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Presented By: Integrative Systems + Design

Manufacturing Research Seminar Series: Data Enabled Smart Manufacturing

Judy Jin, Director, Manufacturing Program of ISD, Professor, Industrial and Operations Engineering, University of Michigan

Dr. Judy Jin Dr. Judy Jin
Dr. Judy Jin
Abstract:
Industrial big data are widely available through connected cyber-physical systems, distributed sensing and the Internet of Things, which provide unprecedented opportunities for real time information sharing and integrative decision making for smart manufacturing. Meanwhile, it also brings data analysis challenges due to massive high dimensional data with spatial and temporal heterogeneity and complex functional dependencies. This talk will first present the research opportunities and challenges of data analytics for smart manufacturing. Examples of ongoing research on methodological developments and their applications will be discussed with the emphasis on information integration for data driven optimal decision making. Specifically, it includes (1) integrating computer simulation model calibration using limited physical tests with optimal robust design; (2) integrating warranty data analysis with the design of accelerated life testing for improving reliability prediction and customer satisfaction; (3) integrative analysis of process sensing signals and product quality measurements for optimal decision-making in monitoring, inferring, and controlling manufacturing processes. The related data analytics methods will be discussed, including high-order tensor data analysis for multistream functional data/images, multiscale data transforms for data dimension reduction of nonstationary waveform signals, a regularized hierarchical variable selection method for combing the two steps of sensor selection and the signal features extraction together, employing the transfer learning technique for knowledge sharing among the similar processes, SPC supervised predictive control for defects prevention, etc. Some discussions will also be given on how the developed methodologies have been applied in automotive, metal forming and semiconductor manufacturing to show the essential need for multidisciplinary integration efforts.

Bio
Jionghua (Judy) Jin is currently a professor in the Department of Industrial and Operations Engineering and the Director of Manufacturing Engineering Program at the University of Michigan. Dr. Jin’s research focuses on developing new data fusion methodologies with broad applications in both manufacturing and service industries. She has received numerous awards including the Forging Achievement Award from Forging Industry Educational and Research Foundation in 2007, the NSF CAREER and the PECASE Awards in 2002 and 2004 respectively and 12 Best Paper Awards since 2000 from the conferences and journals in her research field. She is currently the Editor of Quality and Reliability Engineering for IISE Transactions. She was also the former Vice President of INFORMS-International Activities in 2010~2013 and the President of Quality Control and Reliability Engineering Division in IIE in 2007~2008. She is a Fellow of IISE, a Fellow of ASME, an elected senior member of ISI, and a senior member of ASQ.

She received her BS and MS in Mechanical Engineering at Southeast University, Nanjing, China in 1984 and 1987 respectively, and her PhD in Industrial and Operations Engineering at the University of Michigan in 1999.
Dr. Judy Jin Dr. Judy Jin
Dr. Judy Jin

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