Manufacturing Process Optimization for Sustainable Development Using Digital Twin Applications explores the potential of digital twin applications in the manufacturing sector, with a primary focus on achieving sustainable development.
The edited volume provides a comprehensive overview of the interdisciplinary nature of digital twin applications, considering how collaboration between engineering, data science, environmental science, and other fields can lead to holistic and impactful solutions. The content addresses the challenges and potential hurdles in implementing digital twin solutions in manufacturing while also proposing future directions for research and development in this rapidly evolving field, further reviewing how digital twin technologies can be effectively applied to enhance efficiency, reduce waste, and improve overall productivity in manufacturing processes. The role of digital twins in contributing to sustainable development goals is also analyzed, including considerations such as resource conservation, energy efficiency, and the reduction of environmental impact throughout the manufacturing lifecycle. Case studies and real-world examples are included to illustrate successful implementations.
The publication caters to a diverse audience of professionals, researchers, and academics from engineering disciplines, including mechanical engineers, industrial engineers, electrical and electronic engineers, data scientists and AI engineers, and manufacturing and operations managers. The comprehensive approach makes it an essential resource for anyone seeking to understand the intersection of digital twin technology and sustainable manufacturing practices.
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Santosh Kumar Tamang is an assistant professor in the Department of Mechanical Engineering at the North Eastern Regional Institute of Science and Technology (NERIST), Arunachal Pradesh, India. He holds a Ph.D. in mechanical engineering from NERIST and has authored more than 90 research papers in reputed SCI and Scopus-indexed journals and conferences. His research focuses on integrating artificial intelligence with manufacturing process optimization, additive manufacturing and sustainable materials development for Industry 4.0 applications.
Vishnu Vijay Kumar is a research staff at New York University, Abu Dhabi, and a visiting researcher at KMUTNB, Thailand, and UGM, Indonesia. He completed a joint doctorate from the Indian Institute of Technology Madras and the National University of Singapore, with research interests encompassing artificial intelligence, additive manufacturing, sustainability, and composites. His research has been published in reputable journals with over 700 citations, and he has conducted projects at prestigious institutions, including ISRO and Bharat Petroleum Corporation Limited.
J. Paulo Davim is a professor at the University of Aveiro, Portugal, and holds honorary professorships at several universities in China, India, and Spain. He received his Ph.D., M.Sc., and BE (Mechanical Engineering degree) from the University of Porto, with additional qualifications, including an aggregate title from the University of Coimbra and D.Sc. from London Metropolitan University. With over 35 years of experience in manufacturing and materials engineering, he serves as the editor-in-chief of several international journals and is an editorial board member of 30 international journals and acts as a reviewer for more than 200. He was listed in World´s Top 2% Scientists by Stanford University study 2025 (Ranked at 1 National Ranking/3238 World Ranking career). Also, he was listed in Research.com ranking 2025 (Ranked at 1 National Ranking/82 World Ranking in field of Mechanical and Aerospace Engineering). 2025―Research.
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Hardcover. Condición: new. Hardcover. Manufacturing Process Optimization for Sustainable Development Using Digital Twin Applications explores the potential of digital twin applications in the manufacturing sector, with a primary focus on achieving sustainable development.The edited volume provides a comprehensive overview of the interdisciplinary nature of digital twin applications, considering how collaboration between engineering, data science, environmental science, and other fields can lead to holistic and impactful solutions. The content addresses the challenges and potential hurdles in implementing digital twin solutions in manufacturing while also proposing future directions for research and development in this rapidly evolving field, further reviewing how digital twin technologies can be effectively applied to enhance efficiency, reduce waste, and improve overall productivity in manufacturing processes. The role of digital twins in contributing to sustainable development goals is also analyzed, including considerations such as resource conservation, energy efficiency, and the reduction of environmental impact throughout the manufacturing lifecycle. Case studies and real-world examples are included to illustrate successful implementations.The publication caters to a diverse audience of professionals, researchers, and academics from engineering disciplines, including mechanical engineers, industrial engineers, electrical and electronic engineers, data scientists and AI engineers, and manufacturing and operations managers. The comprehensive approach makes it an essential resource for anyone seeking to understand the intersection of digital twin technology and sustainable manufacturing practices. Manufacturing Process Optimization for Sustainable Development Using Digital Twin Applications explores the potential of digital twin applications in the manufacturing sector, with a primary focus on achieving sustainable development. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781032822297
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Hardcover. Condición: new. Hardcover. Manufacturing Process Optimization for Sustainable Development Using Digital Twin Applications explores the potential of digital twin applications in the manufacturing sector, with a primary focus on achieving sustainable development.The edited volume provides a comprehensive overview of the interdisciplinary nature of digital twin applications, considering how collaboration between engineering, data science, environmental science, and other fields can lead to holistic and impactful solutions. The content addresses the challenges and potential hurdles in implementing digital twin solutions in manufacturing while also proposing future directions for research and development in this rapidly evolving field, further reviewing how digital twin technologies can be effectively applied to enhance efficiency, reduce waste, and improve overall productivity in manufacturing processes. The role of digital twins in contributing to sustainable development goals is also analyzed, including considerations such as resource conservation, energy efficiency, and the reduction of environmental impact throughout the manufacturing lifecycle. Case studies and real-world examples are included to illustrate successful implementations.The publication caters to a diverse audience of professionals, researchers, and academics from engineering disciplines, including mechanical engineers, industrial engineers, electrical and electronic engineers, data scientists and AI engineers, and manufacturing and operations managers. The comprehensive approach makes it an essential resource for anyone seeking to understand the intersection of digital twin technology and sustainable manufacturing practices. Manufacturing Process Optimization for Sustainable Development Using Digital Twin Applications explores the potential of digital twin applications in the manufacturing sector, with a primary focus on achieving sustainable development. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781032822297
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