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
基本信息
- 批准号:1161350
- 负责人:
- 金额:$ 18.75万
- 依托单位:
- 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:
- 关键词:
项目摘要
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。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Yong Chen其他文献
Predictions for Central Lymph Node Metastasis of Papillary Thyroid Carcinoma via CNN-Based Fusion Modeling of Ultrasound Images
通过基于 CNN 的超声图像融合模型预测甲状腺乳头状癌中央淋巴结转移
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:1.9
- 作者:
Yong Chen;Yan;Z. Cai;Mian Jiang - 通讯作者:
Mian Jiang
Shock mitigation effects of cellular cladding on submersible hull subjected to deep underwater explosion
多孔包壳对深水下爆炸作用下潜水器的冲击缓解效果
- DOI:
10.1016/j.oceaneng.2016.03.037 - 发表时间:
2016-05 - 期刊:
- 影响因子:5
- 作者:
Caiyu Yin;Zeyu Jin;Yong Chen;Hongxing Hua - 通讯作者:
Hongxing Hua
Algorithm-level Feedback-controlled Adaptive data prefetcher: Accelerating data access for high-performance processors
算法级反馈控制自适应数据预取器:加速高性能处理器的数据访问
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:1.4
- 作者:
Yong Chen;Huaiyu Zhu;Hui Jin;Xian - 通讯作者:
Xian
Experimental investigation on the characteristics of maximum bubble size of subcooled flow boiling in narrow rectangular channel under different system pressure
不同系统压力下窄矩形通道过冷流沸腾最大气泡尺寸特性的实验研究
- DOI:
10.1016/j.ijheatmasstransfer.2021.121426 - 发表时间:
2021-09 - 期刊:
- 影响因子:5.2
- 作者:
Lin Zhang;Hanzhou Liu;Deqi Chen;Xiaowei Zhou;Yong Chen - 通讯作者:
Yong Chen
Determination of FCMC and SCMC and Speculation of Hexagonally Packed Rods Concentration and Palisade Layer Structure Concentration of SDBS and SDS by Ultraviolet-visible Spectrophotometry
紫外可见分光光度法测定FCMC和SCMC以及六方堆积棒浓度和SDBS和SDS栅栏层结构浓度的推测
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:1
- 作者:
Zhaoxi Huang;Fenghui Zhao;Min Liu;Yong Chen - 通讯作者:
Yong Chen
Yong Chen的其他文献
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{{ truncateString('Yong Chen', 18)}}的其他基金
Collaborative Research: Fusion of Siloed Data for Multistage Manufacturing Systems: Integrative Product Quality and Machine Health Management
协作研究:多级制造系统的孤立数据融合:集成产品质量和机器健康管理
- 批准号:
2323084 - 财政年份:2024
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
Conference: 2024 Manufacturing Science and Engineering Conference and 52nd North American Manufacturing Research Conference; Knoxville, Tennessee; 17-21 June 2024
会议:2024年制造科学与工程会议暨第52届北美制造研究会议;
- 批准号:
2344983 - 财政年份:2023
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
Quantum Many-Body Physics in Spin-Orbit Coupled Bose Gases
自旋轨道耦合玻色气体中的量子多体物理
- 批准号:
2012185 - 财政年份:2020
- 资助金额:
$ 18.75万 - 项目类别:
Continuing Grant
Phase-II IUCRC Texas Tech University: Center for Cloud and Autonomic Computing
第二阶段 IUCRC 德克萨斯理工大学:云和自主计算中心
- 批准号:
1939140 - 财政年份:2020
- 资助金额:
$ 18.75万 - 项目类别:
Continuing Grant
Collaborative Research: CESER: EAGER: "FabWave" - A Pilot Manufacturing Cyberinfrastructure for Shareable Access to Information Rich Product Manufacturing Data
合作研究:CESER:EAGER:“FabWave”——用于共享访问信息丰富的产品制造数据的试点制造网络基础设施
- 批准号:
1812675 - 财政年份:2018
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
CSR: Small: Collaborative Research: Tuning Extreme-scale Storage Stack through Deep Reinforcement Learning
CSR:小型:协作研究:通过深度强化学习调整超大规模存储堆栈
- 批准号:
1817094 - 财政年份:2018
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
Elements:Software:NSCI: Empowering Data-driven Discovery with a Provenance Collection, Management, and Analysis Software Infrastructure
元素:软件:NSCI:通过来源收集、管理和分析软件基础设施支持数据驱动的发现
- 批准号:
1835892 - 财政年份:2018
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
Collaborative Research: Strain Based Devices for Switches and Memory Applications
合作研究:用于开关和存储器应用的基于应变的器件
- 批准号:
1711332 - 财政年份:2017
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
SHF: Small: Collaborative Research: Uncovering Vulnerabilities in Parallel File Systems for Reliable High Performance Computing
SHF:小型:协作研究:发现并行文件系统中的漏洞以实现可靠的高性能计算
- 批准号:
1718336 - 财政年份:2017
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
Additive Manufacturing of Controlled Anisotropic Materials via Electrically Assisted Nanocomposite Fabrication
通过电辅助纳米复合材料制造受控各向异性材料的增材制造
- 批准号:
1663663 - 财政年份:2017
- 资助金额:
$ 18.75万 - 项目类别:
Standard Grant
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