Intelligent Manufacturing

This textbook introduces intelligent manufacturing concepts and strategies toward systems' best performance, especially concerning design and operations. It simplifies theory concepts through examples of real-life systems worldwide and presents many modern concepts such as sensor-based intelligent control systems, industrial decision-making, CAD/CAP/CAM integration in intelligent manufacturing, production control, augmented reality/mixed reality, cloud manufacturing, and manufacturing execution systems. Intelligence Manufacturing: Concepts and Beyond covers the fundamental principles of intelligent manufacturing and provides a comprehensive resource for readers at different levels of expertise. This textbook is written in an infographic language, making complex concepts accessible to a broader audience. It includes many examples and numerical and practical exercises that reinforce learning and demonstrate how intelligent manufacturing systems work. It discusses contemporary technologies and trends, such as digital control and automation and machine/deep learning, and it provides a global perspective toward new emerging trends as it spans various technologies across different disciplines. Written for both undergraduate and graduate courses, this textbook will take the reader from basic concepts and applications to advanced topics and can be the sole source to reach knowledge and explore future possibilities related to intelligent manufacturing techniques, methodologies, operations concepts, and beyond. A solutions manual, PowerPoint slides, and figure slides are available for qualified textbook adoption.

Uzair Khaleeq uz Zaman, PhD, is an Associate Professor and Head of the Department of Mechanical Engineering at the National University of Sciences and Technology, Pakistan. He earned a PhD in industrial engineering at Arts et Métiers Institute of Technology, France, and has over 15 years of combined academic and industry experience. His core expertise includes smart manufacturing, industrial systems design, additive manufacturing, and AI-driven decision-making. Dr. Zaman has taught and conducted research at institutions including Georgia Tech-Lorraine (France), University of Alberta (Canada), Arts et Métiers ParisTech (France), Beihang University (China), ENSET Mohammedia (Morocco), and the University of Lorraine (France). He also focuses on integrating emerging technologies into engineering education, promoting sustainable practices, and leading curriculum reform. Passionate about outcome-based learning and industry collaboration, he mentors students and faculty to bridge research with real-world applications aligned with Industry 4.0. Atal Anil Kumar, PhD, is a Professor at the University of Lorraine, Metz, France, where he is the Chair of Robotics for Sustainable and Agile Industry. He also did his post-doctoral research at the University of Luxembourg in the field of robotics. His research interests include nonlinear control, collaborative robots, robot kinematics and dynamics, and human-robot interaction. He has a bachelor's degree in mechatronics and an Erasmus master's in advanced robotics (with scholarship) from France and Italy. He has been awarded the research internship grant by the Indian Institute of Technology, Bombay (IIT-B) for performing research during his bachelor's degree. Dr. Atal has also worked as an R&D engineer in the automotive and steel manufacturing industries to gain significant hands-on experience and apply his theoretical knowledge. Aamer Ahmed Baqai, PhD, is a Professor at the National University of Sciences and Technology, Pakistan. He earned a master's and a PhD in mechanical engineering at Arts et Métiers ParisTech, France. He has more than 26 years of experience in academia and industry. Dr. Baqai is a researcher of international repute and is a regular Research Visiting Professor at Arts et Métiers ParisTech, France. He has also acted as a foreign evaluator for PhD thesis students at Arts et Métiers ParisTech. His research interests include advanced manufacturing, manufacturing system design and optimization, reconfigurable manufacturing systems, process modeling and optimization, additive manufacturing, and decision-making in manufacturing.

Part 1: Concepts in Intelligent Manufacturing. 1. Manufacturing Concepts and Intelligent Manufacturing. 2. Computer-Aided Design (CAD), Computer-Aided Process Planning (CAPP), Computer-Aided Manufacturing (CAM), and Intelligent Manufacturing. 3. Intelligent Control in Manufacturing Systems. 4. Production Planning and Control. 5. Sensors. Part 2: Intelligent Manufacturing: Transcending the Notions. 6. Role of Decision Intelligence and Machine Learning in Intelligent Manufacturing. 7. Immersive Technologies in Intelligent Manufacturing. 8. Product Life Cycle Management, Big Data and Cloud Manufacturing. 9. Converging Technologies for Smart, Circular, and Energy-Efficient Manufacturing.