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엄주명 교수
- 최종학위
- POSTECH 공학박사
- 연구분야
- 스마트팩토리, 적측형 공정, 증강현실, 지능형제품
- 연구실위치
- 공학관 426호
- 연구실전화
- 031-201-3695
- 이메일
- jayum@khu.ac.kr
학력
Ph.D., Pohang University of Science and Technology, Industrial Engineering, Republic of Korea, 2012.2
B.S., SungKyunKwan University, Information and Communication Engineering / Mechanical Engineering, Republic of Korea, 2002. 2
주요경력 및 활동
Assistant professor, Kyung Hee University, Republic of Korea, 2018 – Present
Senior researcher, German research center of Artificial Intelligence / SmartFactoryKL, Germany, 2016 – 2018
Invited research professor / principle researcher, POSTECH, Republic of Korea, 2015 – 2016
Invited research professor, École centrale de Nantes, France, 2015
Research associate, University of Cambridge, United Kingdom, 2014 – 2015
Post-doctor researcher, École Polytechnique Fédérale de Lausanne, Switzerland, 2012 – 2014
ISO TC 184 SC1/WG7 & WG9 committee member, 2008 – present
ISO JTC1 WG12 committee member, 2018 – present
논문
Volkan Gezer and Jumyung Um and Martin Ruskowski, (2018). An Introduction to Edge Computing and A Real-Time Capable Server Architecture, IARIA Journals, submitted in 15th February.
Jeon, Byeong Woo, Jumyung Um, Soo Cheol Yoon, and Suh Suk-Hwan. "An architecture design for smart manufacturing execution system." Computer-Aided Design and Applications, 2016, Page 1-14.
Yoon, SooCheol, Jumyung Um, Suk-Hwan Suh, Ian Stroud, and Joo-Sung Yoon. "Smart Factory Information Service Bus (SIBUS) for manufacturing application: requirement, architecture and implementation." Journal of Intelligent Manufacturing (SCIE), 2016, Page 1-20.
Jumyung Um, Ian Anthony Stroud, “Design guidelines for remote laser welding in automotive assembly line“, International Journal of Advanced Manufacturing Technology (SCIE), accepted in 26nd June 2016.
Jumyung Um, Matthieu Rauch, Jean-Yves Hascoët and Ian Anthony Stroud, “STEP-NC compliant multiple-process planning of Additive manufacturing: Automotive remanufacturing“, International Journal of Advanced Manufacturing Technology (SCIE), accepted in 14th May 2016.
Jumyung Um, Ian Anthony Stroud, Suk-Hwan Suh, “STEP-NC machine tool data model and its applications”, International Journal of Computer Integrated Manufacturing, Published online in 1st January 2016 (SCIE).
Jumyung Um, Suk-Hwan Suh, "Design method for developing a product recovery management system based on life cycle information", International Journal of Precision Engineering and Manufacturing-Green Technology (SCIE), Volume 2, Issue 2, 12th April 2015, Page 173-187.
Jumyung Um, Ian Anthony Stroud, Suk-Hwan Suh, “Development and evaluation of customization for ubiquitous product recovery management system,” International Journal of Computer Integrated Manufacturing (SCIE), Volume 28, Issue 9, 2015, Page 903-919.
Seung-Jun Shin, Jumyung Um, Joo-Sung Yoon, Suho Jeong, Jae-Min Cha, Suk-Hwan Suh and Dae-Hyuk Chung, “Developing ISO 14649-based conversational programming system for multi-channel complex machine tools.” International Journal of Computer Integrated Manufacturing (SCIE), Volume 22, Issue 6, May 2009, Page 562–575
Seung-Jun Shin, Jumyung Um, Joo-Sung Yoon, Suho Jeong, Jae-Min Cha, Suk-Hwan Suh, Kyeong-Tak Ha, Dae-Hyuk Chung, “Developing an ISO 14649-based e-CAM System Supporting Multi-channel e-CNC for Composite Machine Tools”, Journal of the Korean Society of Precision Engineering (KCI), Volume 26, No.4, April 2009, Page 23-32.
Jumyung Um, Joo-Sung Yoon, Suk-Hwan Suh, “An architecture design with data model for product recovery management systems.” Resources, Conservation and Recycling (SCIE) , Volume 52, Issue 10, August 2008, Page 1175-1184
Suk-Hwan Suh, Seung-Jun Shin, Joo-Sung Yoon, Jumyung Um, “UbiDM: A New Paradigm for Product Design and Manufacturing via Ubiquitous Computing Technology.” International Journal of Computer Integrated Manufacturing (SCIE), Volume 21, Issue 5, June 2008, pages 540 - 549
연구관심분야
Smart Factory / Industry 4.0
Argument reality for factory operators
Additive manufacturing
Edge computing of manufacturing system
Computer Aided Design & Engineering
Product intelligence