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  • 统计与管理学院2016年学术报告第38

    【主  题】Quality Engineering faces the challenges of big data and little data

    【报告人】 Fugee Tsung, Ph.D.

    Hong Kong University of Science & Technology

    【时  间】 2016年10月13日(星期四)15:00-16:00

    【地  点】 上海财经大学统计与管理学院大楼1208室

    【摘  要】This talk will present and discuss the challenges and opportunities that quality engineers face in the era of big data. The ability to separate signal and noise in the data-rich-information-poor environment would be the key, especially for industrial big data. Emerging issues include statistical process control and monitoring for big data streams, and reliability and maintenance modeling with big data.

    The second part of the talk will present and discuss the challenges and opportunities that quality engineers face in the era of additive manufacturing (i.e., 3D printing), where there is little data due to its one-of-a-kind nature. For example, quality control techniques originated from mass production cannot be applied directly to such a highly customized/personalized environment because such a small or single lot production does not have repeated measures of the same kind.

    【嘉宾简介】 Prof. Fugee Tsung is Professor of the Department of Industrial Engineering and Logistics Management (IELM), Director of the Quality and Data Analytics Lab, at the Hong Kong University of Science & Technology (HKUST). He is a Fellow of the Institute of Industrial Engineers (IIE), Fellow of the American Society for Quality (ASQ), Academician of the International Academy for Quality (IAQ) and Fellow of the Hong Kong Institution of Engineers (HKIE). He is Editor-in-Chief of Journal of Quality Technology (JQT), Department Editor of the IIE Transactions, and Associate Editor of Technometrics. He has authored over 100 refereed journal publications, and is the winner of the Best Paper Award for the IIE Transactions in 2003 and 2009. He received both his MSc and PhD from the University of Michigan, Ann Arbor and his BSc from National Taiwan University. His research interests include quality engineering and management to manufacturing and service industries, statistical process control and monitoring, industrial statistics and data analytics.

    【邀请人】 吴纯杰