报告人：Thomas Bäck 院士
工作单位：莱顿大学（荷兰）
报告题目：预测性维护、优化和可解释性建模：CIMPLO项目
报告时间：2023年5月17日（周三）14:30-15:30
报告链接：Teams Link
https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
内容摘要：
跨行业预测性维护优化平台（CIMPLO）项目是与荷兰皇家航空公司、本田研究所和CWI合作的一个行业共同资助的研究项目。该项目结合了基于机器学习的数据驱动建模和组件RUL预测、用于维护调度优化的多目标算法、高效的数据处理和用于模型解释的可解释的人工智能。首先，本报告将概述该项目和当前的软件原型。随后，将说明机器学习在RUL预测中的使用，并通过汽车中的一个例子阐释维护计划的多目标优化，以及一种从发动机巡航数据建模EGT的新方法，从而对EGT及其与传感器数据之间的关系产生可解释性的见解。
个人简介：
Thomas Bäck院士（IEEE会士）于1990年获得计算机科学文凭学位，1994年在H.-P. Schwefel的指导下获得计算机科学博士学位。Thomas Bäck院士现任荷兰莱顿大学莱顿高级计算机科学研究所（LIACS）的计算机科学教授，他的研究兴趣包括进化计算、机器学习及其在现实世界中的应用，特别是在可持续的智能产业和健康领域。Thomas Bäck院士当选荷兰皇家艺术与科学学院成员（KNAW，2021年）、IEEE研究员（2022年级）和欧洲理工学院成员（2022年）。Thomas Bäck院士于1995年获德国计算机科学学会（GI）颁发的最佳博士论文奖，于2003年当选国际遗传和进化计算学会会士，并于2015年获IEEE计算智能学会（CIS）进化计算先锋奖。Thomas Bäck院士现任IEEE《Transactions on Evolutionary Computation》和《Artificial Intelligence Review 》期刊的副编辑，以及ACM《Transactions on Evolutionary Learning and Optimization.》的区域主编，曾任《Handbook of Evolutionary Computation》（CRC出版社/Taylor & Francis 1997）和《Handbook of Natural Computing》（Springer，2013）的联合主编，也是《Evolutionary Computation in Theory and Practice》的作者（OUP，纽约，1996）及《Contemporary Evolution Strategies》的合著者（Springer，2013）。
【编辑：王健】
英文版：
Academic Report Notice of Thomas Bäck : Predictive Maintenance, Optimization, and Explainable Modeling: The CIMPLO Project
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
https://teams.microsoft.com/l/meetup-join/19%3aB4gmRcUATAMA2iJqi-xXvtfPFfTbxVJPxSW_pcAPBao1%40thread.tacv2/1638719716825?context=%7b%22Tid%22%3a%2222804ebb-30d5-47df-942f-f3a3722f0225%22%2c%22Oid%22%3a%2216a60c03-ad7a-4b85-a403-8ebd947e010c%22%7d
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:Jian Wang]