Modeling and Analysis of Profiled Reliability Tests Using Computation-Intensive Statistical Methods

这笔赠款为开发一种创新的研究方法提供资金，以建模和分析复杂的工程可靠性问题。该项目包括四项研究和教育任务：1)开发新的统计模型，将可靠性分析扩展到多应力剖面可靠性试验数据；2)将来自各种来源的可靠性信息，包括机械模型、专家意见和现场失效数据，融合到使用贝叶斯方法及其相关计算工具的可靠性估计和预测中；3)展示使用广义线性模型和贝叶斯分析方法设计和优化可靠性试验的优势；4)让理工科学生，特别是拉美裔学生，主动学习并在实际应用中使用概率和统计模型。如果成功，该项目将提高对复杂测试计划和多种故障模式的统计可靠性分析的知识，开发一种数据分析方法，消除许多不切实际的假设，并将先前的工程知识纳入可靠性分析，并促进质量和可靠性研究人员和工业从业者对计算统计方法的更广泛理解和欣赏。本研究开发的方法论可应用于汽车工业、电子工业、半导体工业以及工程以外的许多领域，如医学和生物科学。此外，该项目将显著加强一所主要拉美裔大学的基础科学和工程教育，促进跨工业工程和数学科学学科的协作研究环境，并使传统上在科学和工程职业中代表性不足的少数族裔学生群体受益。

This grant provides funding for the development of an innovative research approach to modeling and analysis of complicated engineering reliability problems. The project consists of four research and education tasks - 1) developing new statistical models that can extend reliability analysis to multiple-stress profiled reliability testing data; 2) fusing reliability information from various resources, including mechanistic model, expert opinions, and field failure data, into reliability estimation and prediction using Bayesian methods and their associated computational tools; 3) demonstrating the advantages of using generalized linear models and Bayesian analysis methods for the design and optimization of reliability tests; 4) engaging science and engineering students, particularly Hispanics students, in active learning and using probabilistic and statistical models in real-world applications.If successful, this project will advance the knowledge of statistical reliability analysis of a complex testing plan and multiple failure modes, develop a data analysis method which will eliminate many unrealistic assumptions and incorporate prior engineering knowledge into reliability analysis, and promote a broader understanding and appreciation of computational statistics methods among quality and reliability researchers and industrial practitioners. The methodology developed in this research can apply to the automobile industry, electronic industry, semiconductor industry, and many other applications in the fields beyond engineering, such as medical and biological sciences. In addition, this project will significantly enhance the basic science and engineering education in a major Hispanics-serving university, foster a collaborative research environment across the disciplines of industrial engineering and mathematical science, and benefit a minority student group who is traditionally underrepresented in science and engineering careers.