Industry 4.0, Smart Manufacturing, and Industrial Engineering

Amit Kumar Tyagi is an Assistant Professor, at the National Institute of Fashion Technology, New Delhi, India. Previously he worked as an Assistant Professor (Senior Grade 2), and Senior Researcher at Vellore Institute of Technology (VIT), Chennai Campus, India from 2019-2022. He received his Ph.D. Degree (Full-Time) in 2018 from Pondicherry Central University, India. He joined the Lord Krishna College of Engineering, Ghaziabad (LKCE) from 2009 to 2010, and 2012 to 2013. He was an Assistant Professor and head researcher at Lingaya’s Vidyapeeth (formerly known as Lingaya’s University), India from 2018 to 2019. He supervised one PhD thesis and more than ten Master dissertations. He has contributed to several projects such as “AARIN” and “P3- Block” to address some of the open issues related to privacy breaches in Vehicular Applications (such as Parking) and Medical Cyber-Physical Systems (MCPS). He has published over 200 papers in refereed high-impact journals, conferences, and books, and some of his articles won best paper awards. Also, he has filed more than 25 patents (Nationally and Internationally) in the areas of Deep Learning, Internet of Things, Cyber-Physical Systems, and Computer Vision. He has edited more than 25 books for IET, Elsevier, Springer, CRC Press, etc. Additionally, he has authored 4 Books on Intelligent Transportation Systems, Vehicular Ad-hoc Network, Machine learning and Internet of Things, with IET UK, Springer Germany, and BPB India publisher. He won the Faculty Research Award of the Year for 2020, 2021, and 2022 consecutively, given by Vellore Institute of Technology, Chennai, India. Recently, he was awarded the best paper award for his paper “A Novel Feature Extractor Based on the Modified Approach of Histogram of Oriented Gradient”, in ICCSA 2020, Italy (Europe). His current research focuses on Next Generation Machine Based Communications, Blockchain Technology, Smart and Secure Computing and Privacy. He is a regular member of the ACM, IEEE, MIRLabs, Ramanujan Mathematical Society, Cryptology Research Society, Universal Scientific Education and Research Network, CSI, and ISTE. Shrikant Tiwari (Senior Member, IEEE) received his Ph.D. in the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012 and his M. Tech. in Computer Science and Technology from the University of Mysore (India) in 2009. Currently, he is working as an Associate Professor in the Department of Computer Science & Engineering (CSE) School of Computing Science and Engineering (SCSE) at Galgotias University (India). He has authored or co-authored more than 75 national and international journal publications, book chapters, and conference articles. He has five patents filed to his credit. His research interests include machine learning, deep learning, computer vision, medical image analysis, pattern recognition, and biometrics. Dr. Tiwari is a member of ACM, IET, FIETE, CSI, ISTE, IAENG, SCIEI. He is also a guest editorial board member and a reviewer for many international journals of repute. Sayed Sayeed Ahmad is a seasoned academician with nearly 20 years of experience in the educational sector across the UAE. He earned his Ph.D. in Management from Banasthali Vidyapith, India, and another Ph.D. in Computer Science and Engineering from Integral University, India. Dr. Ahmad has served at prestigious institutions like De Montfort University Dubai, Rochester Institute of Technology Dubai, University of Dubai, and Al Ghurair University Dubai, showcasing his expertise in a wide array of subjects from machine learning to computer engineering. His contributions extend beyond teaching to include curriculum development, quality assurance, and research with publications and patents in advanced technology fields.

1. Introduction to Industry 4.0. 2. Security Concerns and Controls of Intelligent Cobots of Industry 4.0. 3. Big Data Analytics (BDA) for Industry 5.0. 4. Machine Learning – Enabled Predictive Analytics for Quality Assurance in Industry 4.0 and Smart Manufacturing: A Case Study on Red and White Wine Quality Classification. 5. Leveraging Clustering Algorithms for Predictive Analytics in Blockchain Networks. 6. Use of Digital Twin and Internet of Vehicles Technologies for Smart Electric Vehicles in the Manufacturing Industry. 7. AI Applications in Production. 8. IoT-Driven Supply Chain Management: A Comprehensive Framework for Smart and Sustainable Operations. 9. Supply Chain Management in the Digital Age for Industry 4.0. 10. Artificial Intelligence, Computer Vision and Robotics for Industry 5.0. 11. Data Analytics and Decision-Making in Industry 4.0. 12. Evolving Landscape of Industrial Engineering in Modern Era. 13. Artificial Intelligence (AI)-Enhanced Digital Twin Technology in Smart Manufacturing. 14. Smart Manufacturing: Navigating Challenges, Seizing Opportunities, and Charting Future Directions - A Comprehensive Review. 15. Industry 4.0 in Manufacturing, Communication, Transportation, Healthcare. 16. Artificial Intelligence-Based Anomaly Detection for Industry 4.0: A Sustainable Approach. 17. Future of Industry 5.0 in Society 5.0: Human-Computer Interaction-Based Solutions for Next Generation. 18. The Future of Manufacturing and Artificial Intelligence: Industry 6.0 and Beyond.