Collaborative Research: Integrated Modeling and Optimization of Manufacturing Variability and Product Reliability for Advanced and Evolving Technologies

该奖项的研究目标是开发集成质量和可靠性模型和分析工具，为不断发展的技术的成功开发和商业化提供基本见解，例如微机电系统（MEMS）和生物医学植入设备。对于许多新的和不断发展的技术，它们的持续成功开发依赖于过程可变性和产品寿命的并行建模和优化，这对于许多这些技术来说是内在联系的。第一个研究工作是开发一种综合定量方法来共同优化系统质量和可靠性。基于这一集成框架，将研究概率模型，以预测由于同时暴露于退化和冲击载荷而经历多重失效过程的设备的可靠性。将开发和扩展具有依赖失效过程的竞争风险模型。此外，将为具有多个独立或相关组件的复杂系统开发可靠性模型。多目标优化问题的制定和求解将同时考虑多个用户目标（如质量、可靠性、成品率、成本等）。最后，开发的模型将通过与工业和政府合作伙伴的合作，在MEMS和生物医学植入设备上进行验证。这项研究的结果将通过贡献新的概念、模型和算法来推进最先进的技术。将建立坚实的多学科科学基础，以结合质量、可靠性、统计和运筹学方面的方法。此外，这项研究的成功将提供基本的见解，可以转化为许多新的设计和制造问题，如纳米技术，也有独特的制造挑战。集成方法可以为制造业决策者提供及时有效的工具，以经济地优化运营决策，提高可靠性、质量和生产率。来自代表性不足群体的本科生和研究生将不断被招募参与这项研究。

The research objective of this award is to develop integrated quality and reliability models and analysis tools that provide fundamental insights for the successful development and commercialization of evolving technologies, such as Micro-Electro-Mechanical Systems (MEMS) and biomedical implant devices. For many new and evolving technologies, their continued successful development depends on the concurrent modeling and optimization of process variability and product life, which are inherently linked for many of these technologies. The first research effort is to develop an integrated quantitative methodology to jointly optimize system quality and reliability. Based on this integrated framework, probabilistic models will be investigated for predicting reliability of devices that experience multiple failure processes due to simultaneous exposure to degradation and shock loads. Competing risk models with dependent failure processes will be developed and extended. In addition, reliability models will be developed for complex systems with multiple independent or dependent components. Multiple user objectives (e.g., quality, reliability, yield, cost, etc.) will be simultaneously considered by the formulation and solution of multi-objective optimization problems. Finally, the developed models will be validated for MEMS and biomedical implant devices through collaborations with industrial and government partners.The results of this research will advance the state-of-the-art by contributing new concepts, models and algorithms. A solid multidisciplinary scientific foundation will be built to combine methodologies in quality, reliability, statistics and operations research. In addition, the success of this research will offer fundamental insights that can be transformed to many newer design and manufacturing problems, such as nano-technology that also has unique manufacturing challenges. The integrated methodology can provide timely and effective tools for decision-makers in manufacturing to economically optimize operational decisions for improving reliability, quality and productivity. Undergraduate and graduate students from underrepresented groups will be continuously recruited to work on this research.