Speaker: Academician Thomas Bäck
Title: Predictive Maintenance, Optimization, and Explainable Modeling: The CIMPLO Project
Time: 14:30-15:30, May 17th, 2023 (Wednesday)
Website: Teams Link
Abstract:
The Cross-Industry Predictive Maintenance Optimization Platform (CIMPLO)project is an industry co-funded research project in collaboration with KLM, Honda Research Institute, and CWI. The project combines machine learning based data-driven modeling and prediction of RUL of components, multi-objective algorithms for maintenance scheduling optimization, efficient data processing, and explainable AI for model interpretation. In the talk, an overview of the project and the current software prototype is provided. I will then illustrate the use of machine learning for RUL prediction, multiple objective optimization of maintenance schedules (by means of an example from automotive), and a novel way of modeling EGT from engine cruising data that yields explainable insights into EGT and its relation to sensor data.
Personal Introduction:
Thomas Bäck (Fellow, IEEE) received the Diploma degree in Computer Science in 1990 and the Ph.D. degree in Computer Science in 1994 (under supervision of H.-P. Schwefel), both from the University of Dortmund, Germany. He is Professor of Computer Science with the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, Netherlands. His research interests include evolutionary computation, machine learning, and their real-world applications, especially in sustainable smart industry and health. Dr. Bäck has been elected as member of the Royal Netherlands Academy of Arts and Sciences (KNAW, 2021), as IEEE Fellow (class of 2022), and as a member of Academia Europaea (2022). He was a recipient of the IEEE Computational Intelligence Society (CIS) Evolutionary Computation Pioneer Award in 2015, was elected as Fellow of the International Society of Genetic and Evolutionary Computation in 2003, and received the best Ph.D. thesis award from the German society of Computer Science (GI) in 1995. He currently serves as an Associate Editor for the IEEE Transactions on Evolutionary Computation and Artificial Intelligence Review journals and area editor for the ACM Transactions on Evolutionary Learning and Optimization. He was also co-editor-in-chief of the Handbook of Evolutionary Computation (CRC Press/Taylor & Francis 1997), co-editor of the Handbook of Natural Computing (Springer, 2013), author of Evolutionary Computation in Theory and Practice (OUP, New York, 1996) and co-author of Contemporary Evolution Strategies (Springer, 2013).
[Editor:Xiaohan Liu]