Aim:This Special Session is dedicated to the latest developments of computational intelligence (CI) for Industry 4.0, the first a-priori engineered (and the fourth) 'Industrial Revolution'. Focusing on smart manufacturing and cyber-physical systems so far, efforts in Industry 4.0 have lacked smart design and business elements for manufacture that are necessary in completing this unprecedented upgrade of value chain. Computational intelligence has however provided an extra-numeric, as well as efficiently-numeric, tool to realise this goal. The Special Session therefore encourages and reports applications to Industry 4.0 in the era of interactive cloud computing and data science.
Scope:Computational intelligence, primarily comprising artificial neural network and learning systems, evolutionary computation, and fuzzy logic and systems, is a set of nature-inspired modelling and optimisation approaches to complex real-world problems, to which traditional approaches such as first principles modelling and statistical or curve fitting are ineffective or incapable of addressing. We are soliciting original research papers or reviews that would shape and advance a smart design and business environment for Industry 4.0. Papers addressing how to revolutionise the way that smart designs are created and smart machines are built, thereby leading to a step improvement in manufacturing autonomy and industrial efficiency, performance and competitiveness, will be most welcome.
Main Topics (include but are not limited to):
- Computer intelligence or machine learning for cyber-physical systems;
- Computer-automated design, machine learning or intelligent search for Industry 4.0;
- Computational intelligence for smart design for smart manufacture;
- Computational intelligence for Industry 4.0 in cloud and big data environments;
- Computational intelligence and data science applications to marketing for design;
- Computational intelligence and data science for marketing and service in Industry 4.0 value chain;
- Computational intelligence or other learning techniques for Industry 4.0 business informatics and risk management;
- Computational intelligence for Industry 4.0 digital economy;
- Evolutionary distributed or cloud computing for interactive product design and marketing;
- Evolutionary big data interaction for predictive product design and marketing.
Conference Proceedings:This is a cross-disciplinary and CI applications Special Session. Therefore, a submitted paper (if duly accepted and presented) will be published under one of the three conference proceedings (IEEE CEC, Fuzzy-IEEE, or IJCNN) that is most appropriate to the paper. Such decision will be made by the Special Session Organizers in consultation with the Special Session Chair and one of the three Conference Chairs.
Names of Organisers:Professor Yun Li
School of Engineering
University of Glasgow, U.K.
Dr. Leo Chen
School of Engineering and Built Environment
Glasgow Caledonian University, U.K.
Asso. Prof. Cindy Goh
University of Glasgow Singapore
Republic of Singapore
Asso. Prof. Zhi-Hui Zhan
School of Advanced Computing
Sun Yat-sen University, China
Short Biography of the Organizers:Yun Li received his PhD from University of Strathclyde, U.K., in 1990. During 1989 and 1990, he was with U.K. National Engineering Laboratory and Industrial Systems and Control Ltd. He joined University of Glasgow as Lecturer in 1991, was Founding Director of University of Glasgow Singapore during 2011-2013 and served as Founding Director of the University's international joint programme with University of Electronic Science and Technology of China in 2013. He established and chaired both the IEEE Computer-Aided Control System Design Evolutionary Computation Working Group and the European Network of Excellence in Evolutionary Computing Workgroup on Systems, Control, and Drives for Industry in 1998. Professor Li is a Chartered Engineer in the U.K. and is currently an Associated Editor of IEEE Transactions on Evolutionary Computation. He has over 200 publications and one of them has been noted the most popular article every month in IEEE Transactions on Control Systems Technology.
Leo Chen, PhD, CEng, is currently Lecturer in Dynamics and Control at Glasgow Caledonian University. His research which has been published in scholarly journals and edited volumes, explores the aspects: computational intelligence, dynamics and control, multidisciplinary design and optimisation under uncertainty; reliability and risk analysis; dynamics and intelligent control, with the modelling and simulation of robotics, automotive systems, space tether systems, MOS device reliability, computational finance and optical engineering, etc. Dr. Chen also studies how people construct evaluations and preferences in social contexts. He has recently served as Guest Editor of Mathematical Problems in Engineering Special Issue on Computational Intelligence Approaches to Robotics, Automation, and Control.
Cindy Goh received her PhD from the University of Glasgow, U.K., in 2004. From 2011 to 2013, she was an Assistant Professor at the University of Glasgow, Singapore (UGS). In 2013, she was promoted to Associate Professor and became the Director of Research Programmes at UGS where she has overall responsibility for its research strategy and knowledge exchange portfolio. Her research interest is in intelligent optimisation and data analytics for optimal decision making and design to advance the state-of-the-art in complex engineering systems, energy and transport networks, and smart manufacturing. Her work has been published in internationally peer reviewed journals. She is a member of the IEEE, and a founding member of the International Union of Radio Science Committee, Singapore.
Zhi-Hui Zhan received his Bachelor's and PhD degrees from the Department of Computer Science of Sun Yat-Sen University, Guangzhou, China, in 2007 and 2013, respectively. He is currently an Associate Professor with the School of Advanced Computing, Sun Yat-sen University. His research interests include evolutionary computation, swarm intelligence, and their applications to real-world problems and in environments of cloud computing and big data. His PhD dissertation received the China Computer Federation Outstanding Dissertation Award in 2013. Dr. Zhan also received an award of the Natural Science Foundation for Distinguished Young Scientists of Guangdong Province, China, in 2014 and the Pearl River New Star in Science and Technology Award in 2015. Dr. Zhan is listed by Thomson Reuters as one of the Most Cited Chinese Researchers in Computer Science.