CAREER: Adaptive Operational Coordination Methodology for Uncertainty Reduction in Product Life Cycle Reliability and Service Logistics

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The research objective of this Faculty Early Career Development (CAREER) project is to develop a cohesive, adaptive operational coordination methodology for overall uncertainty reduction in product life cycle reliability and service logistics. The methodology consists of three stages: robust accelerated testing (AT), AT-enhanced condition based maintenance, and operational coordination, each of which needs its own mathematical models and computational tools. In particular, this methodology offers a new optimal experimental design approach for planning robust AT that preliminarily reduces the uncertainty in product reliability estimate under generic (e.g., stochastic) operating conditions. Based on the refined reliability estimate, mathematical and statistical models will be developed to enable the real-time control of product reliability. By incorporating the information about service delays, maintenance and logistic processes will be adjusted along with the real-time control of product reliability to reduce the overall uncertainty involved. The methodology will be validated through ongoing wind energy research involving wind turbine test bed development and collaboration with leading industry partners. If successful, this research will lead to fundamental contributions to reliability testing, condition based maintenance, and service logistics, as it integrates disjoint tasks into a more efficient and viable framework. Essentially, the increased understanding of adaptive coordination in a product life cycle will make radical changes to the current research direction and industry practices that demand advanced mathematical tools. Moreover, this research will support the development and use of renewable energy technologies in the US, as a national priority, for energy security and independence. It will positively impact multiple engineering fields, such as composites materials, sensors, controls, and power systems. Finally, the planned educational activities in a multidisciplinary environment will help students and working professionals acquire both analytical and experimental skills as well as systems thinking capabilities to meet societal needs.