Design and Operation of Smart Reconfigurable Manufacturing Systems in Industry 4.0/5.0

Author:   Sihan Huang ,  Xingyu Li ,  Xi Gu ,  Yoram Koren
Publisher:   Springer
ISBN:  

9783032002839


Pages:   210
Publication Date:   03 October 2025
Format:   Hardback
Availability:   Not yet available   Availability explained
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Design and Operation of Smart Reconfigurable Manufacturing Systems in Industry 4.0/5.0


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Overview

This book presents the evolution roadmap of Reconfigurable Manufacturing Systems (RMS) and their characteristics since its invention in the 1990s. It discusses the role of RMS in today’s increasingly competitive manufacturing environment and unpredictable markets and the new challenges and opportunities in RMS design and operations in the emerging Industry 4.0/5.0 era. In addition, this book investigates the relationship between reconfigurable manufacturing and smart manufacturing and demonstrates how smart manufacturing techniques can facilitate the design and operations of RMSs. With state-of-the-art research on the development of novel methodologies based on smart manufacturing to guide the design and operations of reconfigurable machines and manufacturing systems, this book is a valuable handbook for reconfigurable manufacturing/smart manufacturing researchers and practitioners. Engineering professionals will find the practical values and managerial insights of smart RMS implementations through case studies.

Full Product Details

Author:   Sihan Huang ,  Xingyu Li ,  Xi Gu ,  Yoram Koren
Publisher:   Springer
Imprint:   Springer
ISBN:  

9783032002839


ISBN 10:   3032002834
Pages:   210
Publication Date:   03 October 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Chapter 1. The Evolution Roadmap of Reconfigurable Manufacturing Systems.- Chapter 2. Part Family Formation Method for Delayed Reconfigurable Manufacturing System based on Machine Learning.- Chapter 3. A Multi-Objective Joint Optimisation Method for Simultaneous Part Family Formation and Configuration Design in Delayed Reconfigurable Manufacturing System (D-RMS).- Chapter 4. Configuration Design for Smart Reconfigurable Manufacturing Systems.- Chapter 5. Self-adaptive Reconfiguration Decision-making Method of Smart Manufacturing Systems Based on Game Theory.- Chapter 6. Reinforcement Learning-based Dynamic Reconfiguration Planning for Digital Twin-Driven Smart Manufacturing Systems with Reconfigurable Machine Tools.- Chapter 7. Integrated Operational and Preventative Decision-Making in a Smart Reconfigurable Manufacturing Systems.- Chapter 8. Dynamic Reconfiguration Optimization of Smart Manufacturing System with Human-Robot Collaboration based on Digital Twin.- Chapter 9. Cultivating Knowledge in Human-Machine Teams for Efficient Equipment Diagnosis by leveraging Smart Reconfigurable Manufacturing Systems.- Chapter 10. Achieving Manufacturing Resilience Through Reconfigurable Manufacturing Systems and Supply Chains.- Chapter 11. Coordination of Manufacturing and Supply Chain Network in Emergency Situations via Smart Reconfigurable Manufacturing Systems.- Chapter 12. Realization of Responsive and Sustainable Reconfigurable Manufacturing Systems.- Chapter 13. Configuration Design in Scalable Reconfigurable Manufacturing Systems by Analyzing the Effect of Data Accuracy on System Reconfiguration Costs.- Chapter 14. Towards a sustainable reconfigurable manufacturing system (SRMS): multi-objective based approaches for process plan generation problem.- Chapter 15. Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model.- Chapter 16. Digital twin framework for reconfigurable manufacturing systems (RMSs): design and simulation.- Chapter 17. Robust Configuration Design of Sustainable Reconfigurable Manufacturing System Under Uncertainty.- Chapter 18. Production scheduling in a reconfigurable manufacturing system benefiting from human-robot collaboration.

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Author Information

Sihan Huang received B.Eng. degree in Industrial Engineering from Beijing Institute of Technology, China, in 2014 and Ph.D. degree in Mechanical Engineering from Beijing Institute of Technology, China, in 2020. He visited the University of Michigan-Ann Arbor, USA from 2017 to 2019. He is currently an associate professor of the School of Mechanical Engineering at Beijing Institute of Technology, China. His current research interests include reconfigurable manufacturing systems, human-centric smart manufacturing, digital twin and robotic-driven smart manufacturing. He has published more than 40 papers (One ESI highly-cited paper) and is the inventor of 16 China patents. He also served as associate editor of Journal of Intelligent Manufacturing (Editorial Contribution Award 2025), associate editor and special corresponding expert of Frontiers of Engineering Management, youth editorial board member of Journal of Mechanical Engineering, Industrial Engineering Journal, Journal of Xi’An Jiaotong University, and Journal of Advanced Manufacturing Science and Technology. Xingyu Li is an Assistant Professor in the School of Engineering Technology at Purdue University, West Lafayette. Before joining Purdue, he was an Adjunct Assistant Research Scientist at the Department of Mechanical Engineering at the University of Michigan - Ann Arbor. Dr. Li received his Ph.D. degree in Mechanical Engineering from the University of Michigan – Ann Arbor in 2018. Dr. Li is currently a CIRP Research Affiliate, an ASTAR Visiting Fellow, an AnalytiXIN Fellow, and a corresponding expert in Engineering, he is also a recipient of the Best Student Research Award Winner in NAMRC 2025, Journal of Manufacturing Systems Outstanding Reviewer in 2024, the Best Reviewer of OMEGA in 2023, Best Paper Award at the 2019 IEEE Ai4i, Ford COVID-19 Innovation Challenge Award and Presidents Health and Safety Award. Xi Gu obtained a B.S. degree in mechanical engineering from Zhejiang University, Hangzhou, Zhejiang, China, an M.S. in industrial and operations engineering and a Ph.D. degree in mechanical engineering, both from the University of Michigan, Ann Arbor, MI, USA. He is currently an Associate Teaching Professor in the Department of Mechanical and Aerospace Engineering at Rutgers, The State University of New Jersey. He is a recipient of the Outstanding Young Manufacturing Engineer Award from SME and is a member of the NAMRI scientific committee. His research interests include smart manufacturing, reconfigurable manufacturing systems, maintenance decision-making in manufacturing systems, and engineering education. Yoram Koren is the James J. Duderstadt Distinguished University Professor Emeritus of Manufacturing and the Paul G. Goebel Professor Emeritus of Engineering at the University of Michigan, Ann Arbor, and a Distinguished Visiting Professor at the Technion, Israel Institute of Technology. He is internationally recognized as the father of Reconfigurable Manufacturing Systems. He is a member of the U.S. National Academy of Engineering and an honorable member of SME. He is a Fellow of CIRP, SME, ASME, and IEEE. Dr. Koren has authored 350 papers and 4 original books, that have 39,000 citations per Google Scholar. His 1985 pioneering textbook Robotics for Engineers was translated by the publisher (McGraw Hill) to French and Japanese.  Two of his other textbooks were translated to Chinese. He is the inventor of 18 U.S. patents, including the patents on Reconfigurable Manufacturing System, Reconfigurable Machine Tool, and Reconfigurable Inspection Machine. From 1996 to 2010, he was the Director of the NSF-sponsored Engineering Research Center for Reconfigurable Manufacturing Systems at the University of Michigan that was sponsored by the NSF ($32.5 million), U.S. industry ($10 million), and State and Federal agencies ($4 million). The ERC-RMS implemented RMS technologies in numerous powertrain factories of GM, Ford, Chrysler, and Cummins.

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