International Journal of Modeling, Simulation, and Scientific Computing

Call for Papers

Special Issue on Digital Twins for Intelligent Manufacturing and Robotics

Recently, rapid development of information and communication technology such as Internet of Things (IoT), 5G, cloud computing, edge computing, intelligent sensors, big data, artificial intelligence and their increasing embedding into and integration with advanced manufacturing enable intelligent manufacturing. Due to the great potential of intelligent manufacturing in bringing remarkable benefits, great competitive advantages, and numerous research opportunities, it has attracted a lot of attention from governments, enterprises, and researchers around the world. Simultaneously, as a class of manufacturing equipment, industrial robots play an increasingly important role in manufacturing, especially with their growing learning ability and adaptability enabled by artificial intelligence such as deep reinforcement learning, and contribute to the implementation of intelligent manufacturing.

Digital twin is an important underpinning technology for intelligent manufacturing and robotics. In the context of intelligent manufacturing and robotics, a digital twin is a virtual representation of a machine tool, a robot, or a manufacturing system that spans their lifecycles and updated with real-time data to accurately reflect the real-world counterparts. The virtual model can thus be used to generate possible improvements and valuable insights through simulations, which can then be applied back to the corresponding physical equipment/product, systems, and processes. Digital twin constitutes the core of future Cyber-Physical Production Systems, and is also vital for intelligent control and decision-making of industrial robots, and therefore opens up new revenues for academic research and industrial applications.

Significant advances of digital twins in intelligent manufacturing and robotics have been achieved. But related research, industrial implementation, and applications are overall still at the very early stage and numerous opportunities are to be uncovered. This special issue aims to further advance academic research, industrial implementation and applications, and provide a forum for presenting latest insights and thoughts from all relevant parties.

The theme of the special issue includes, but is not limited to:

• Function, system and technology architecture of digital twins for intelligent manufacturing and robotics
• Technologies and methodologies for development, construction, and applications of digital twins, e.g. model engineering technologies for digital twins
• Quality assurance, evaluation, verification, security and privacy, and standards of digital twins
• Industrial implementation and applications of digital twins

Guest Editorial Team:

Lead Guest Editor
Dr. Yongkui Liu
Associate Professor, Xidian University, Xi’an, China
Official Email ID: ykliu@mail.xidian.edu.cn
Google Scholar: https://scholar.google.com/citations?user=ddmHL5MAAAAJ&hl=zh-CNamp;oi=ao
Research Gate: https://orcid.org/0000-0003-2165-775X

Dr. Yongkui Liu is an associate professor at the School of Mechano-Electronic Engineering, Xidian University. He received his Ph.D. from Xidian University, China, in 2010. From 2011 to 2018, he worked as a postdoctoral fellow at Beihang University in Beijing, The University of Auckland in New Zealand, and the Royal Institute of Technology in Sweden, respectively. His research interests include cloud manufacturing, intelligent scheduling of manufacturing systems, intelligent robots, digital twin, and big data analytics. He has published over 50 papers in international journals and conferences. He serves as editorial boards and guest editors for several well-known international journals, including International Journal of Modeling, Simulation, and Scientific Computing and Robotics and Computer-Integrated Manufacturing, etc.

Co-Guest Editorsr
Dr. Ray Y Zhong
Assistant Professor, Department of Industrial and Manufacturing Systems Engineering
The University of Hong Kong, Hong Kong
Official Email ID: zhongzry@hku.hk
Google Scholar: https://scholar.google.co.nz/citations?user=KfDl2DIAAAAJ&hl=enamp;oi=sra
ResearchGate: https://www.researchgate.net/profile/Ray-Zhong

Dr. Ray Y Zhong is an Assistant Professor in The Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong. He was a lecturer in The Department of Mechanical Engineering, University of Auckland, New Zealand from 2016-2019. Ray gained his M.Phil. and Ph.D. in Signal & Information Processing and Industrial & Manufacturing Systems Engineering from the Guangdong University of Technology (China) and The University of Hong Kong (Hong Kong) respectively. His research interests include Internet of Things (IoT)-enabled manufacturing, Big Data in manufacturing & SCM and data-driven APS. He has published over 160 papers in international journals and conferences. Ray serve as editorial boards and guest editors for several well-known international journals: International Journal of Production Economics, Computers & Industrial Engineering: An International Journal, International Journal of Computer-Integrated Manufacturing, etc. In addition, he has participated in a set of projects sponsored by the National R&D department, HK ITF and HKU. He is a member of HKIE, ASME (USA), IET (UK), IEEE (USA) and LSCM HK.

Co-Guest Editorsr
Dr. Vincent Xi Wang
Associate professor
Department of Production Engineering
KTH Royal Institute of Technology
Brinellvägen 68, 114 28 Stockholm, Sweden
Official Email ID: wangxi@kth.se
Google Scholar: https://scholar.google.com/citations?user=JfOD5J8AAAAJ&hl=en
ResearchGate: https://www.researchgate.net/profile/Xi-Wang-32/stats

Dr. Xi Vincent Wang is an Associate Professor in the IIP Department of Production Engineering, KTH Sweden. He is working with the division of Sustainable Manufacturing Systems (SPS). In 2021 Vincent received his Docentship from KTH. He received his PhD and Bachelor degrees in Mechanical Engineering from the University of Auckland (New Zealand) and Tianjin University (China), respectively in 2013 and 2008. Vincent’s main research focus includes Cloud-based manufacturing, sustainable manufacturing, robotics, digital twin, computer-aided design, and manufacturing systems. He also serves as the Managing Editor of the International Journal of Manufacturing Research (IJMR), Associate Editor of SME Journal of Manufacturing Systems (JMS), and Array – Open Access Journal by Elsevier, and Editorial Board Member of other 3 international journals.