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2018.02.01 ~ 3

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Professor
Professor
Jumyung Um Professor
  • Dgree
  • POSTECH 공학박사
  • Interest
  • 스마트팩토리, 적측형 공정, 증강현실, 지능형제품
  • Tel
  • 031-201-3695
  • Email
  • jayum@khu.ac.kr
Education
Ph.D., Pohang University of Science and Technology, Industrial Engineering, Republic of Korea, 2012.2 B.S., Sung Kyun Kwan University, Information and Communication Engineering / Mechanical Engineering, Republic of Korea, 2002. 2
Career
Assistant professor, Kyung Hee University, Republic of Korea, 2018 – Present Senior researcher, German research center of Artificial Intelligence / SmartFactory KL, 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
Paper
 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
Interest
Smart Factory / Industry 4.0 Argument reality for factory operators Additive manufacturing Edge computing of manufacturing system Computer Aided Design & Engineering Product intelligence