Emerging Techniques for Reliability and Predictive Maintenance Empowering reliability and predictive maintenance with Digital Twins and AI
November 18 @ 9:00 am - 5:00 pm
This Mini-Symposium aims to gather leading experts to discuss the implementation and implications of recent advances for reliability analysis and maintenance planning, specifically the integration of predictive maintenance, AI, digital twins and other related topics. There is much exciting new research on Digital Twins and AI that is making fundamental advancements in reliability and predictive maintenance. The increasing availability of condition-monitoring data has incentivized in recent years the development of machine learning for prognostics and diagnostics, big data analytics, generative AI. With these, Digital Twins have also become increasingly <a href="http://performant.
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You are cordially invited to share your knowledge and opinions, and to learn more on the application of Digital Twins and/or AI models to support reliability and predictive <a href="http://maintenance.
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Speaker(s): Anne Barros, Professor, David Coit, Professor, Christophe Berenguer, Professor, Konstantinos C. Gryllias, Professor,
Agenda:
(Tentative)
8:30 – 9:00: Registration, Welcome coffee
9:00 – 9:30: Prof. Anne Barros, Centralesupélec France: Welcome speech; Recent advancements in reliability and resilience at RRSC, CentraleSupé<a href="http://lec.
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9:30 – 10:25: Prof. Zhiguo Zeng, Centralesupélec France: Empowering predictive maintenance with digital twins and AI: An application on <a href="http://robots.
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10:25 – 10:35: Coffee break
10:35 – 11:30: Prof. Janet Lin, Lulea University of Technology, Sweden: Industrial AI-Driven Maintenance and the Evolution of Digital Twins
11:30 – 12:25: Prof. Konstantinos Gryllias, KU Leuven, Belgium: Fault diagnosis based on digital twins and transfer learning
12:25 – 13:30: Lunch
13:30 – 14:25: Prof. Giovanni Lugaresi, KU Leuven, Belgium: Data-Driven Modelling of Digital Twins for Circular Production Systems
14:25 – 15:20: Prof. Christophe Berenguer, Grenoble INP, France: On the degradation and RUL Control of Degrading Controlled Systems
15:20 – 15:30: Coffee break
15:30 – 16:25: Prof. Jie Liu, Beihang University, China: Causality-based representation learning for fault diagnosis of complex <a href="http://systems.
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16:25 – 17:20: Prof. Mihaela Mitici, Utrecht University, the Netherlands and Prof. David Coit, Rutgers University, USA: Predictive maintenance at the intersection between OR and ML – methodological challenges and opportunities
17:20 – 17:45: Closing cocktail, announcement of next workshop, <a href="http://discussions.
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