Keywords
Artificial Intelligence in Manufacturing, Machine Learning for Smart Manufacturing, Industry 4.0 Technologies, Industry 5.0 Applications, Smart Factory Systems, Industrial Internet of Things, AI-Driven Manufacturing, Predictive Maintenance Systems, Deep Learning in Manufacturing, Computer Vision for Quality Inspection, Digital Twins in Manufacturing, Cyber-Physical Systems, Manufacturing Data Analytics, Sustainable Manufacturing Technologies, Industrial Automation Systems, Human-AI Collaboration, Intelligent Manufacturing Systems, Industrial Cybersecurity, Data-Driven Manufacturing, Natural Language Processing in IndustryArtifical Intelligence and Machine Learning for Smart Manufacturing
edited by: Hitesh VasudevLength: 229 mm | Breadth: 24.2 mm | Height: 152 mm | Imprint: NIPA | Weight: GMS
This book will be available from 12-Jul-2026
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.
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