This book provides readers with a guide to the use of Digital Twin in manufacturing. It presents a collection of fundamental ideas about sensor electronics and data acquisition, signal and image processing techniques, seamless data communications, artificial intelligence and machine learning for decision making, and explains their necessity for the practical application of Digital Twin in Industry.

Providing case studies relevant to the manufacturing processes, systems, and sub-systems, this book is beneficial for both academics and industry professionals within the field of Industry 4.0 and digital manufacturing.

Offers a guide to the practical implementation of Digital Twin Provides practical case studies for each theoretical topic discussed Describes methods relevant to the manufacturing applications clearly and succinctly

Autorentext

Professor Surjya K Pal gained his M.Tech from IIT Kanpur in 1993, and his PhD from IIT Kharagpur in 1999. He then worked as postdoctoral researcher at The University of Sheffield until 2002, after which he took up a teaching position at IIT Guwahati. Since 2004, he has been working at IIT Kharagpur, where he is currently a Professor in the Department of Mechanical Engineering, and the Chairperson of the Centre of Excellence in Advanced Manufacturing Technology. He has written over 156 international journal articles, 90 conference papers and presentations, and 15 book chapters. He has also filed 11 patents. His research interests primarily focus on Industry 4.0, friction stir welding, and the modelling and simulation of manufacturing processes. Debasish Mishra is a doctoral student in Advanced Technology Development Centre at IIT Kharagpur, after gaining his M.Tech from VSSUT Burla in 2016. He has published 9 international journal articles and 2 book chapters, as well as filed 4 patents. His research interests are primarily in Industry 4.0 based real-time monitoring and control of manufacturing process. Dr Arpan Pal gained his M.Tech from IIT Kharagpur in 1993, and his PhD from Aalborg University in 2013. He has worked in several research and industry positions, including his current role as Chief Scientist and Research Area Head, in Embedded Systems and Robotics at TATA Consultancy Services Research. He has filed more than 150 patents, and over 130 journal articles, conference papers and book chapters. His research interests include sensing and IoT, signal processing and AI, and robotics and edge processing. Dr Samik Dutta gained his M.Tech from the National Institute of Technology, Durgapur, in 2004, and his PhD from IIT Kharagpur in 2015. He is currently Principal Scientist in the Surface Engineering and Tribology Group at the CSIR-Central Mechanical Engineering Research Institute, and also an Associate Professor at the Academy of Scientific and Innovative Research. He has published over 20 international journal articles, 10 conference papers and 1 book chapter. His research interests are primarily in image processing, machine learning, and process monitoring, and precision engineering. Professor Debashish Chakravarty gained his masters and PhD from IIT Kharagpur, in 1993 and 1995 respectively, where he currently works as a Professor in the Department of Mining Engineering. His research interests are focused on rescue & field robotics with AI applications of digital image & signal processing. He has written 125 journal articles and conference papers, as has filed for 3 patents. Professor Srikanta Pal gained his M.Tech in 1992 from Jadavpur University (India), and his PhD in 2003 from Oxford University. He has worked in several teaching and research positions, including his current role as Professor, and previously as Head of the Department of Electronics & Communication Engineering at the Birla Institute of Technology Mesra. He has published over 80 journal and conference papers, focused primarily on antennas, statistical signal processing, metamaterials, and 3D printing.

Inhalt
Introduction.- Sensor Electronics.- Signal Acquisition and Processing.- Image Processing.- Data Communication: Cloud and Fog Computing.- Machine Learning and Decision Making.- Artificial Intelligence in Decision Making.- Digital Twin Application.- Conclusions. <p