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Monitoring Spatial Uniformity of Particle Distributions in Manufacturing Processes Using the K Function

机译:使用K函数监控制造过程中颗粒分布的空间均匀性

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Data in the form of spatial point patterns are frequently encountered in some manufacturing processes such as the nanoparticle reinforced composite materials and defects on semiconductor wafers. Their spatial characteristics contain rich information about the fabrication processes and are often strongly related to the product quality. The distributional characteristics of a spatial point pattern can be summarized by functional profiles such as the popular Ripley's K function. By analyzing the K function, we can effectively monitor the distributional behaviors of the spatial point data. In this study, statistical properties of the K function are investigated, and a Gaussian process is found to be appropriate in characterizing its behavior under complete spatial randomness. A control chart is proposed based on the results to monitor the uniformity of point patterns. Our proposed approach has been compared with existing methods through numerical simulations and shown superior performances.
机译:在某些制造过程中经常会遇到空间点图案形式的数据,例如纳米粒子增强的复合材料和半导体晶圆上的缺陷。它们的空间特性包含有关制造过程的丰富信息,并且通常与产品质量密切相关。空间点图案的分布特征可以通过功能配置文件来概括,例如流行的Ripley's K函数。通过分析K函数,我们可以有效地监视空间点数据的分布行为。在这项研究中,调查了K函数的统计性质,并发现了一个高斯过程适合描述在完全空间随机性下的行为。根据结果​​提出了控制图,以监控点图案的均匀性。通过数值模拟将我们提出的方法与现有方法进行了比较,并显示了优越的性能。

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