Jay Lee is Ohio Eminent Scholar, L.W. Scott Alter Chair Professor and Distinguished University Professor at the University of Cincinnati. He is the Founding Director of National Science Foundation (NSF) Industry/University Cooperative Research Center (I/UCRC) on Intelligent Maintenance Systems (IMS, which is a multi-campus NSF Industry/University Cooperative Research Center, which consists of the Univ. of Cincinnati (lead institution), the University of Michigan, Missouri University of S&T, and University of Texas-Austin. The Center has developed partnerships with over 85 companies from 15 countries since its inception in 2001. In addition, he has mentored his students and developed a spin-off company predictronics with support from NSF Innovation ICorps Award in 2012. He also serves as an invited committee member for White House Cyber Physical Systems (CPS) Advisory Group in 2013


In today’s competitive wind energy business environment, companies are facing challenges in dealing with big data issues for rapid decision making for improved performance and asset management. Many wind turbine systems arenot ready to manage big data due to the lack of smart analytics tools. U.S. has been driving the Cyber Physical Systems (CPS) and Industrial Internet to advance future industry. It is clear that as more predictive analytics software and embedded IoT are integrated in today’s industrial products and systems, predictive technologies can further intertwine intelligent algorithms to predict windturbine performance degradation and autonomously manage and optimize service needs. The presentation will address the trends of predictive big data analytics as well as the readiness of smart predictive tools to manage wind turbine big data to achieve resilient life cycle management with improved service value.

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