Proceedings of the 2nd International Conference on Sustainability and Emerging Technologies for Smart Manufacturing

SETSM 2025, 22-23 April, Hanoi, Vietnam

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Springer


Paru le : 2025-10-25



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Description

This book presents peer reviewed articles from the 2nd International Conference on Sustainability and Emerging Technologies for Smart Manufacturing (SETSM 2025) held on 22-23 April at Hanoi in Vietnam. It presents latest research and innovation in Sustainability and emerging technologies for Smart Manufacturing, especially innovative solutions for development of sustainable and smart eco-systems in industries, healthcare and medicine.
The book provides researchers, professionals, and decision-makers a platform to present their results on the following topics:
Smart Manufacturing, Lean Manufacturing 4.0, Rapid Manufacturing and Cloud Manufacturing
Sustainable Design and Manufacturing
Advanced Materials Engineering
Advanced Computational Modeling, Simulation and Optimization
Additive Manufacturing, and Advanced machining processes
Renewable energy and clean technologies, electric and hybrid technologies
Autonomous vehicles, connected vehicles, and Intelligent Transportation Systems
Mechatronics, robotics and digital twin
Biomedical Engineering: Emerging technologies for medical diagnosis, treatments and rehabilitations, personalization and mass-personalization, Telehealth and in-home Healthcare.
ICT—Information and Communications Technologies and applications for Smart Manufacturing and Industry 4.0.
Pages
746 pages
Collection
n.c
Parution
2025-10-25
Marque
Springer
EAN papier
9789819517497
EAN PDF
9789819517503

Informations sur l'ebook
Nombre pages copiables
7
Nombre pages imprimables
74
Taille du fichier
158095 Ko
Prix
294,34 €
EAN EPUB
9789819517503

Informations sur l'ebook
Nombre pages copiables
7
Nombre pages imprimables
74
Taille du fichier
162683 Ko
Prix
294,34 €

Dr. Dzung Hoang Tien is the dean of the School of Mechanical and Automotive Engineering at Hanoi University of Industry, Vietnam (HaUI). He has more than 20 years of academic experience in Mechanical Engineering. His research interests include Dynamic Machining, Modeling and Optimization, polishing, CAD/CAM/CAE/CNC, AM/3D Printing Technology, Mold Manufacturing, Optimization, and Intelligent Manufacturing System. He received his Ph.D. degree from the Hanoi University of Science and Technology in 2016 in Vietnam.

Dr. Vijender Kumar Solanki is  an associate professor in the Department of Computer Science & Engineering at Stanley College of Engineering and Technology for Women, Hyderabad,  India. He has more than 18 years of academic experience in network security, IoT, Big Data, Smart City, and IT. Before his current role, he was associated with the CMR Institute of Technology, Hyderabad; Apeejay Institute of Technology, Greater Noida, UP; KSRCE (Autonomous) Institution, Tamil Nadu, India; and the Institute of Technology & Science, Ghaziabad, UP, India. He is a Senior Member of IEEE.

Dr. J. Paulo Davim is a professor at the University of Aveiro, Portugal. He received his Ph.D. in Mechanical Engineering, M.Sc. in Mechanical Engineering from the University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra and the D.Sc. (Higher Doctorate) from London Metropolitan University. His research interests are in the areas of Manufacturing, Materials, Mechanical, and Industrial Engineering, with special emphasis in Machining, Tribology & Surface Engineering. He has also interest in Design, Management, Sustainability, Industry 5.0, Engineering Education and Higher Education for Sustainability.

Dr. Nguyen Thi Dieu Linh is the deputy head of Science and Technology Department, Hanoi University of Industry, Vietnam (HaUI). She has more than 20 years of academic experience in electronics, IoT, Smart Garden, and Telecommunication. She obtained her Ph.D. in Information and Communications Engineering from Harbin Institute of Technology, Harbin, China. Her research interests are in the areas of Artificial Intelligence, Data Analytics, Machine Learning, Deep Learning, and Artificial Intelligence.

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