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Multivariate Process Variability Monitoring Through Projection

机译:通过投影进行多变量过程可变性监控

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Inspired by the recently developed projection chart, such as the U~2 chart for monitoring a shift in the multivariate mean, this article proposes a multivariate projection chart for monitoring process variability. In engineering practice, people often build a linear process model to connect the multivariate quality measurements with a set of fixed assignable causes. The column space of the process model naturally provides a subspace for projection and subsequent monitoring and was indeed used as the projection subspace in the recently developed projection control charts for monitoring a shift the mean. For the purpose of monitoring variability, however, we will show that such a projection may not be advantageous. We propose an alternative projecting statistic, labeled as VS, to be used for constructing a multivariate variability monitoring chart. We show, through extensive numerical studies, that the VS chart entertains several advantages over other competing methods, such as its less restrictive requirements on the process model and generally improved detection performance.
机译:受最近开发的投影图(例如用于监视多元均值变化的U〜2图)的启发,本文提出了一种用于监视过程变异性的多元投影图。在工程实践中,人们通常会建立一个线性过程模型,以将多元质量测量结果与一组固定的可分配原因联系起来。过程模型的列空间自然为投影和后续监视提供了一个子空间,并且确实在最近开发的投影控制图中用作监视子平均值的投影子空间。但是,出于监视可变性的目的,我们将表明这种预测可能不是有利的。我们提出了一种替代的投影统计量,标记为VS,用于构建多元变异性监测图。通过大量的数值研究,我们显示了VS图表比其他竞争方法更具优势,例如,它对过程模型的要求不那么严格,并且总体上提高了检测性能。

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