The book provides a comprehensive introduction to the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in modern industrial systems. The book explores how smart manufacturing technologies are reshaping conventional production environments into intelligent, connected, and data-driven ecosystems. It systematically covers core concepts of Industry 4.0, data acquisition, analytics, statistical modeling, predictive maintenance, computer vision, deep learning, digital twins, and Industrial Internet of Things (IIoT) applications. Emphasis is also placed on human–AI collaboration, sustainable manufacturing practices, Industry 5.0 principles, cybersecurity, ethical considerations, and global industrial standards.

Combining theoretical foundations with practical industrial applications, the book serves as a valuable resource for researchers, academicians, graduate students, and industry professionals in manufacturing engineering, industrial automation, artificial intelligence, and data science. It aims to support the development of intelligent, resilient, and sustainable manufacturing systems for the future.

Prof. (Dr.) Hitesh Vasudev is working as a Professor in the School of Mechanical Engineering, Lovely Professional University, Phagwara, Punjab, India. He has received his Ph.D. degree from Guru Nanak Dev Engineering College, LudhianaIndia in 2018 under the guidance of Prof. (Dr.) Harmeet Singh, GNDEC, Ludhiana and Dr. Lalit Thakur, NIT, Kurukshetra. His research areas include Surface Engineering/Thermal Spraying (HVOF, FLAME SPRAY, COLD SPRAY AND PLASMA SPRAY AND MICROWAVE CLADDINGS) -Currently working on the development of Nanostructured || Multi-modal || High entropy alloys coatings for high temperature oxidation and corrosion resistance -Thermal Barrier Coatings (TBCs) Microwave processing of materials and slurry erosion behavior using Machine Learning to Develop prediction models. He has successfully supervised numerous master’s and bachelor students, with 13 Ph.D. degrees awarded under his guidance. Recently, he has listed in World top 2% Scientists twice published by Stanford University and Elsevier-2023, 2024 & 2025, and also in Carrer List of Scientists. He has contributed extensively in thermal spray coatings in repute journals which include Surface coatings and Technology, Materials Today Communications, Engineering Failure Analysis, Journal of Cleaner Production, Surface Topography: Metrology and Properties and Journal of failure prevention and control, International Journal of Surface Engineering and Interdisciplinary Materials Science under the flagship of various publication groups such as Elsevier, Taylor & Francis, Springer nature, IGI Global and In-Tech Open. Moreover, he is a dedicated reviewer of reputed journals such as Surface Coatings and Technology, Journal of Thermal Spray and Technology, Ceramics International, Journal of Material Engineering Performance, Engineering Failure Analysis, Surface Topography: Metrology and Properties Material Research Express, Engineering Research Express and IGI Global journals etc. He has been awarded a "Top Cited Paper Awards India 2022" by @ IOP Publishing, United Kingdom in Review Category. He has won Research Excellence Award- 2019, 2020, 2021, 2022, 2023, 2024 and 2025 in Lovely Professional University. He has published over 200+ publications and 15 books. He has been granted a patent titled “High- Temperature Oxidation and Erosion Resistant Alloy-718/Al2 O3 Composite Coatings”

Chapter 1. Introduction to Smart Manufacturing and Industry 4.0
Chapter 2. Data Acquisition and Management for Smart and Sustainable Manufacturing Systems
Chapter 3. Fundamentals of Artificial Intelligence for Manufacturing
Chapter 4. Statistical and Data-Driven Approaches for Intelligent and Resilient Manufacturing Systems
Chapter 5. Manufacturing Data Acquisition and Management in the Era of Industry 4.0: Concepts, Architectures, Analytics, and Applications
Chapter 6. Human–AI Collaboration in Smart Factories: Towards Sustainable and Inclusive Industry 5.0
Chapter 7. Statistical and Data-Driven Modeling for Manufacturing System
Chapter 8. Intelligent and Ethical Manufacturing: Harnessing AI, IIoT, and Robotics for Industry 5.0
Chapter 9. Deep Learning Techniques for Smart Manufacturing
Chapter 10. Sustainability and Green Manufacturing Enabled by AI
Chapter 11. Natural Language Processing for Industrial Knowledge Management
Chapter 12. Digital Twins and Cyber-Physical Manufacturing Systems
Chapter 13. Human–AI Collaboration and Smart Factory Integration
Chapter 14. Smart Factory Integration and Industrial IoT Platforms
Chapter 15. Cybersecurity and Data Privacy in AI-Driven Manufacturing
Chapter 16. AI-Driven Predictive Maintenance and Asset Management
Chapter 17. Computer Vision and Deep Learning for Quality Inspection
Chapter 18. Challenges, Ethics, and Future Directions of AI-Driven Manufacturing