Control charts are effective tools for signal detection for both manufacturing and service processes. Much of the data in service industries come from processes exhibiting non-normal or unknown distributions, for which Shewhart variables control charts are not appropriate. This paper thus proposes a new exponentially weighted moving average (EWMA) interquartile range control chart with single sampling and double sampling schemes, respectively, for detecting the out-of-control variance/standard deviation of a critical quality characteristic that exhibits a non-normal or unknown distribution. We explore the sampling properties of the new monitoring statistics, and calculate the average run length of the proposed chart to compare the out-of-control detection performance with existing nonparametric variance charts/standard deviation for cases in which the critical quality characteristic follows the normal and non-normal distributions. Comparison results show that the proposed double sampling EWMA interquartile range control chart exhibits better detection performance than that of the single sampling EWMA interquartile range control chart. Moreover, the former always outperforms existing control charts for small and medium shifts in process variance/standard deviation. Finally, we use a numerical example with service data from a local bank branch to illustrate the application of the proposed control chart.

控制图是用于制造和服务过程的信号检测的有效工具。服务行业中的许多数据来自表现出非正态分布或未知分布的过程，对于这些分布，Shewhart变量控制图不适用。因此，本文提出了一种新的指数加权移动平均值（EWMA）四分位数间距控制图，分别具有单采样和双采样方案，用于检测表现出非正态的关键质量特征的失控方差/标准偏差。或未知的分布。我们探索了新的监控统计数据的抽样属性，并计算建议图表的平均游程长度，以比较临界质量特征遵循正态分布和非正态分布的情况下的失控检测性能与现有非参数方差图/标准偏差。比较结果表明，所提出的双采样EWMA四分位距控制图具有比单采样EWMA四分位距控制图更好的检测性能。此外，对于过程方差/标准偏差的中小变化，前者总是优于现有的控制图。最后，我们使用一个带有本地银行支行服务数据的数值示例来说明所建议的控制图的应用。比较结果表明，所提出的双采样EWMA四分位距控制图具有比单采样EWMA四分位距控制图更好的检测性能。此外，对于过程方差/标准偏差的中小变化，前者总是优于现有的控制图。最后，我们使用一个带有本地银行分支机构的服务数据的数值示例来说明所建议的控制图的应用。比较结果表明，所提出的双采样EWMA四分位距控制图具有比单采样EWMA四分位距控制图更好的检测性能。此外，对于过程方差/标准偏差的中小变化，前者总是优于现有的控制图。最后，我们使用一个带有本地银行支行服务数据的数值示例来说明所建议的控制图的应用。