Abstract

Machine learning has great potential for reliability assurance through prognosis and health management (PHM) of engineering assets. It has been attracting attention from both academic and industrial sectors. Recent developments in machine learning, especially the evolving branches of deep learning, transfer learning, and reinforcement learning, bring new opportunities for effective PHM. This talk will first introduce prognosis and health management and machine learning. We will then present our recent research work on developing machine-learning techniques for PHM. Finally, the development of PHM tools for industrial settings including traditional and intelligent approaches will be covered.

Speaker

Professor Mingjian Zuo Canada

Professor of Department of Mechanical Engineering

University of Alberta &
University of Electronic Science and Technology of China

FCAE, FIISE, FEIC, FISEAM

Dr. Mingjian Zuo received the Bachelor of Science degree in Agricultural Engineering in 1982 from Shandong Institute of Technology, China, and the Master of Science degree in 1986 and the Ph.D. degree in 1989 both in Industrial Engineering from Iowa State University, Ames, Iowa, U.S.A. He is the Founder and CEO of Mingserve Technology Co. Ltd., China, a Guest Professor at the University of Electronic Science and Technology of China, and a Full Professor at the University of Alberta, Canada. His research interests include system reliability analysis, maintenance modeling and optimization, signal processing, fault diagnosis, machine learning, and prognosis & health management. He served as Department Editor of IISE Transactions, Associate Editor of IEEE Transactions on Reliability, Associate Editor of the Journal of Risk and Reliability, Associate Editor of the International Journal of Quality, Reliability and Safety Engineering, Regional Editor of the International Journal of Strategic Engineering Asset Management, and Editorial Board Member of Reliability Engineering and System Safety, Journal of Traffic and Transportation Engineering, and International Journal of Performability Engineering. He is a Fellow of the Canadian Academy of Engineering, a Fellow of the Institute of Industrial and Systems Engineers (IISE), a Fellow of the Engineering Institute of Canada (EIC), and a Founding Fellow of the International Society of Engineering Asset Management (ISEAM).