AI AND INDUSTRY 4.0 IN MECHATRONICS: Intelligent Systems, Cyber-Physical Architectures, and the Future of Smart Manufacturing (Mechatronics, Robotics & Industrial Automation)

The fourth industrial revolution has redrawn the boundaries of what mechanical, electrical, and software engineers are expected to know. A factory floor in the mid-twentieth century relied on hydraulics, relays, and human judgement; a factory floor today relies on networked sensors, embedded intelligence, digital twins, and machine learning models that anticipate failure before it happens. Mechatronics, the discipline born from the marriage of mechanics and electronics, has always been the natural home for this convergence — and Industry 4.0, in turn, has given mechatronics a new vocabulary, a new toolkit, and a new sense of urgency.
This book, AI and Industry 4.0 in Mechatronics: Intelligent Systems, Cyber-Physical Architectures, and the Future of Smart Manufacturing, was written to give students, practising engineers, and researchers a single, coherent account of how artificial intelligence and the broader Industry 4.0 movement are reshaping mechatronic design, control, and operation. It is organised to be read cover to cover as a semester-length course, or consulted chapter by chapter as a reference by professionals who need a rigorous but accessible treatment of a specific topic — from smart sensors and industrial IoT architectures to reinforcement-learning-based control, digital twins, predictive maintenance, additive manufacturing, and industrial cybersecurity.
Three convictions shaped the writing of this book. First, that AI in mechatronics cannot be taught in the abstract; every algorithm and architecture is presented alongside the physical systems — actuators, sensors, robots, production lines — that it ultimately serves. Second, that engineers need both breadth and depth: breadth to see how sensing, communication, computation, and control fit together as a system, and depth to understand the mathematics and engineering trade-offs within each layer. Third, that diagrams and worked comparisons communicate what paragraphs alone cannot; every chapter therefore includes original figures, tables, key-term boxes, and review questions designed to consolidate learning.
No book of this scope can claim to be exhaustive — the field is evolving too quickly for that, with new standards, tools, and algorithms appearing every year. What this book aims to offer instead is a durable conceptual foundation: the principles of cyber-physical systems, the architecture of intelligent control, and the engineering discipline required to move from a laboratory prototype to a dependable, secure, and maintainable industrial system. Readers who master these foundations will be well equipped to evaluate whatever new tool or platform the market offers next.
I am grateful to the wider community of mechatronics and manufacturing researchers whose published work informed the discussion throughout this text, and to the students and colleagues whose questions, over the years, shaped the way these ideas are explained here. I hope this book serves as both a rigorous textbook and a practical companion for anyone building the intelligent machines of the next industrial era.