Special Session IV

Prognostic and Health Management of Systems in the Environment of Big Data
大数据环境下的故障预测以及健康管理研究

The research of prognostic and health management (PHM) has remained very active over the last few decades. Besides lifetime data, with the advancements of sensor technologies, it is now possible to collect, store, and process a huge amount of other data, such as vibration, temperature, stress, etc. Big data attracts tremendous attentions in recent years. However, the questions remain how to reveal the useful information behind these big data. Many data-driven models in different fields have been developed based on machine learning and artificial intelligence methods, and showed some significance. This special session therefore calls for studies on prognostic and health management of systems in the environment of big data. Both abstract and full text in the field are welcome.

在过去的几十年中,故障预测和健康管理 (PHM) 领域的研究一直非常活跃。除了寿命数据,随着传感器技术的进步,现在可以收集、存储和处理大量其它数据,如振动、温度、应力等。近年来,大数据引起了极大的关注。然而,如何有效地发掘这些大数据背后的有用信息依然是个问题。在不同领域,涌现出基于机器学习和人工智能方法的数据驱动模型,取得一定效果。因此,本主题会议专注于大数据环境下系统的故障预测和健康管理研究。欢迎投稿该领域的摘要或者全文。

 Chair:

Jiawen Hu is an associate professor in School of Astronautics and Aeronautic, University of Electronic Science and Technology of China, Chengdu, China. He received the B.S. degree in mechanical engineering from Shanghai Jiao Tong University, Shanghai, China, in 2009, the M.S. degree in mechanical engineering from Chinese Academy of Sciences, Beijing, China, in 2012, and the Ph.D. degree in industrial engineering from Shanghai Jiao Tong University, Shanghai, China, in 2017. He was a research fellow with the Department of Industrial Systems Engineering and Management, National University of Singapore from 2017 to 2020. His research interests include maintenance optimization, degradation modeling. His work has appeared in journals including IEEE Transactions on Industrial Informatics, IISE Transactions, IEEE Transactions on Reliability, Reliability Engineering & System Safety, Journal of Manufacturing Systems, International Journal of Production Research. (Emailhdl@uestc.edu.cn)

Co-chair:

Weiwen Peng is an associate professor in the School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China. He received the B.E., M.E., and Ph.D. degrees in Engineering from the University of Electronic Science and Technology of China, Chengdu, China, in 2009, 2012 and 2015, respectively. From 2016 to 2019, he worked as a Research Fellow in the National University of Singapore, Singapore. He His research interests include degradation modeling, machinery health prognostics, and Bayesian machine learning in reliability engineering. His work has appeared in journals including IEEE Transactions on Industrial Informatics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Reliability, Reliability Engineering & System Safety. (Email:pengww3@mail.sysu.edu.cn )


 Submission Portal

If you are interested in the special session, please submit your paper or abstract here
http://confsys.iconf.org/submission/srse2021-session4

For any questions, please mail the organizers or conference secretary srse@sciei.org.

 

 

 

 

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