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Poisson progressive mean control chart

机译:泊松渐进均值控制图

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In real applications, many process-monitoring problems in statistical process control are based on attribute data resulting from quality characteristics that cannot be measured on numerical or quantitative scales. For the monitoring of such data, a new attribute control chart has been proposed in this study, namely, the Poisson progressive Mean (PPM) control chart. The performance of the PPM chart is compared with the existing charts used for the monitoring of Poisson processes such as the Shewhart c-chart, Poisson Exponentially Weighted Moving Average chart, Poisson double Exponentially Weighted Moving Average chart and the Poisson Cumulative Sum charts. The average run length comparison indicated the superior performance of the PPM chart in terms of shift detection ability. This study will help quality practitioners to choose an efficient attribute control chart.
机译:在实际应用中,统计过程控制中的许多过程监视问题都是基于无法在数字或定量尺度上测量的质量特性所产生的属性数据。为了监视此类数据,本研究提出了一种新的属性控制图,即泊松渐进均值(PPM)控制图。将PPM图表的性能与用于监视Poisson过程的现有图表进行比较,例如Shewhart c图,Poisson指数加权移动平均值图表,Poisson双指数加权移动平均值图表和Poisson累积总和图表。平均行程比较表明,在移位检测能力方面,PPM图表具有优越的性能。这项研究将帮助质量从业人员选择有效的属性控制图。

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