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

GOALI/协作研究：用于制造质量控制的空间点模式的建模、监控和分析

• 批准号: 1161077
• 负责人: Shiyu Zhou
• 金额: $ 20.24万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1161077&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Modeling; Monitoring

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.

该研究项目的研究目标是建立一系列关于空间点模式建模、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。这是一种自然的方式来模拟各种制造过程中的许多关键质量特性，例如钢筋，板坯和半导体晶片上的表面缺陷，以及复合材料中增强颗粒的分布。研究方法主要有三个方面：（1）通过整合确定性点模式对齐方法和空间统计技术，对重复的空间点模式进行建模和监测;（2）基于非参数函数回归模型，识别协变量对重复点模式的影响;以及（iii）通过将Hough变换方法（一种有趣的计算机视觉方法）引入质量控制领域来进行几何和三维点图案检测。如果成功，本研究的成果将提供一套新颖的品质控制工具给各种相关产业，例如轧钢、半导体制造、以及复合材料制造。这些工具将利用日益可用的空间点数据，并有助于显著提高流程的生产率和质量。与OG技术在这个赠款机会学术联络与行业项目的密切合作将导致一个现实的试验台和研究成果的快速传播从业人员，以及启动技术转让。该项目的跨学科性质可以为学生提供获得空间统计，制造质量控制和计算机视觉培训的独特机会。