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Prognostics and Health Management for the Predictive Maintenance of Components and Systems

Distinguished Research Seminar Series

20230203Prof Enrico ZioEvent banner
  • Date

    03 Feb 2023

  • Organiser

    Department of Industrial and Systems Engineering, PolyU; Centre for Advances in Reliability and Safety (CAiRS)

  • Time

    16:00 - 17:30

  • Venue

    Online via ZOOM  


Professor Enrico Zio


Meeting link will be sent to successful registrants

20230203Prof Enrico ZioPoster


The increased availability of data coming from monitoring the relevant parameters of components and systems, and the grown ability of treating these data by intelligent machine learning algorithms allow improved design, operation, management and maintenance of components and systems.

In this lecture, I look into the perspectives of Prognostics and Health Management (PHM) for the predictive maintenance of industrial components and systems in various industrial sectors, highlighting practical challenges and recent advancements in methods and techniques.

Keynote Speaker

Professor Enrico Zio

Professor Enrico Zio

Department of Energy, 
Politecnico di Milano, Milan, Italy.

Enrico Zio received the MSc degree in nuclear engineering from Politecnico di Milano in 1991 and in mechanical engineering from UCLA in 1995, and the Ph.D. degree in nuclear engineering from Politecnico di Milano and in probabilistic risk assessment at MIT in 1996 and 1998, respectively. He is currently full professor at the Centre for research on Risk and Crises (CRC) of Ecole de Mines, ParisTech, PSL University, France, full professor and President of the Alumni Association at Politecnico di Milano, Italy, distinguished guest professor at Tsinghua University, Beijing, China, adjunct professor at City University of Hong Kong, Beihang University and Wuhan University, China and Co-Director of the Center for REliability and Safety of Critical Infrastructures (CRESCI) and the sino-french laboratory of Risk Science and Engineering (RISE), at Beihang University, Beijing, China.
He is IEEE and Sigma Xi Distinguished Lecturer. In 2020, he has been awarded the prestigious Humboldt Research Award from the Alexander von Humboldt Foundation in Germany (, one the world's most prestigious research awards across all scientific disciplines. The Award is given to outstandingly qualified researchers and future leaders from science-related fields (but very seldom awarded to engineers!). The Award is granted in recognition of a researcher's entire achievements to date, to academics whose fundamental discoveries, new theories, or insights have had a significant impact on their own discipline and who are expected to continue producing cutting-edge achievements in the future. Professor Zio has been selected for the Award in light of being a World leading scientist in Risk and Resilience Assessment, Safety Analysis and Reliability Engineering of complex systems and infrastructures, in particular for energy applications. His H-index is 72. He has been one of the pioneers in using artificial intelligence (such as neural networks) and genetic algorithms in reliability engineering and risk assessment, solving key problems related to the safety and reliability of critical systems such as those used in the nuclear, oil and gas, transportation industries. He has promoted the use of computational modeling within various international initiatives.
His research focuses on the modeling of the failure-repair-maintenance behavior of components and complex systems, for the analysis of their reliability, maintainability, prognostics, safety, vulnerability, resilience and security characteristics, and on the development and use of Monte Carlo simulation methods, artificial intelligence techniques and optimization heuristics. He is author and co-author of seven books and more than 500 papers on international journals, Chairman and Co-Chairman of several international Conferences, associate editor of several international journals and referee of more than 20.  

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