GOALI/Collaborative Research: Modeling, Monitoring, and Analysis of Spatial Point Patterns for Manufacturing Quality Control

这项学术与工业联络合作研究奖的研究目标是建立一系列空间点模式建模、监测和诊断的质量控制方法。空间点模式是在指定区域内随机分布的一组位置。它是模拟各种制造过程中许多关键质量特征的自然方法，例如钢筋、板和半导体晶圆的表面缺陷，以及复合材料中增强颗粒的分布。研究方法集中在三个重点领域：(i)结合确定性点模式对齐方法和空间统计技术，对重复空间点模式进行建模和监测；根据非参数功能回归模型确定协变量对重复点模式的影响；（iii）将Hough变换方法（一种有趣的计算机视觉方法）引入质量控制领域，进行几何和三维点模式检测。如果成功，本研究结果将为轧钢、半导体制造和复合材料制造等相关行业提供一套新颖的质量控制工具。这些工具将利用日益可用的空间点数据，并有助于显著提高过程生产率和质量。与OG Technologies在这个“学术与工业联络资助机会”项目上的密切合作，将带来一个现实的测试平台，并在实践者之间迅速传播研究成果，以及启动技术转让。这个项目的跨学科性质可以为学生提供独特的机会，获得空间统计，制造质量控制和计算机视觉方面的培训。

The research objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) collaborative research award is to establish a series of quality control methodologies on modeling, monitoring, and diagnosis of spatial point patterns. A spatial point pattern is a set of locations randomly distributed within a designated region. It is a natural way to model many critical quality characteristics in various manufacturing processes, such as the surface defects on steel bars, slabs and semiconductor wafer, and the distribution of reinforce particles in composite materials. The research approach is in three focus areas: (i) Modeling and monitoring of replicated spatial point patterns by integrating the deterministic point pattern alignment methods and spatial statistics techniques; (ii) Identification of the impacts of covariates on replicated point patterns based on a nonparametric functional regression model; and (iii) Geometric and three-dimension point pattern detection by bringing the Hough Transform method, an interesting computer vision method, into the quality control area.If successful, the results of this research will provide a novel set of quality control tools to various relevant industries such as steel rolling, semiconductor manufacturing, and composite fabrication. These tools will take advantage of the increasingly available spatial point data and help to significantly improve the process productivity and quality. The close collaboration with OG Technologies in this Grant Opportunities for Academic Liaison with Industry project will lead to a realistic testbed and quick dissemination of research results among practitioners, as well as initiation of technology transfer. The interdisciplinary nature of this project can provide students the unique opportunity to obtain training in spatial statistics, manufacturing quality control, and computer vision.