Data Fusion for System Analysis and Improvements
Research Seminar Series
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Date
13 Nov 2024
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Organiser
Department of Industrial and Systems Engineering, PolyU
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Time
10:00 - 11:30
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Venue
Online via ZOOM
Speaker
Dr Weihong Guo
Remarks
Meeting link will be sent to successful registrants
Summary
The wide applications of automatic sensing devices and computer systems have resulted in a temporally and spatially dense data-rich environment, which provides unprecedented opportunities for quality improvement in various applications including manufacturing, supply chain, health care, and so on. The increasing complexity of data structures raises significant research challenges on data analytics. New methodologies for effective data fusion and information integration to support decision-making are in demand. To achieve optimal product and service quality, my current research focuses on process monitoring, prognostics, and diagnostics in advanced manufacturing, with a special focus on the digital thread of metal additive manufacturing, and then expanding the breadth of my research to smart and robust manufacturing supply chain. I will share my research in three areas: (1) Process monitoring, prognostics, and diagnostics in advanced manufacturing; (2) Integrating data science with physics for “process-signature-quality” relationship in additive manufacturing; and (3) Robust and smart manufacturing systems and supply chain.
Keynote Speaker
Dr Weihong Guo
Associate Professor
Department of Industrial & Systems Engineering,
Rutgers, The State University of New Jersey, USA
Weihong “Grace” Guo is an Associate Professor in the Department of Industrial and Systems Engineering at Rutgers University. She earned her B.S. degree in Industrial Engineering from Tsinghua University, China, in 2010 and her Ph.D. in Industrial & Operations Engineering from the University of Michigan, Ann Arbor, in 2015. Her research focuses on developing novel methodologies for extracting and analyzing massive and complex data to facilitate effective monitoring of operational quality, early detection of system anomalies, quick diagnosis of fault root causes, and intelligent system design and control. She has collaborated with a domestic logistics/supply chain company, a university-affiliated health system and worldwide manufacturers of automobiles and personal care products. Her research has been funded by NSF, DOT, Ford Motor Company, etc. She received the Barbara M. Fossum Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing Engineers in 2019. She also received several best paper awards/finalists from ASME, INFORMS, IISE, and IEEE. She is an Associate Editor for IISE Transactions, IEEE T-ASE, IEEE RA-L, and Manufacturing Letters.
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