This book is a comprehensive guide to the latest advancements in manufacturing, adopting an Industry 4.0 approach. It covers the core principles of big data informatics, digital twin technology, artificial intelligence, and machine learning strategies. Readers will gain insights into the realm of cyber-physical intelligent systems in production, the role of blockchain, and the significance of information and communication technology. With a focus on real-time monitoring and data acquisition, the book offers practical solutions for online error troubleshooting in manufacturing systems. It explores a wide range of Industry 4.0-based applied manufacturing technologies and addresses the challenges posed by the dynamic market of production. Recognizing the lack of a cohesive resource on manufacturing advancements within the context of Industry 4.0, the authors have taken the initiative to compile this valuable knowledge from domain experts. Their goal is to disseminate these insights with this book. The book will be beneficial to various stakeholders, including industries, professionals, academics, research scholars, senior graduate students, and those in the field of human healthcare. With its comprehensive coverage, the book is an important reference for technical institution libraries and a useful reader for senior graduate students. 
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This book is a comprehensive guide to the latest advancements in manufacturing, adopting an Industry 4.0 approach.
Industry 4.0 in Manufacturing technologies: Pathways and Practices.- Chapter 2. Manufacturing 4.0 evaluation and revolution: A conceptual Framework.- Modeling the barriers in adoption of Industry 4.0 in manufacturing.- Bibliometric analysis of manufacturing techniques in context of Industry 4.0.-  Digital twin Model for advanced manufacturing systems.- Manufacturing techniques triggered by Industrial Artificial Intelligence.
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This book is a comprehensive guide to the latest advancements in manufacturing, adopting an Industry 4.0 approach. It covers the core principles of big data informatics, digital twin technology, artificial intelligence, and machine learning strategies. Readers will gain insights into the realm of cyber-physical intelligent systems in production, the role of blockchain, and the significance of information and communication technology. With a focus on real-time monitoring and data acquisition, the book offers practical solutions for online error troubleshooting in manufacturing systems. It explores a wide range of Industry 4.0-based applied manufacturing technologies and addresses the challenges posed by the dynamic market of production. Recognizing the lack of a cohesive resource on manufacturing advancements within the context of Industry 4.0, the authors have taken the initiative to compile this valuable knowledge from domain experts. Their goal is to disseminate these insights with this book. The book will be beneficial to various stakeholders, including industries, professionals, academics, research scholars, senior graduate students, and those in the field of human healthcare. With its comprehensive coverage, the book is an important reference for technical institution libraries and a useful reader for senior graduate students. 
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Provides case studies showing solutions from industry and society Integrates Industry 4.0 tools, e.g., digital twins, artificial intelligence, nature-inspired algorithms, and the IoT Bridges the gap between R&D in human-machine interaction for manufacturing and practical application
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Produktdetaljer

ISBN
9783031682704
Publisert
2024-09-14
Utgiver
Vendor
Springer International Publishing AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Innbundet

Om bidragsyterne

Prof. Ajay Kumar is currently serving as a Professor in Department of Mechanical Engineering, School of Engineering and Technology, JECRC University, Jaipur, Rajasthan, India. He received his Ph.D. in the field of Advanced Manufacturing from Guru Jambheshwar University of Science & Technology, Hisar, India after B.Tech. (Hons.) in mechanical engineering and M.Tech. (Distinction) in manufacturing and automation. His areas of research include Incremental Sheet Forming, Artificial Intelligence, Sustainable Materials, Additive Manufacturing, Mechatronics, Smart Manufacturing, Industry 4.0, Waste Management, and Optimization Techniques. He has over 140 publications in international journals of repute including SCOPUS, Web of Science and SCI indexed database and refereed international conferences. He has also co-authored and co-edited more than 20 books and proceedings with ELSEVIER, Springer, CRC Press, WILEY, De Gruyter, IOP, AIP and IGI Global. He has organized various national and international events including an International conference on Mechatronics and Artificial Intelligence (ICMAI-2021), International conference on Artificial Intelligence, Advanced Materials, and Mechatronics Systems (AIAMMS-2023) as conference chair. He has more than 20 national and international patents to his credit. He has supervised more than 8 M.Tech, Ph.D scholars and numerous undergraduate projects/ thesis. He has a total of 15 years of experience in teaching and research. He is Guest Editors and Review Editor of the reputed journals including Frontiers in Sustainability. He has contributed to many international conferences/ symposiums as a session chair, expert speaker, and member of the editorial board. He has won several proficiency awards during the course of his career, including merit awards, best teacher awards, and so on. He is adviser of QCFI, Delhi Chapter student cell at JECRC University and has also authored many in-house course notes, lab manuals, monographs and invited chapters in books. He has organized a series of Faculty Development Programs, International Conferences, workshops, and seminars for researchers, PhD, UG and PG level students. He is associated with many research, academic, and professional societies in various capacities. ORCID ID: https://orcid.org/0000-0001-7306-1902  
 

Parveen Kumar is currently serving as an Assistant Professor and Head in Department of Mechanical Engineering at Rawal Institute of Engineering and Technology, Faridabad, Haryana, India. He has submitted  Ph.D. from National Institute of Technology, Kurukshetra, Haryana, India. He completed his B.Tech. (Hons.) from Kurukshetra University, Kurukshetra, India and M.Tech. (Distinction) in Manufacturing and Automation from Maharshi Dayanand University, Rohtak, India. His areas of research include Intelligent Manufacturing Systems, Materials; Die less Forming, Design of Automotive systems, Additive Manufacturing, CAD/CAM and Artificial Intelligence, machine learning and Internet of Things in manufacturing, multi objective optimization techniques. He has over 50 publications in international journals of repute including SCOPUS, Web of Science and SCI indexed database and refereed international conferences. He has 8 national and international patents in his credit. He has supervised 2 M.Tech. scholars and numerous undergraduate projects/theses. He has a total of 13 years of experience in teaching and research. He has co-authored/co-edited several books with ELSEVIER, CRC Press, WILEY, De Gruyter and IGI Global. He is also book series editor of “Industrial and Manufacturing Systems and Technologies: Sustainable and Intelligent Perspectives” in CRC Press, Taylor and Francis. He has organized a series of Faculty Development Programmes, workshops, and seminar for researcher, UG level students.
ORCID ID: https://orcid.org/0000-0002-2922-6228

Dr. Yang Liu received the M.Sc. (Tech.) degree in telecommunication engineering and D.Sc. (Tech.) degree in industrial management from the University of Vaasa, Finland, in 2005 and 2010, respectively. He is currently a tenured Associate Professor and Doctoral Supervisor with the Department of Management and Engineering, Linköping University, Sweden; a Visiting Faculty with the Department of Production, University of Vaasa, Finland; and a Chair Professor with Jinan University, China. Meanwhile, he is an Adjunct/Visiting Professor at multiple other universities. His research interests include sustainable smart manufacturing, product service innovation, decision support system, competitive advantage, control systems, autonomous robots, signal processing, and pattern recognition.
Prof. Liu has authored or co-authored more than 130 peer-reviewed scientific articles and is ranked No.1 among the top authors on “big data analytics in manufacturing”. His publications have appeared in multiple distinguished journals, and some ranked as top 0.1% ESI Hot Papers and top 1% ESI Highly Cited Papers. He serves as an Associate Editor of the prestigious Journal of Cleaner Production and Journal of Intelligent Manufacturing, referees in over 60 SCI leading journals, and external reviewer for NSERC of Canada and CONICYT of Chile.