Overview

Digital Twin for Smart Manufacturing: Emerging Approaches and Applications provides detailed descriptions on how to integrate and optimize novel digital technologies for smart manufacturing. The book discusses digital twins, which combine the industrial internet of things, artificial intelligence, machine learning and software analytics with spatial network graphs to create living digital simulation models that update and change as their physical counterparts change. In addition, they provide an effective way to integrate technologies like cyber-physical systems into a smart manufacturing system, potentially optimizing the entire business process and operating procedure of the manufacturing firm. Drawing on the latest research, the book addresses the topics and technologies key to successful implementation of a smart manufacturing system, including augmented and virtual reality, big data and energy management. Broader subjects such as additive manufacturing and robotics are also covered in this context, covering every aspect of production.

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9780323992053

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Dr. Dhanaraj holds a PhD in Information and Communication Engineering by Anna University, Chennai, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and of the International Association of Engineers (IAENG). He is an Expert Advisory Panel Member of Texas Instruments Inc. (USA), and an Associate Editor of International Journal of Pervasive Computing and Communications (Emerald Publishing). Ali Kashif Bashir is an Associate Professor at the School of Computing and Mathematics of Manchester Metropolitan University, United Kingdom, an Adjunct Professor at the School of Electrical Engineering and Computer Science at the National University of Science and Technology, Islamabad (NUST), Pakistan, an Honorary Professor at the School of Information and Communication Engineering of the University of Electronics Science and Technology of China (UESTC) and a Chief Advisor at the Visual Intelligence Research Center, UESTC, China. He is a senior member of Institute of Electrical and Electronics Engineers (IEEE), USA and Distinguished Speaker of Association for Computing Machinery (ACM), USA. Vani Rajasekar is an Assistant Professor at the School of Computer Science and Technology at Kongu Engineering College. Her research focuses on network security and cryptography, and she has been published in 8 international journals, and presented at 8 international conferences. Prof. Balamurugan Balusamy is the Associate Dean Student at Shiv Nadar Institution of Eminence, Delhi-NCR. He is also an Adjunct Professor at the Department of Computer Science & Information Engineering at Taylor University, Malaysia. Before this assignment, he was a Professor at the School of Computing Sciences & Engineering and Director of International Relations at Galgotias University, Greater Noida, India. His contributions focus on Engineering Education, Blockchain, and Data Sciences. His academic degrees and twelve years of experience working as a faculty member in a global university like VIT University, Vellore, have made him more receptive and prominent in his domain. He does have 200 plus high-impact factor papers in Springer, Elsevier, and IEEE. He has written and authored over 200 books and edited and collaborated with eminent professors from top-ranked universities worldwide. He has published 80+ books on various technologies and visited 15-plus countries for his technical course. He has several top-notch conferences in his resume and has published over 200 quality journal, conference, and book chapters combined. Pooja Malik is an Assistant Professor at the Department of Computer Science and Engineering at Shiv Nadar University, India. She teaches courses on computing and programming, data structures, and artificial intelligence, and her research interests include artificial intelligence, natural language processing, and machine learning.

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