Collaborative Research: Experimental Design and Analysis of Quantitative-Qualitative Responses in Manufacturing and Biomedical Systems

协作研究：制造和生物医学系统中定量-定性响应的实验设计和分析

基本信息

批准号：
1435902
负责人：
Lulu Kang
金额：
$ 11.79万
依托单位：
Illinois Institute of Technology
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-01 至 2018-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1435902&HistoricalAwards=false
关键词：
Collaborative Research Experimental Design Analysis

项目摘要

The research objective of this award is to establish a set of experimental design, analysis, and quality control methodologies for systems with both quantitative and qualitative (QQ) responses. Systems with QQ responses are commonly encountered in various manufacturing and biomedical applications. For example, in a thermal spray coating process, the coating quality is often measured by quantitative surface roughness and a qualitative coating failure indicator. Another example can be found in an organ transplant process, where the quantitative biopsy testing scores and doctors, qualitative evaluation are used to evaluate the health condition of the organ. The new methodologies are based on a joint modeling of the QQ responses to unveil the hidden relationship between the two types of the responses, and thus are more advantageous than the traditional methods that model the two types of responses separately. These methodologies will be tested and implemented in real case studies provided by industrial collaborators. The education plan will promote undergraduate and graduate students from the underrepresented groups to obtain the rigorous quality control training in various manufacturing and biomedical applications. The research results will be used to improve the quality in real industrial practices. If successful, this research will lead to effective and reliable modeling, experimental design, monitoring and control of the systems with QQ responses. The joint modeling method considers constrained likelihood estimation with joint variable selection. It will further accommodate various complex scenarios including functional predictors, missing values, multiple responses, and nonlinear quality-process relationship. A Bayesian optimal design of QQ responses is planned to address the experimental design needs, which can be extended to sequential designs and designs for robust systems. Based on the modeling method, the model-oriented process monitoring will detect process changes, and identify root causes from the predictors or from the system itself. The quality improvement will be fulfilled by optimizing objectives accounting for the hidden relationship between the QQ responses. These methodologies will serve a set of powerful tools for manufacturing scale-up and biomedical quality improvement. Moreover, the educational plan will provide undergraduate and graduate students with various course modules and research opportunities. Real case studies will be used in lab sessions and undergraduate capstone projects. The research will equip students with critical thinking and hands-on skills in applied statistics, manufacturing, and biomedical systems. Research results will also be disseminated to academia and industry through publications, conferences, and workshops. A website will be established to share data, case studies, and advanced tools for promoting research collaboration.

该奖项的研究目标是为具有定量和定性响应的系统建立一组实验设计，分析和质量控制方法。具有QQ响应的系统在各种制造和生物医学应用中通常会遇到。例如，在热喷涂过程中，通常通过定量表面粗糙度和定性涂层破坏指标来测量涂料质量。可以在器官移植过程中找到另一个示例，其中定量活检测试评分和医生，定性评估用于评估器官的健康状况。新方法基于QQ响应的联合建模，以揭示两种响应类型之间的隐藏关系，因此比分别对两种类型的响应进行建模的传统方法更有利。这些方法将在工业合作者提供的实际案例研究中进行测试和实施。该教育计划将促进来自代表性不足的团体的本科生和研究生，以获得各种制造和生物医学应用中严格的质量控制培训。研究结果将用于提高实际工业实践的质量。如果成功，这项研究将导致具有QQ响应的系统的有效和可靠的建模，实验设计，监视和控制系统。联合建模方法考虑了与关节变量选择的限制可能性估计。它将进一步适应各种复杂的方案，包括功能预测变量，缺失值，多个响应和非线性质量过程关系。计划对QQ响应的贝叶斯最佳设计，以满足实验设计需求，可以将其扩展到可靠系统的顺序设计和设计。基于建模方法，面向模型的过程监视将检测过程的变化，并从预测变量或系统本身中识别根本原因。通过优化目标QQ响应之间的隐藏关系来实现质量改进。这些方法将为制造规模扩大和生物医学质量改进提供一系列强大的工具。此外，教育计划将为本科生和研究生提供各种课程模块和研究机会。实际案例研究将用于实验室会议和本科盖石项目。这项研究将使学生在应用统计，制造和生物医学系统方面具有批判性思维和动手技能。研究结果还将通过出版物，会议和讲习班传播到学术界和行业。将建立一个网站，以共享数据，案例研究和高级工具，以促进研究合作。