2017-09-11l 조회수 1159
1. 제목 : Smart Production Systems
2. 연사 : Semyon M. Meerkov
Department of Electrical Engineering and Computer Science
University of Michigan
Ann Arbor, MI, USA
3. 일시 : 9월 11일 월요일 오전 11시
4. 장소 : 글로벌공학센터 (38동) 422호
5. 연사소개 및 세미나 내용 :
미르코프 교수는 vibrational control 의 원리를 해석하고 적용 가능한 시스템의 범위를 밝히는 업적으로 IEEE Fellow가 되었고 제어와 통신, 그리고 생산시스템 분야에서 많은 연구 업적을 남겼습니다. 이번 세미나는 특히 industry 4.0 동향과 부합하는 스마트 생산 시스템에 관한 내용입니다. 미르코프 교수는 생산 시스템 분야 연구에서 업적이 매우 뛰어나고 특히 실제 측정을 바탕으로 현장에 적용이 가능한 실용적 이론을 연구하시는 것으로 명성이 있습니다. 4차 산업혁명에 대한 관심이 높은 때 그 핵심 기술인 스마트 생산 시스템에 관한 연구결과를 소개하는 세미나를 개최하니 많은 분들의 참석을 부탁드립니다.
초록: Smart Production Systems (SPS) are manufacturing systems capable of self-diagnosing and providing operation managers with an advice concerning optimal continuous improvement projects, with analytically predicted results. In SPS, both manufacturing equipment and decision-making processes are automated. As such, SPS can be viewed as a part of the Industry 4.0 movement. To be “smart”, a production system must be equipped with an Advising Tool (AT) intended to calculate the optimal decision for productivity improvement. The AT developed in this work consists of three units: Information Unit (IU), Analytics Unit (AU), and Optimization Unit (OU). The IU is intended to utilize sensing, computing, and communication devices (e.g., Industry 4.0 technology), in order to monitor system’s performance metrics (i.e., throughput, WIP, blockages, starvations, etc.) and machine parameters (i.e., cycle time, MTBF, MTTR, etc.), and communicate this information to AU and OU. Based on this information and the theory of Production Systems Engineering (see our textbook under the same title, Springer 2009), the AU is intended to quantitatively evaluate the “health” of the production system, investigate various “what if” scenarios for potential improvement, and autonomously design a continuous improvement project, along its analytically predicted results. Finally, the OU is intended to develop an optimal way for implementing the above continuous improvement project, using the methods of Artificial Intelligence. The outputs of AU and OU form the advice to the operations manager. In this talk, the theoretical foundations of all three units of AT will be discussed, and an SPS development for the underbody assembly system at an automotive assembly plant will be described.
6. 약력 :
Semyon M. Meerkov received his MSEE degree from the Polytechnic of Kharkov, Ukraine, in 1962 and Ph.D. in Systems Science from the Institute of Control Sciences, Moscow, Russia, in 1966. He was with the Institute of Control Sciences until 1977. From 1979 to 1984 he was with the Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL. Since 1984 he has been a Professor at the Department of Electrical Engineering and Computer Science of the University of Michigan, Ann Arbor, MI. He held visiting positions at UCLA (1978-1979), Stanford (1991), Technion, Israel (1997-1998, 2008, and 2017), Tsinghua, China (2008), and Ben-Gurion University, Israel (2011). He was the Editor-in-Chief of Mathematical Problems in Engineering, Department Editor for Manufacturing Systems of IIE Transactions and Associate Editor of several other journals. Presently, he is on the Editorial Board of the International Journal of Production Research and Associate Editor of Automation and Remote Control. He is a Life Fellow of IEEE and Foreign Member of the Russian Academy of Sciences. His current research interests are in Systems and Control (with applications to production systems) and in Mathematical Theory of Rational Behavior (with applications to resilient monitoring and control).
7. 주관기관 :
서울대학교 자동화시스템공동연구소 제어계측신기술연구센터
DGIST CPS Global Center
8. 문의 : 심형보 교수(880-1745,880-6486)