Yu | Smart Logistics in Industry 5.0 | Buch | 978-1-032-71798-2 | sack.de

Buch, Englisch, 226 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

Yu

Smart Logistics in Industry 5.0


1. Auflage 2025
ISBN: 978-1-032-71798-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 226 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

ISBN: 978-1-032-71798-2
Verlag: Taylor & Francis Ltd


Given the importance of human centricity, resilience, and sustainability, the emerging concept of Industry 5.0 has pushed forward the research frontier of the technology-focused Industry 4.0 to a smart and harmonious socio-economic transition driven by both humans and technologies, where the role of the human in the technological transformation is predominantly focused on. Compared with Industry 4.0, smart logistics in Industry 5.0 puts more focus on the interaction between humans and technology in the digital transition with the increasing adoption of collaborative technologies, e.g., human-machine systems, collaborative robots, and human-robot collaboration.

In this book, a comprehensive overview on how technological enablers will help the smart and sustainable transition of logistics planning and operations is provided. Specifically, the book focuses on the conceptual development and framework of smart logistics transformation in Industry 5.0, smart and sustainable logistics planning and operations, smart manufacturing logistics and warehousing, data-driven smart logistics and transportation, digital twin of logistics systems, and smart reverse logistics transformation. Most importantly, the role of humans in the smart logistics transformation is predominantly focused on in this book.

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Zielgruppe


Academic and Postgraduate


Autoren/Hrsg.


Weitere Infos & Material


Preface. Distribution and Logistics Network Design in Industry 5.0: Models, Methods, and the Impact of Generative AI and Large Language Models. Distribution and Logistics Network Design Using Digital Twin: Concepts, Methods, and Applications. Artificial Intelligence and Data-driven Smart Transportation and Logistics: Unsupervised Learning Models and Ensemble Learning Models. Artificial Neural Network Methods in Smart Logistics: Concept, Methods, and Applications. Embedding Social Value in Sustainable Transport and Smart Logistics Systems. Extended Reality in Warehousing: Bridging Industry 4.0 and 5.0 for Smart Logistics. Circular Economy Principles and Sustainable Logistics Practices in Industry 5.0. Reverse Logistics in Industry 5.0: Opportunities and Challenges: A Systematic Literature Review and Research Agenda.


Hao Yu received his Ph.D. degree in Applied Mathematics and Computational Engineering from UiT—The Arctic University of Norway in 2018. At the moment, he is a tenured Associate Professor and the Director of Master Program of Industrial Engineering at UiT—The Arctic University of Norway. His research focuses on applied operations research and real-problem-driven model development to solve complex problems in sustainable supply chain, reverse logistics, location and network design, service systems, scheduling, and smart manufacturing and logistics in Industry 4.0/5.0. He is the Associate Editor of IEEE Transactions on Intelligent Transportation Systems and World Journal of Engineering, and editorial member of several other journals. He also manages or being a key member of several national and international projects, and his current research focuses on the combination of predictive analytics, prescriptive analytics, and descriptive analytics in an Industry 5.0 enabled Smart Digital Logistics Twin that can be used in, for example, reverse logistics, humanitarian/epidemic logistics, and reconfigurable remanufacturing systems.



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