The fourth industrial revolution (Industry 4.0) has brought the overall transformation using digital integration and intelligent engineering. It is quoted as the next level of manufacturing where machines will redefine themselves in how they communicate and perform individual functions. The notion of Industry 4.0 was coined by Kagermann et al. in 2011, which fuses the virtual and the real world with emphasis on engineering applications such as robotics, digitization, and automation. For any system to be regarded as Industry 4.0, constant connectivity, human assistance and decentralized decision making are absolute necessities. The essential components of Industry 4.0 comprised of cyber–physical systems (CPSs), additive manufacturing, virtual and augmented reality, cloud computing, big data analytics, data science etc. to name a few. While going through these application domains and key areas, it is found that energy efficiency, scheduling, big-data, real-time computing, reliability engineering, high computation time and decision making are some of the common major challenges of different Industry 4.0 systems.
Various studies have shown that digitization of products and services has become a necessity for a sound industrial ecosystem. However, these requirements and advanced technologies have made the systems more complex and led to many other challenges such as information security, reliability, integrity, etc. These are the major bottlenecks which need to be overcome with the use of computational intelligence (CI) approaches for the successful design and deployment of Industry 4.0. Therefore, this special session aims to introduce the necessity and use of computational intelligence techniques in the key areas of Industry 4.0.
Moreover, one of the purposes of this special session is to address the problem of uncertainty modelling in the industrial revolutions, whether it’s the ongoing Industry 4.0 or the upcoming industry 5.0 or society 5.0. We further aim to explore the explainability of the underlying algorithms and outcomes with respect to the industrial processes which ultimately helps in the decision making.
The broader scopes of this special issue (but not limited to) are as follows:
CI approaches for Cyber-Physical Systems/ Internet of Things/ Cloud Computing / Big Data Analytics /Transportation Systems
CI approaches for Social Network Analysis
CI approaches for Cyber Security
Transfer learning for Industry 4.0
CI approaches for Power Systems / Energy Optimization / Green Computing
CI approaches for Pollution Routing Problem
CI approaches for Smart manufacturing
CI approaches for Smart Industry
CI approaches in Digitization of supply chain
CI approaches for Digital Manufacturing
CI approaches for Sustainable Manufacturing
CI approaches for Autonomous Robot
CI for Reliability Engineering and System Safety
CI for Explainable Artificial Intelligence
CI approaches for Dynamic System
CI approaches for Efficent Transportaion
Generative adversarial networks for Industry 4.0
January 31, 2022 (11:59 PM AoE) - Paper submission deadline
April 26, 2022 - Notification of acceptance
May 23, 2022 - Final Paper Submission
18 - 13, July 2022 - IEEE WCCI 2022, Centro Congressi Padova, Itlay
Amit K. Shukla (firstname.lastname@example.org) is currently a Postdoctoral Researcher & Lecturer at Faculty of Information Technology, University of Jyvaskyla, Finland. He received his Ph.D. in Computer Science from South Asian University, New Delhi, India. Amit is a gold medalist in the master’s degree (2013) in Computer Science from South Asian University. He has chaired the ACM chapter of South Asian University from 2011/12 and currently a IEEE Young Professional and an active member of societies such as: IEEE Computational Intelligence Society and EUSFLAT. Amit recently joined the editorial board of Axioms journal of MDPI in July, 2021. He is a regular reviewer of Journals such as: Engineering Applications of Artificial Intelligence, Applied Soft Computing, IEEE Transactions on Fuzzy Systems, Neural Computing and Applications, Journal of Advanced Research etc. His research areas include: Fuzzy Sets and Systems, eXplainable Artificial Intelligence, anomaly detection, real-time systems, deep learning, and soft-computing techniques.
Rahul Nath (email@example.com) received his Ph.D. degree from Dept. of Computer Science, SAU, New Delhi in 2021. He got his B.Sc. degree from Delhi University and M.Sc. in Computer Science from South Asian University (SAU) in 2011 and 2013, respectively. Currently, he is a Post doctoral researcher at IRISA Université de Rennes 1, France. Rahul was a CSIR Senior research fellow. He is a member of several technical societies and participates in events actively. Rahul has ardently volunteered in organising several international workshops. His research interests include evolutionary computation, multi-objective/many objective, Bi-level optimization, Explainable AI and real-time systems.
Amit Rauniyar (firstname.lastname@example.org) received his Ph.D. degree form Department of Computer Science, South Asian University (SAU), New Delhi, India. He got his Bachelor degree in Computer Applications from HNB Garhwal University in 2012 and M.Sc. Computer Science in 2015 from SAU. He has always exhibited a profound interest in co-curricular activities and volunteered in organizing technical events at SAU. Amit is an active member of IEEE Computational Intelligence Society and IEEE Systems, Man and Cybernetics Society. His research interests include evolutionary algorithms, multi-factorial optimization, real-time, green logistics, cyber-physical systems and multi-robots systems.
Pranab K. Muhuri (email@example.com) received his Ph.D. degree in Computer Engineering in 2005 from IT-BHU [now Indian Institute of Technology, (BHU)], Varanasi, India. He is a Professor and Dean with the Department of Computer Science, South Asian University, India, and leading the computational intelligence research group. Pranab has been in the editorial board /guest editor and/or in the reviewers’ panel of a number of reputed journals such as Applied Soft Computing, Granular Computing, IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, Computers and Industrial Engineering, Engineering Applications of Artificial Intelligence, International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems, Wireless Personal Communication etc. He is serving in the Editorial Boards of two journals: Applied Soft Computing, and Engineering Application of Artificial Intelligence.