Abstract Because the in-control distribution and parameters are generally unknown, control limits have to be estimated using a Phase I reference sample. Because different practitioners obtain different samples, their control limit estimates will vary and, consequently, also their control chart performance. We propose the use of nonparametric tolerance intervals in statistical process monitoring to guarantee a minimum control chart performance with a prespecified probability. We evaluate the performance of the proposed limits for various distributions and sample sizes. Note that this nonparametric set-up includes control charts for location and dispersion. Moreover, we compare the performance with other existing methods involving data transformations and a bootstrap procedure. It turns out that the use of nonparametric tolerance intervals performs very well in statistical process monitoring, especially when moderately large sample sizes are available in Phase I.

中文翻译：

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统计过程监控中条件性能的非参数控制

摘要 由于受控分布和参数通常是未知的，因此必须使用阶段 I 参考样本来估计控制限。因为不同的从业者获得不同的样本，他们的控制限估计会有所不同，因此，他们的控制图性能也会有所不同。我们建议在统计过程监控中使用非参数容差区间，以保证具有预先指定概率的最低控制图性能。我们评估了针对各种分布和样本大小提出的限制的性能。请注意，此非参数设置包括位置和分散的控制图。此外，我们将性能与涉及数据转换和引导程序的其他现有方法进行了比较。