Weighted signal-to-noise ratio robust design for a new double sampling npx chart
Weighted signal-to-noise ratio robust design for a new double sampling npx chart
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新双采样 npx 图的加权信噪比稳健设计
DOI：
10.1016/j.cie.2019.106124
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发表时间：
2020
影响因子：
7.9
通讯作者：
Wei Xie
中科院分区：
文献类型：
--
作者：
Wenhui Zhou;Zixuan Wang;Wei Xie
最近，为了通过属性检查来监控过程的均值漂移，提出了一种新的 np 图，称为 np x 图，以综合属性图和变量图的优点。受该图易于实现和良好性能的吸引，本文提出了双采样（DS）np x 图来提高单采样 np x 图的效率。我们建立了一个过程成本模型来比较 DS np x 图和传统 np x 图的性能。为了最大限度地降低不确定性的过程成本，我们引入了一种基于“加权信噪比（WSNR）”的稳健设计方法。具体来说，我们考虑了多种场景的加权期望，并将信噪比视为对方差的响应。与传统设计相比，WSNR鲁棒设计不仅保留了统计优势和经济效率，而且还表现出了灵活性和适应性的优势。然后，进行数值实验来测量我们模型的性能。结果表明，DS np x 图在控制 ARL 1 和工艺成本方面优于 np x 图。通过分析过程成本，我们发现场景范围越大，WSNR鲁棒设计的性能越好。此外，所提出的鲁棒设计的性能相对于现有的鲁棒测量（例如，绝对鲁棒性、鲁棒偏差和相对鲁棒性）具有明显的优势，对于实践者来说，WSNR 将是一种有前景的方法。
Recently, to monitor the mean shifts of a process by using attribute inspection, a new np chart, called np x chart, was proposed to synthesize the advantages of attribute and variable charts. Attracted by the easy-implementation property and good performance of this chart, in this paper, we propose a double-sampling (DS) np x chart to improve the efficiency of the single-sampling np x chart. We build up a process cost model to compare the performance of DS np x chart and the traditional np x chart. To minimize the process cost with uncertainty, we introduce a robust design method based on the “weighted signal-to-noise ratio (WSNR)”. Specifically, we take into account the weighted expectation on multiple scenarios and regard signal-to-noise ratio as a response to variance. Compared to the traditional designs, the WSNR robust design not only preserves the statistical strengths and economic efficiency, but also shows the advantages of flexibility and adaptability. Then, numerical experiments are conducted to measure the performance of our model. The results demonstrate that the DS np x chart is superior to the np x chart in controlling the ARL 1 and the process cost. By analyzing the process cost, we find that the larger the scenario range is, the better the WSNR robust design performs. In addition, the performance of the proposed robust design presents clear advantages to the existing robust measures (eg, absolute robustness, robust deviation, and relative robustness), for which the WSNR will be a promising approach for the practitioners.
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影响因子：
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DOI：
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