Nowadays, technology is under rapid change and numerous innovative systems, e.g. robots, new energy sources and digital twin, are being created to satisfy the ever growing demand of better life. Due to the complexity of these new systems, the conventional reliability engineering and PHM methods have been challenged for more accurate prediction of system lifetime and more economic decision for health managements. With the prevalence of sensor data and the advancements of physics-of-failure models as well as artificial intelligence methods, prognostic methods are being constantly upgraded and new health condition indices are being proposed. On the other hand, optimization models and methods are being developed for maintenance/scheduling/logistic action planning accounting for the prediction errors and failure/degradations uncertainties. This session is dedicated to the challenging problems and the cutting-edge PHM methods for advanced industrial systems.
Tsinghua University, China
Dr. Yan-Fu Li is currently a full professor at the Department of Industrial Engineering (IE), Tsinghua University and the director of the Reliability & Risk Management Laboratory at the Institute of Quality and Reliability in Tsinghua University. He is a scholar of Thousand Talent Program for Young Outstanding Scientists of China. He received his B.Eng degree in Software Engineering from Wuhan University in 2005 and Ph.D in Industrial Engineering from National University of Singapore in 2010. He was a faculty member at Laboratory of Industrial Engineering at CentraleSupélec, France, from 2011 to 2016.
His current research areas include system reliability, PHM, predictive maintenance and cyber-security with the applications onto energy systems, transportation systems, computing systems, etc. He is the Principal Investigator (PI) of several government projects including one key project funded by National Natural Science Foundation of China, one project in National Key R&D Program of China, and the projects supported by EU and French funding bodies. He is also experienced in industrial research, the partners include Huawei, China General Nuclear, Mitsubishi heavy industry, EDF, ALSTOM, etc. Dr. Li has published more than 90 research papers, including more than 50 peer-reviewed international journal papers. Dr. Li is currently an Associate Editor of IEEE Transactions on Reliability, a senior member of IEEE and a member of INFORMS. He is a member of the Executive Committee of the Reliability Chapter of Chinese Operations Research Society; Executive Committee of Industrial Engineering Chapter of Chinese Society of Optimization, Overall Planning and Economic Mathematics; Committee of Uncertainty Chapter of Chinese Artificial Intelligence Society.
Xi’an Jiaotong University, China
Yaguo Lei received the B.S. degree and the Ph.D. degree both in mechanical engineering from Xi’an Jiaotong University, P. R. China, in 2002 and 2007, respectively. He is currently a full professor in mechanical engineering of Xi’an Jiaotong University, P. R. China. Prior to joining Xi’an Jiaotong University in 2010, he worked at the University of Alberta, Canada as a postdoctoral research fellow. He ever worked at the University of Duisburg-Essen, Germany as an Alexander von Humboldt fellow. His research interests focus on machinery condition monitoring and fault diagnosis, mechanical signal processing, intelligent fault diagnostics and remaining useful life prediction. He is also a member of IEEE and ASME, senior member of CMES and the editorial board member of MSSP, MST, NC&A, etc.
Shanghai Jiaotong University, China
Dong Wang received his Ph.D. at the City University of Hong Kong in 2015. Currently, he is an associate professor in Department of Industrial Engineering and Management and in The State Key Laboratory of Mechanical Systems and Vibration at Shanghai Jiao Tong University. Prior to joining Shanghai Jiao Tong University, he was a research fellow in School of Data Science at City University of Hong Kong and a postdoctoral research fellow in Department of Systems Engineering and Engineering Management at City University of Hong Kong, respectively. His research interests include prognostics and health management, statistical modeling, condition monitoring and fault diagnosis, signal processing, data mining and deep learning, nondestructive testing and sensors. He is an associate editor for IEEE Access and Journal of Low Frequency Noise, Vibration & Active Control. He is a recipient of 1000 Youth Talents Program, Elsevier and IEEE Outstanding Reviewer Status, Hong Kong PhD Fellowship, etc.
Beijing University of Technology, China
Rui Peng received his Ph.D. degree in ISE department from National University of Singapore. He is currently a school professor in the School of Economics & Management, Beijing University of Technology. Before that, he was an associate professor in Donlinks School of Economics & Management, University of Science & Technology Beijing. He was a key member in Prof Wenbin WANG’s group. His main research interests include software reliability, multi-state system reliability, system maintenance and defense strategies. He has about 60 papers in leading journals, such as IIE Transactions, European Journal of Operational Research, Reliability Engineering & System Safety, and IEEE Transactions on Reliability. He is a senior member of IEEE, and in the editorial board of the journal Reliability Engineering & System Safety. He is listed in the 2018 Elsevier highly cited Chinese Scholars.
Tsinghua University, China
Chen Zhang is an Assistant Professor in Industrial Engineering, Tsinghua University. She received her B.Eng. degree in Electronic Science and Technology from Tianjin University in 2012, and her Ph.D. degree in Industrial Systems Engineering from National University of Singapore in 2017. Her research interests include developing methodologies and algorithms for complex or large-scale systems with multivariate or high-dimensional data, including intelligent sampling and sensing for data collection, data mining and information extraction for system modeling, and on-line monitoring and efficient anomaly detection for streaming data.
Cambridge University, UK
Zhenglin Liang received his PhD at the University of Cambridge in 2015. After that, he worked at the Asset Management group at the University of Cambridge as a Research Associate for three years. During this time, he also collaborated with Centre for Smart Infrastructure and Construction (CSIC) and Centre for Digital Built Britain (CDBB) at the University of Cambridge on predictive maintenance and digital twins related projects. His research interest focusses on predictive maintenance, maintenance scheduling, infrastructure maintenance, maintenance of power devices and network science. He services as a reviewer for journals of Reliability Engineering & System Safety, IEEE Transactions on Reliability and International Journal of Production Economics.