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Yong-Hong (Hrsg.) Kuo

Intelligent Engineering and Management for Industry 4.0

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Industry 4.0 is changing how we manage operations to drive systems more intelligently. Technologies and applications are rapidly evolving. Disruptive technologies, such as artificial intelligence, big data, cloud computing and digital twin, are shaking up different industries and have motivated us to revisit engineering and management tools for improving system design, efficiency, effectiveness, reliability, and responsiveness. While these emerging technologies have powered new applications, novel industrial engineering methodologies are required to achieve the goals.Industrial Engineering was sprouted from major engineering disciplines that… Mehr

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Produktdetails


Weitere Autoren: Fu, Yelin (Hrsg.) / Wang, Junwei (Hrsg.) / Or, Calvin Ka-lun (Hrsg.) / Huang, George G. (Hrsg.) / Chen, Peng-Chu (Hrsg.)
  • ISBN: 978-3-030-94682-1
  • EAN: 9783030946821
  • Produktnummer: 39148607
  • Verlag: Springer International Publishing
  • Sprache: Englisch
  • Erscheinungsjahr: 2022
  • Seitenangabe: 196 S.
  • Masse: H28.5 cm x B21.5 cm x D1.6 cm 745 g
  • Auflage: 1st ed. 2022
  • Abbildungen: HC runder Rücken kaschiert
  • Gewicht: 745

Über den Autor


Yong-Hong Kuo is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his M.Phil and Ph.D. in Systems Engineering & Engineering Management at the Chinese University of Hong Kong. His research spans theory and actual application of mathematical modeling and optimization for decision problems encompassing the ¿eld of operations research & management science with a focus on discrete optimization, system simulation, and simulation optimization. He is on the Editorial Advisory/Review Boards of Decision Sciences Journal and Transportation Research Part E. Yelin Fu is a Post-doctoral Fellow at the Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong. Dr. Fu earned two Ph.D. degrees from the College of Business, City University of Hong Kong, and School of Management, University of Science and Technology of China. Dr. Fu does research in multiple criteria decision analysis, robust optimization, composite indicators methodology and e-commerce logistics. Peng-Chu Chen is an Assistant Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his Ph.D. in Industrial Engineering at Purdue University and his M.S. in Transportation Engineering at the University of California, Berkeley. He is a member of both INFORMS and SIAM. Calvin Ka-lun Or is an Associate Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned his Ph.D. in Industrial and Systems Engineering at the University of Wisconsin-Madison and his M.S. in Industrial Engineering at Mississippi State University. He was President of the Hong Kong Ergonomics Society from 2019-2021. He is an Editor for Applied Ergonomics Journal and is on the Editorial Board for various ergonomics and health informatics journals. George G. Huang is Chair Professor and Head of Department in the Department of Industrial and Manufacturing Systems Engineering at The University of Hong Kong. He earned his BEng and PhD in Mechanical Engineering from Southeast University (China) and Cardiff University (UK) respectively. He has conducted research projects in the field of Physical Internet for Smart Manufacturing and Logistics with substantial government and industrial grants. He has published extensively including over two hundred refereed journal papers in addition to over 200 conference papers and ten monographs, edited reference books and conference proceedings. Junwei Wang is an Assistant Professor in the Dept. of Industrial and Manufacturing Systems Engineering at the University of Hong Kong. He earned a Ph.D. at the University of Saskatchewan, Canada and another at Northeastern University, China. His research interests include Transportation Systems, Modeling and Optimization.

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