WCCI2020-CISM

IEEE WCCI2020 Special Session on Computational Intelligence and Smart Manufacturing (CISM)

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IEEE WCCI2020 Special Session on Computational Intelligence and Smart Manufacturing (CISM)

https://wcci2020.org/cross-disciplinary-applications-sessions/

https://leoyichen.github.io/WCCI2020-CISM/

@ wcci2020.org

1. Title:

Computational Intelligence and Smart Manufacturing (CISM)

2. Aims:

Computational Intelligence (CI) offers a wealth of ideas for solving real-world problems. Smart manufacturing (SM) employs computer-integrated engineering in industrial value chain. The special session in ‘Computational Intelligence and Smart Manufacturing’ aims to call for papers reporting various applications of CI to SM.

3. Scope:

This special session includes theoretical, numerical, and experimental contributions that describe original CI-related research results that address any aspect of design, optimization, manufacturing and engineering management in the context of SM.

Potential topics include, but are not limited to:

  • Scale up methodologies for novel manufacturing products and processes
  • Innovative design for manufacturing
  • Manufacturing informatics and ICT
  • Dynamical modelling and control for manufacturing machinery
  • Manufacturing with precision, efficiency, reliability and repeatability
  • Digital manufacturing
  • Manufacturing at the nano-scale, large-scale and cross-scale
  • Additive manufacturing
  • Big data in manufacturing
  • Wireless mechatronic embedded intelligent systems and applications
  • Industrial internet of things
  • Data analytics and decision making
  • The future industrial worker
  • Cyber-physical systems
  • Innovative service, customisation and management
  • Industrial software for manufacturing
  • Machining and forming technology
  • Non-traditional material removal processes
  • Machine tools technology
  • Materials in manufacturing
  • Laser technology and applications
  • Micro and nano-fabrication
  • Robotics, mechatronics and manufacturing automation
  • Precision engineering, inspection, measurement and metrology
  • Sustainable and green manufacturing
  • Computer-integrated manufacturing systems
  • CI techniques in manufacturing operations
  • Manufacturing planning, optimisation and simulation
  • Digital twins
  • AI and smart manufacturing standards

4. Organisers:

Dr Leo Chen, Professor Yun Li Professor Xifan Yao Professor Jorn Mehnen

1) Dr Leo Chen Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom. leo.chen@newcastle.ac.uk

Leo Chen (M’10-SM’17) received the B.Sc degree in Automotive Engineering from Chongqing University of Technology, in 2000, the M.Sc. degree in Automotive Engineering from Chongqing University, in 2004, and the Ph.D. degrees in Mechanical Engineering from University of Glasgow, in 2010. He has been taking a leading role in the previous and current department to maintain cross-disciplinary research links, and develop external research collaborations both nationally and internationally. Also, he has been leading a few research grants in the areas of artificial intelligence, high-performance computing, robotics and autonomous systems, and also studies in multi-disciplinary contexts. He has a high-level output of research publications in leading international journals and presentations at international conferences, which related to the research area of robotics, digital manufacturing, and industry 4.0, which demonstrates significant research and grant potential in engineering and cross-disciplinary applications. He is a member of IET, AAAI, AIAA, and ASME, a fellow of HEA, and a fellow of IMechE. He is also a Chartered Engineer. Dr Chen has published over 100 academic papers in both high impact international academic journal and international conferences and has been selected as a Publons’ top 1% of reviewers in Computer Science and Engineering. He has been actively involved in both academic research and KTP projects as PI and CoI funded by EPSRC (UK), Horizon2020 (EU), NSFC (China), National Key Research and Development Program of China and Industrial funding bodies. One of the co-organisers of the WCCI’16 Special Session on Computational Intelligence for Industry 4.0 and CEC’19 Special Session on Evolutionary Computation for Creativity, Manufacture and Engineering Management in the Industry 4.0 Era. Besides, he is an editorial board member, and he has been a guest editor for five special issues.

