AI-enabled plant-wide process monitoring in Industry 4.0
Abstract
This presentation will focus on the recent advancement in industrial safety and security issues and will discuss several SOTA approaches enabled by AI technologies. Data-driven process monitoring has been extensively studied by both academia and industry, yet, there is still very large gap to achieve effective and efficient plant-wide monitoring. In this talk, in addition to novel theoretical ideas and identified challenges through broad investigation, a powerful open-source toolbox will be put forward. It realizes a series of basic and advanced AI algorithms for process monitoring, and is useful for research and teaching. The delivered content is based on recent research results from the speaker’s group, which are recognized as 'Featured Article of the Journal' or ESI Highly-Cited Paper.
Short Biography
Dr. Yuchen Jiang is an Assistant Professor with Harbin Institute of Technology (HIT). He received the B.E. degree in automation and the Ph.D. degree in control science and engineering from HIT. His research interests include data-driven process monitoring, fault diagnosis and prognosis, industrial cyber-physical systems, and artificial intelligence. Dr. Jiang is the author/co-author of 50+ scientific publications and the PI of several research projects.