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 digital twins, industrial decision-making, intelligent control systems, cobots, 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. The 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. The textbook discusses contemporary technologies and trends, such as digital control, automation, and Machine/Deep learning, and provides a global perspective towards 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, and operations concepts, and beyond.
A Solutions Manual, PowerPoint slides, and figure slides are available for qualified textbook adoption.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Postgraduate and Undergraduate Core
Illustrationen
45 s/w Abbildungen, 32 s/w Zeichnungen, 17 s/w Tabellen, 13 s/w Photographien bzw. Rasterbilder
17 Tables, black and white; 32 Line drawings, black and white; 13 Halftones, black and white; 45 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
Gewicht
ISBN-13
978-1-032-77792-4 (9781032777924)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Uzair Khaleeq uz Zaman is a highly accomplished academic and globally engaged educator, holding a PhD in Industrial Engineering from Arts et Metiers ParisTech, France, with over ten years of experience in university teaching, curriculum development, and applied research. Currently serving as Associate Professor and Head of the Mechanical Engineering Department at National University of Sciences and Technology, Pakistan, he is recognized for his expertise in Smart Manufacturing, Industry 4.0, and Digital Transformation. Dr. Uzair's international teaching footprint spans France, China, and Luxembourg, where he has delivered lectures and workshops at leading institutions. As a published author, keynote speaker, and subject matter expert, his work focuses on industrial automation, additive manufacturing, and smart manufacturing systems. Moreover, with a strong commitment to bridging academia and industry, he has successfully led industry-funded research projects and consultancy assignments in areas such as manufacturing optimization, warehouse automation using AGVs, and process planning. Beyond his technical expertise, Dr. Uzair is a strong advocate for global academic collaboration and student-centered, outcome-based learning, ensuring that his teaching and research contribute meaningfully to both academic excellence and real-world industrial innovation.
Dr. Atal Anil Kumar is currently working as a Professor at the Laboratory of Design, Fabrication, and Control (LCFC), Universite de Lorraine, France, as the chair of Robotics for Sustainable and Agile Industry. 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 a research internship grant by the Indian Institute of Technology, Bombay (IIT-B), for performing research during his bachelor's degree. Before joining as a Professor, Dr. Atal worked as a Research Scientist in the Department of Engineering at the University of Luxembourg. Dr. Atal has also worked as an R&D Engineer in the automotive and steel manufacturing industries to gain significant hands-on experience to apply his theoretical knowledge. His research interests include Nonlinear control, Collaborative robots, Robot Kinematics and Dynamics, and Human-Robot Interaction.
Dr. Aamer Ahmed Baqai is a Professor at the College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Pakistan. He earned his Ph.D. and master's in mechanical engineering from the Arts et Metiers Institute of Technology, France. Dr. Baqai has over 30 years of professional experience spanning both academia and industry in France. He is a researcher of international repute and is a regular research Visiting Professor at ParisTech, France. He has also acted as a foreign evaluator for Ph.D. thesis students at 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. Dr Baqai has numerous industrial projects to his credit as a team lead, dealing with workflow design and optimization.
Autor*in
Post-Doc Researcher, Dept. of Engr., Fac. of Sci., Technology and Med., Univ. of Luxembourg
Part I: 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 II: Intelligent Manufacturing: Transcending the Notions. 6. Role of Decision Intelligence and Machine Learning in Intelligent Manufacturing. 7. Immersive Technologies in Intelligent Manufacturing. 8. Product Lifecycle Management, Big Data and Cloud Manufacturing. 9. Converging Technologies for Smart, Circular, and Energy-Efficient Manufacturing.