题 目: Computation Services in Cybermanufacturing Systems（赛博制造系统的计算服务研究）
时 间：2018年6月1日 10:00-11:00
地 点：机械与动力工程学院 F207会议室
邀请人：潘尔顺教授（工业工程与管理系）
Abstract
Traditional smart manufacturing emphasizes data-driven decision making for individual systems. When manufacturing systems are connected, computation services executed by ubiquitous computing resources transform data sets to decisions that can adaptively improve productivity, quality and flexibility of a cybermanufacturing system. Such a system poses significant challenges in communication, computation and control. Motivated by these challenges, this presentation will mainly focus on how to improve performance, reliability and responsiveness of computation service. The authors proposed a recommendation-based adaptive pipeline methodology to identify the best method option in manufacturing customization. The authors proposed a predictive offloading methodology to minimize the energy consumptions of computation, while satisfying the constraints on computation availability and deadline of computation tasks. Manufacturing case studies were performed to validate the proposed methodologies.
Biography
Dr. Ran Jin is an assistant professor and the Director of Laboratory of Data Science and Visualization at the Grado Department of Industrial and Systems Engineering at Virginia Tech. He received his Ph.D. degree in Industrial Engineering from Georgia Tech, Atlanta, his Master’s degrees in Industrial Engineering and in Statistics, both from the University of Michigan, Ann Arbor, and his bachelor’s degree in Electronic Engineering from Tsinghua University, Beijing. His research focuses on Data Fusion in Smart Manufacturing, including the integration of different types of data sets (e.g., ensemble models), variables (e.g., quantitative and qualitative models), and information (e.g., product quality and equipment reliability) for synergistically modeling, monitoring and control of manufacturing processes and systems. He is currently serving as an Associate Editor for IISE Transactions, Focus Issue on Design and Manufacturing. For more information about Dr. Jin, please visit: https://ise.vt.edu/ran-jin
