart with/without runs rules is more sensitive than the GWMA control chart in detecting small shifts of the process mean. The resulting ARLs obtained by the GWMA control chart when the assumption of normality is violated are discussed.
机译:提出并分析了指数加权移动平均(EWMA)控制图的一般化。我们提出的广义控制图称为一般加权移动平均(GWMA)控制图。 GWMA控制图具有随时间变化的控制范围,可以更灵敏地检测启动偏移,在检测过程平均值的较小偏移方面表现更好。我们使用仿真来评估EWMA控制图和GWMA控制图的平均运行长度(ARL)属性。广泛的比较显示,GWMA控制图比EWMA控制图更灵敏,可检测过程平均值的微小变化。为了提高GWMA控制图的检测能力,我们提交了复合Shewhart-GWMA方案来监视过程均值。具有/不具有运行规则的合成Shewhart-GWMA控制图在检测过程平均值的微小变化时比GWMA控制图更敏感。讨论了当违反正常性假设时,通过GWMA控制图获得的最终ARL。

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