ISyE Seminar - Shiyu Zhou

Event Details
  • Date/Time:
    • Wednesday April 5, 2017 - Thursday April 6, 2017
      3:00 pm - 3:59 pm
  • Location: Groseclose 402
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Summary Sentence: ISyE Seminar - Shiyu Zhou

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TITLE:  Data Analytics for Failure Prognosis for Smart Tele-Service Systems


Driven by the development of sensing, communication, and cloud-based data management platform, smart tele-service systems have seen tremendous growth in recent years. The smart tele-service system can monitor the operation of a product/system at real time and provide service alerts to the end-users when an imminent failure is predicted. The unprecedented data availability in smart tele-service systems provides significant opportunities for the data-drive failure prognosis but, at the same time, reveals some critical challenges. First, the heterogeneous data with diverse data types often hinder to establish a unified prognostic framework. Second, individual-level data has become available in large scale and consequently, there is a pressing need for individualized modeling and prognosis. Lastly, severe signal noise and non-stationary behavior in the monitoring data need to be addressed appropriately. To address those challenges, a series of data-driven prognostic methodologies have been proposed by my research group. First, a flexible hierarchical Bayesian model namely the joint prognostic model framework is proposed. The joint prognostic model integrates information from diverse data types and considers the data heterogeneity through the mixed-effects model. Leveraging on Bayesian theory, our prognostic model provides highly individualized failure prediction based on the smart tele-service system. Furthermore, the joint prognostic model has been extended to address the severe noise issue and the non-stationary behavior in the monitoring data. Those extensions increase the accuracy of the failure prediction significantly. All methods have shown advantageous features in both numerical studies and case studies with real world data from the smart tele-service systems in the application of automotive battery failure prognosis

Bio: Shiyu Zhou is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. He received his B.S. and M.S. in Mechanical Engineering from the University of Science and Technology of China in 1993 and 1996, respectively, and his master’s in Industrial Engineering and Ph.D. in Mechanical Engineering from the University of Michigan in 2000. His research interests include industrial data analytics for quality and productivity improvement methodologies by integrating statistics, system and control theory, and engineering knowledge. He is a recipient of a CAREER Award from the National Science Foundation and the Best Application Paper Award from IIE Transactions. He is currently the editor for the Design and Manufacturing focus issue of IISE Transactions, a fellow of ASME and member of IIE, INFORMS, and SME.

Additional Information

In Campus Calendar

School of Industrial and Systems Engineering (ISYE)

Invited Audience
Faculty/Staff, Public, Undergraduate students, Graduate students
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  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Jan 10, 2017 - 10:17am
  • Last Updated: Apr 13, 2017 - 5:13pm