Catégorie : Séminaires projet SDF-PHM2

Réunion SdF-PHM2

7 mars 2024 @ 14h00 – 16h00 –  14:00-14:45 –  Cutting Tool Health Monitoring with Artificial Intelligence par Lorenzo COLANTONIO (PhD candidate, University of MONS, Belgium) Abstract: In the manufacturing industry, the state of the cutting tool is of crucial importance. During machining, the tool inevitably degrades leading to production of suboptimal parts. The degradation of the tool is due to different mechanisms occurring […]

Doctoral workshop SDF-PHM2 – Université de Tongji, Shanghai

27 mars 2024 @ 8h00 – 12h00 – 8:00-8:05, Introduction – UL, Benoît Iung 8:05-8:10, Introduction – UTongJi, Li Li PhD candidate presentations 8:10-8:35, Critical evolutionary mechanisms of complex manufacturing systems under risk propagation, Ji Peng-Cheng (UTongji) 8:35-8:50, Federated Learning for Prognostics & Health Management, Ilias Abdouni (UL) 8:50-9:15, Application of DRL for complex scheduling problems, Kunhao Chen (UTongji) 9:15-9:40, AI-based machine learning […]

Réunion SdF-PHM2

16 mai 2024 @ 13h00 – 14h00 – 13:00-13:40 “Quantitative Modeling for Enhanced End-of-Life Management of EV Batteries: The Role of System Dynamics and Agent-Based Approaches”, Alaa SHQAIRAT (PhD candidate, CRAN/UL) 13:40-14:00 « Failure prognostics and predictive maintenance for manufacturing system with sensor data uncertainty », Thanh THAI (PhD candidate, 1st year, CRAN/UL)

Réunion SdF-PHM2

4 juillet 2024 @ 13h00 – 14h00 – 13:00-13:30 –  “Modelling Degradation And Ageing Phenomena In A Digital Twin Using Profile-Based Stochastic Hybrid Automata”, Gael HEQUET (PhD candidate, Reactor project, CRAN/UL) 13:30-14:00 – « Multi Criteria Importance Measure for Identifying Critical Components of Electro-Hydrogen Generator », Soufian Echabarri (PhD candidate, Cifre EODev, CRAN/UL)

Réunion SdF-PHM2

3 octobre 2024 @ 13h00 – 14h00 – « A Parallel-Machine Learning framework to tune metaheuristics for advanced manufacturing scheduling problems », Hanser Jiménez (Postdoc, European project MODAPTO, CRAN/UL) Abstract: Meta-heuristics (MH) have become a de facto approach to find approximate solutions for complex scheduling problems. However, since the quality of solutions provided by these methods is highly sensitive to the value of their parameters, […]

Réunion SdF-PHM2

7 novembre 2024 @ 13h00 – 14h00 – 13:00-13:30 –  “Developing Data-Driven O&M Policy through Sequential Pattern Mining: A case study”, Rafael Paiva (Visiting PhD student, UFPE/Brazil) 13:30-14:00 – « AI-based Data Augmentation for Lithium-Ion Batteries State-of-Health Prediction: Application to Hydrogen Power Generators », Soufian Echabarri (PhD student, EODev group/CRAN)

Réunion SdF-PHM2

5 décembre 2024 @ 14h00 – 16h00 – 14:00-14:10 – Introduction 14:10-14:30 – “Contribution to the failure prediction of industrial products using a hybrid approach combining artificial intelligence and physical models – Application to Schneider Electric products”, Mélvin FERNANDES NOVO (PhD student, Schneider Electric/CRAN) 14:30-15:00 – “Federated Learning for Prognostics and Health Management”, Ilias ABDOUNI (PhD student, CRAN) 15:00-15:30 – “On the Construction […]