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, 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 issue aims to introduce the necessity and use of computational intelligence techniques in the key areas of Industry 4.0.
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
15 January, 2020 30 January, 2020 - Paper submission deadline
15 March, 2020 - Author notification of acceptance or rejection
15 April 2020 - Final Paper Submission and Early Registration Deadline
19-24 July 2020 - IEEE WCCI 2020, Glasgow, Scotland, UK
Department of Computer Science, South Asian University, New Delhi-110021, India,
Post-Doctoral Fellow at ENSSAT, IRISA Lab, University of Rennes 1, Lannion, France,
Pranab K. Muhuri 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 with the Department of Computer Science, South Asian University, India, where he is leading the computational intelligence research group. Pranab has been the guest editor of a number of special issues/sessions on computational intelligence related topics and applications. He is in the reviewers’ panel of a number of reputed journals such as IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, Fuzzy Sets and Systems, Computers and Industrial Engineering, International Journal of Uncertainty, Fuzziness, and Knowledge-Based Systems and Evolutionary Computation. Pranab’s current research interests are mainly in real-time systems, fuzzy systems, evolutionary optimization, perceptual computing, and machine learning. Pranab has published about more than 80 peer-reviewed papers in reputed journals and conferences including IEEE Transactions on Fuzzy Systems, Reliability Engineering and Systems Safety, Fuzzy Sets and Systems, Applied Soft Computing, Computers and Industrial Engineering and Future Generation Computer Systems. Currently, he is serving as editorial board member in two leading journals: Applied Soft Computing and Engineering Applications of Artificial Intelligence.
Dr. Amit K. Shukla is currently a Post-Doctoral Fellow at ENSSAT, IRISA LAB, France. He received his Ph.D. in Computer Science from South Asian University, New Delhi, India. He is a gold medal holder in his master’s degree (2013) in Computer Science from South Asian University. He has chaired the ACM chapter of South Asian University from 2011-12. He is also an IEEE Young Professional and an active member of societies such as: IEEE Computational Intelligence Society and EUSFLAT. His research areas include: higher order uncertainty modeling, fuzzy sets and systems, anomaly detection, real-time systems, deep learning, and soft-computing techniques.