Digital Twin-Driven Manufacturing System
Description
This book provides a comprehensive and systematic framework for digital twin-driven manufacturing systems in the era of Industry 5.0. As the demand for human-centric, resilient, and sustainable manufacturing continues to grow, Digital Twin technology is emerging as a key enabler of end-to-end digitalization across the entire product manufacturing lifecycle. Yet, despite its potential, industrial adoption still faces significant challenges, including fragmented data, limited interoperability, insufficient real-time optimization, and concerns surrounding data security.
To address these gaps, the book clarifies core concepts and defining characteristics of digital twin-driven systems, introduces essential enabling technologies, and presents practical methodologies for system design and implementation. It also explores advanced and emerging topics such as cross-X manufacturing and biotwins, while discussing future opportunities shaped by the Industry 5.0 paradigm. By integrating recent research outcomes with real-world case studies, the book serves as both a rigorous academic reference and a practical guide for researchers, engineers, and industry professionals.
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Persons
Dr. Liu Shimin is presently serving as a Postdoctoral Fellow at the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. His research portfolio is diverse, encompassing areas such as digital twin-driven machining processes, bionic digital manufacturing, and intelligent manufacturing. Since 2019, Dr. Liu has dedicated himself to the exploration of theories, technologies, and applications related to digital twins in the processing field, thereby amassing substantial theoretical knowledge and practical experience. Throughout his academic career, Dr. Liu has been an active participant in several significant projects. These include the Ministry of Industry and Information Technology's Intelligent Manufacturing Project, initiatives sponsored by the Shanghai Municipal Science and Technology Commission.
Prof. Bao Jinsong is the Director of the Institute of Intelligent Manufacturing at Donghua University and a PhD supervisor. He has led several research initiatives, including two National Natural Science Foundation of China projects, one sub-project under the Ministry of Science and Technology's support plan, two special manufacturing projects by the Shanghai Municipal Science and Technology Commission, one aerospace-specific project, one Shanghai Aerospace Fund project, two integration projects of informatization and industrialization supported by the Shanghai Economic and Information Commission, and one key laboratory fund project from Shanghai Jiao Tong University. Additionally, Prof. Bao has been responsible for over 20 corporate scientific research projects. He participated in the China Lunar Rover project, focusing on the development of a mobile subsystem simulation platform, with many results applied in aerospace and shipbuilding enterprises. As the principal investigator, he has also managed one project under the National Natural Science Foundation, one major project from the National Development and Reform Commission, and the Ministry of Industry and Information Technology's 2015 intelligent manufacturing standardization project.
Dr. Zheng Pai is currently a tenured Associate Professor at the Hong Kong Polytechnic University, where he will officially start on July 1, 2024. He also serves as a PhD supervisor and holds the title of Huang Tiecheng Young Scholar in Intelligent Robotics. Dr. Zheng earned his doctoral degree in a field closely related to intelligent manufacturing and robotics. As the Director of the "Hong Kong Polytechnic University-Rheinkost" Intelligent Manufacturing Joint Laboratory and the leader of the Research in AI and Digital Service for Industrial Systems (RAIDS) team, he is deeply involved in pioneering research. His main research interests include industrial artificial intelligence, human-robot collaborative manufacturing systems, and intelligent product-service systems.
Content
Introduction to Digital Twins and Smart Manufacturing.- Evolution of Manufacturing Paradigms.- Fundamentals of Digital Twin Technology.- Digital Twins for Product Lifecycle Management.- Enabling Mass Customization through Digital Twins.- Simulation, Testing, and Optimization.- Implementation Challenges and Strategies.- Ethical Considerations and Data Security.- Future Trends and Innovations in Digital Twin Technologies.- Conclusion.