Reliability Analysis, Prediction and Maintenance
Optimization for Electro-Mechanical Systems Subject to Condition Monitoring
状态监测下机电系统的可靠性分析、预测与维护优化
Modern electro-mechanical systems are typically equipped with dedicated sensors to monitor the real-time health states of their critical components. With in-filed health data of these critical components, the physical models, statistical methods and advanced machine learning techniques can be employed to effectively analyze and predict the reliability status and remaining useful life for these critical components and even entire systems, for achieving the accurate reliability evaluations and predictions. With these reliability analysis and prediction results, optimal maintenance decisions can be made for single critical components or entire electro-mechanical systems based on the consideration of operational costs, reliability or availability objectives. The purpose of this special session is to promote the investigation and application of reliability analysis and prediction methods as well as maintenance optimization models for modern electro-mechanical systems subject to condition monitoring.
现代机电系统通常配置了专用传感器对关键部件的健康状态进行实时监测。基于关键部件运行过程中的健康数据，可以采用物理模型、统计方法或者先进的机器学习方法对关键部件乃至整个系统的可靠性和剩余寿命进行分析与预测。根据部件或系统的可靠性分析与预测结果，进而可以在考虑运行成本、可靠性或可用度目标的基础上对关键部件或整个机电系统做出最优维护决策。本专题旨在促进现代机电系统的可靠性分析和预测以及维护优化模型的研究和应用。
Related topics: Some topics that are relevant may include, but are not limited to: reliability evaluation; physics-of-failure modeling; degradation modeling; remaining useful life prediction; predictive maintenance; condition-based maintenance; opportunistic maintenance; grouping maintenance.
相关主题包括但不限于：可靠性评估；失效物理模型；退化建模；剩余寿命预测；预测性维护；视情维护；机会维护；成组维护。
Chair: Biao Lu, Nanjing University of Aeronautics and Astronautics, China
Biao Lu is currently an assistant professor with the Department of management science and engineering, College of Economics and Management, Nanjing University of Aeronautics and Astronautics. He received his doctoral degree in mechanical engineering in 2019 from Shanghai Jiao Tong University, China. He was a visiting scholar with the Department of Industrial Systems Engineering and Management, National University of Singapore from Sep 2022 to Sep 2023, supervised by Prof. Ye Zhisheng. His research interests include reliability evaluation, maintenance optimization, and their applications in industrial systems. He is currently the author of more than 20 journal papers in the field of reliability and maintenance engineering. (E-Mail: lubiao123@nuaa.edu.cn)
陆彪，2019年在上海交通大学获得机械工程专业博士学位，现为南京航空航天大学经济与管理学院助理教授。2022年9月至2023年9月在新加坡国立大学工业工程与系统管理系做访问学者，合作导师为叶志盛副教授。主要研究方向为可靠性评估、维护优化及其在工业系统中的应用，在可靠性与维护领域主流期刊发表了20余篇论文。
Chair: Yifan Hu, Huawei Technologies Company Ltd., China
Yifan Hu received the Ph.D. degree in electrical engineering in 2024 from Harbin Institute of Technology, China. He was also a Visiting Research Scholar with the Department of Industrial Systems Engineering and Management, National University of Singapore, from 2022 to 2023. He currently works at Huawei Technologies Company Ltd. His research interests include degradation modeling, reliability evaluation and health management for electronic devices. He has published more than 10 peer-reviewed journal papers. (E-Mail: yifanhu_123@163.com)
胡义凡，2024年在哈尔滨工业大学获电气工程专业博士学位，曾于2022-2023年在新加坡国立大学工业工程与系统管理系访学，目前就职于华为技术有限公司。主要研究方向为电子设备退化建模、可靠性评估与健康管理，已在可靠性领域主流期刊发表10余篇论文。
Submission Portal
If you are interested in the special
session, please submit your paper or abstract here
https://www.zmeeting.org/submission/srse2024 and choose special session 5.
For any questions, please mail the organizers or conference secretary
srse@sciei.org.
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