Dr. Xiaoning Jin 学术报告

发布日期：2018-05-29 浏览：6175

Title: Augmenting Manufacturing System Intelligence through Data-Driven Analytics

标题：基于数据驱动分析的增强制造系统智能化研究

报告人：Dr. Xiaoning Jin (Assistant professor, Northeastern University)

时 间：2018年5月29日星期二 14:00-15:00

地 点：机械与动力工程学院 F301

邀请人：夏唐斌副教授（工业工程与管理系）

Abstract:

Modern manufacturing processes are often complex systems of numerous interacting components that operate in multiple physical domains and often follow highly nonlinear dynamics. This talk will describe a recently proposed hybrid modeling method that use data-driven models and physics-based models collaboratively in a multimodal data-rich manufacturing environment to characterize the process normal behavior, error propagation dynamics, hence enabling real-time process condition monitoring, fault detection and identification. The new hybrid modeling paradigm was applied to a semi-continuous manufacturing system-roll-to-roll (R2R) manufacturing system for elastic film products. It will be shown that integrating sensor-data fusion and data-driven methods in terms of process modeling carries significant potential benefits compared to the more traditional physics-based methods. The talk will be ended with a brief summary of possible future research directions both in terms of manufacturing process monitoring and diagnostics, and in terms of data-analytics in modern manufacturing.

Short Bio:

Xiaoning Jin is currently an assistant professor in the Department of Mechanical and Industrial Engineering at Northeastern University. She received her M.S. and Ph.D. degree in Industrial and Operations Engineering from the University of Michigan, Ann Arbor in 2008 and 2012 respectively. Her research interests include physics-based and data-driven predictive analytics and decision support tools for manufacturing system operations and maintenance, manufacturing process monitoring, diagnostics, prognostics and health management. Her works have been applied to a variety of industry applications ranging from advanced manufacturing systems such as automotive assembly systems, roll-to-roll printing process monitoring, smart operations and maintenance decision-making. She co-authored more than 40 published or accepted journal papers and conference proceedings. She is the recipient of several prizes and awards including the 2016 Outstanding Young Manufacturing Engineer Award from the Society of Manufacturing.