Keywords
Artificial Intelligence in Manufacturing, Smart Manufacturing, Intelligent Automation, Industry 4.0, Industry 5.0, Machine Learning in Manufacturing, Industrial IoT, Cyber-Physical Systems, Digital Twins, Predictive Maintenance, Computer Vision, Robotics and Automation, Edge AI, Cloud Manufacturing, Additive Manufacturing, Big Data Analytics, Supply Chain Optimization, Sustainable Manufacturing, Autonomous Factories, Real-Time Industrial AnalyticsAI-Enabled Manufacturing Processes and Intelligent Automation : Volume 02 : Integration of AI and ML into Manufacturing - Volume 02
edited by: Hitesh VasudevLength: 229 mm | Breadth: 22.6 mm | Height: 152 mm | Imprint: NIPA | Weight: GMS
This book will be available from 13-Sep-2026
AI-Enabled Manufacturing Processes and Intelligent Automation provides a comprehensive exploration of the transformative role of artificial intelligence in modern manufacturing systems. The book presents the foundational concepts of AI, machine learning, deep learning, reinforcement learning, and computer vision, highlighting their applications in intelligent production, adaptive control, quality inspection, and automated decision-making. It examines the integration of cyber-physical systems, Industrial Internet of Things (IIoT), digital twins, cloud manufacturing, and edge AI technologies that are shaping smart and connected manufacturing environments.
Special emphasis is given to intelligent automation, predictive maintenance, supply chain optimization, additive manufacturing, materials processing, and sustainable manufacturing practices driven by real-time analytics and data-centric approaches. The volume also addresses important concerns related to data security, ethical implications, workforce transformation, and human–machine collaboration in AI-driven industries.
Designed for researchers, academicians, engineers, and industry professionals, this book serves as a valuable resource for understanding emerging trends such as Industry 5.0, autonomous factories, and future intelligent manufacturing ecosystems.
Chapter 1. Introduction to AI-Enabled Manufacturing
Chapter 2. Reinforcement Learning and Adaptive Control in Manufacturing
Chapter 3. Computer Vision and Deep Learning for Quality Inspection
Chapter 4. Smart Manufacturing Architectures and Cyber-Physical Systems
Chapter 5. Edge AI-Driven Real-Time Analytics for Smarter and Resilient Manufacturing
Chapter 6. Artificial Intelligence in Additive Manufacturing and Advanced Materials Processing
Chapter 7. Fundamentals of Artificial Intelligence and Machine Learning for Manufacturing
Chapter 8. Edge AI and Real-Time Industrial Analytics
Chapter 9. Intelligent Automation and Autonomous Production Systems
Chapter 10. AI for Robotics and Human–Robot Interaction
Chapter 11. AI in Inventory Management and Logistics Optimization
Chapter 12. Energy-Efficient Manufacturing Systems Using AI
Chapter 13. Artificial Intelligence in Manufacturing: Integrating Ethics, Security, and Innovation for Sustainable Development
Chapter 14. Cloud Manufacturing and AI-Based Platforms
Chapter 15. AI-Driven Predictive Maintenance and Asset Management
Chapter 16. Role of Big Data Analytics in Manufacturing Intelligence
Chapter 17. AI in Workforce Training and Skill Development
Chapter 18. Digital Twins and Simulation-Driven Manufacturing Intelligence
Chapter 19. Data Acquisition, Sensors, and Industrial IoT in Smart Manufacturing
Chapter 20. Machine Learning Principle and Workflow
Chapter 21. Supply Chain Analytics and AI-Based Production Planning
Chapter 22. Artificial Intelligence in Manufacturing Process Optimization
Chapter 23. Smart and Green Manufacturing: The Role of Artificial Intelligence in Sustainable Industry
Chapter 24. Future Trends: Industry 5.0, Autonomous Factories, and Beyond