活動

講座|Smart Manufacturing Data-driven Modeling and Control with Energy Aware Operation

發布時間:2023-12-07

學術講座:Smart Manufacturing Data-driven Modeling and Control with Energy Aware Operation

   智能製造系統基於數據驅動的建模和節能控製

主 講 人🤦🏼:Jing Zou, Data Scientist, ZhenDui Industry Artificial Intelligence Co. Ltd

時     間:9:00 - 10:00, December 7, 2023 (Beijing Time)

地     點🤌🏿🏸:202, Yue-Kong Pao Library's Annex

 包玉剛圖書館東翼意昂2体育200報告廳


講座摘要:

Advance manufacturing systems are becoming increasing complex, subjecting to constant changes driven by market demands, new technology insertion, as well as random disruption events. To support daily operation, distributed sensors are utilized to monitor the status of each process. While information about production processes has been becoming increasing transparent, detailed, and real-time, the utilization of this information for real-time manufacturing analysis and decision-making has been lagging behind largely due to the limitation of the traditional methodologies for production system analysis, and a lack of real-time data-driven manufacturing processes modeling, analysis and control approaches. Hence, it is necessary to develop manufacturing system real-time data-driven modeling, analysis and control approaches for improving system responsiveness and efficiency.

In this presentation, we will introduce a novel manufacturing system real-time data-driven mathematical model to describe the system production dynamics. Furthermore, systematic methods will be illustrated to identify the causes of system permanent production loss. In the end, real-time production control policies based on the system diagnostic results will be presented to improve system profit, energy efficiency and responsiveness.


主講人簡介👨:

JING ZOU received the B.S. degree from the Huazhong University of Science and Technology, Wuhan, China, in 2012, the M.S. degree from the University of Florida, Gainesville, FL, USA, in 2014, and the Ph.D. degree from Stony Brook University, Stony Brook, NY, USA, in 2019, all in mechanical engineering.

He is currently a data scientist with ZDIAI. His current research interests include smart manufacturing, knowledge-basedAI, and data-driven manufacturing system modeling and analysis.


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