2) Professor Yun Li Industry 4.0 Artificial Intelligence Laboratory, Dongguan University of Technology, China, Yun.Li@ieee.org

Yun Li (S’87-M’90-SM’17-F’20) received the B.S. degree in electronics from Sichuan University in 1984, the M.E. degree in electronic engineering from University of Electronic Science and Technology of China in 1987, and the Ph.D. degree in parallel computing and control from University of Strathclyde in 1990. In 1989, he was Control Engineer with the U.K. National Engineering Laboratory. In 1990, he was Postdoctoral Research Engineer with Industrial Systems and Control Ltd, Glasgow. From 1991 to 2018, he was Lecturer, Senior Lecturer and Professor with University of Glasgow and served as its Founding Director of University of Glasgow Singapore. He is currently Founding Director of Dongguan Industry 4.0 Artificial Intelligence Laboratory and Distinguished Professor with Dongguan University of Technology, China. Since 1991, his research interest has been computational artificial intelligence and its applications. He is the author of the popular 1997 online interactive courseware for evolutionary algorithms, EA_demo (http://i4ai.org/EA-demo/). He has published 270 papers, one of which is seen among the top 5 in IEEE TSMC-B and another the most popular every month in IEEE TCST. Prof Li is an Associate Editor of the IEEE TEVC, TNNLS, and TETCI. He has co-led the U.K. founding council’s Industrial Systems in the Digital Age Network Plus. He is an FIEEE in the US and FRSA in the U.K.

3) Professor Xifan Yao School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China. mexfyao@scut.edu.cn

Xifan Yao received the B.S. degree from Hefei University of Technology, Hefei, China, in 1985, and the M.S. and Ph.D. degrees from South China University of Technology, Guangzhou, China, in 1988 and in 1999 respectively. From 1988, he has worked at South China University of Technology, and since 2004 he has been a professor. His research interests include digital manufacturing, integrated manufacturing systems, smart/intelligent manufacturing, proactive manufacturing, intelligent control and scheduling in complex manufacturing systems. He is the author of 3 books and published over 200 research papers at national and international journals, as well as conference proceedings.

4) Professor Jorn Mehnen Department of Design, Manufacturing and Engineering Management, University of Strathclyde, Glasgow G1 1XJ, UK. jorn.mehnen@strath.ac.uk

Priv.-Doz. Dr.-Ing. Dipl.-Inform. J?rn Mehnen has a background in machining technology (PhD) and soft computing (MSc) from TU Dortmund, Germany. He studied computer science and mathematics (Dipl.-Inform.). In 1995 he began his research career at the Department of Machining Technology (ISF) at the University of Dortmund, Germany. There he obtained his PhD (Dr.-Ing., summa cum laude) and received admittance for teaching (venia legendi, Habilitation) in 2005 as a Privatdozent (Priv.-Doz.). In 2007 he joined Cranfield University as a Senior Lecturer within the Manufacturing Department. He is also Privatdozent at TU Dortmund (Germany). In 2013 he was promoted to Reader in Computational Manufacturing at Cranfield University. In 2016, he was appointed to Professor at University of Strathclyde. Prof Mehnen is specialised in Advanced Digital Manufacturing. His research aims to deliver new and exciting scientific insights as well as practical technological solutions that help industry and academia alike. His current interests include Advanced Digital Manufacturing,?Industry 4.0 technology, Cyber Physical Systems (CPS), Industrial Internet of Things (IIoT)，Cloud Manufacturing and Big Data Analytics. His work around Design for Industry 4.0 and Digital Manufacturing is aiming to improve existing Manufacturing Systems to make them smarter, more autonomous and agile, cost efficient, better connected and well informed Through-Life. These efforts are supported by research into Additive Manufacturing, Data Analytics, Computational Intelligence and Visualisation.

5.Important Dates:

15 Jan 2020 Paper Submission Deadline

15 Mar 2020 Paper Acceptance Notification Date

15 April 2020 Final Paper Submission and Early Registration Deadline

19-24 July 2020 IEEE WCCI 2020, Glasgow, Scotland, UK

6. Submission

Submissions to this Special Session should follow the same submission guidelines as other papers of WCCI 2020. For more information, please refer to the WCCI2020 (wcci2020.org).

Go to WCCI2020 submission page: https://wcci2020.org/submissions/

Click on CEC: https://ieee-cis.org/conferences/cec2020/upload.php

Select SC29. Computational Intelligence and Smart Manufacturing (CISM)