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2022 | Book

Digital Twin – Fundamental Concepts to Applications in Advanced Manufacturing

Authors: Prof. Dr. Surjya Kanta Pal, Debasish Mishra, Dr. Arpan Pal, Prof. Dr. Samik Dutta, Prof. Dr. Debashish Chakravarty, Dr. Srikanta Pal

Publisher: Springer International Publishing

Book Series : Springer Series in Advanced Manufacturing

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About this book

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.

Table of Contents

Frontmatter
Chapter 1. Evolution of Manufacturing and Its Journey Towards Digital Twin
Abstract
This chapter sets the prologue of industrial revolutions, starting from the first to the fourth. It aims at making the readers aware of the transformations happened so far.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 2. Sensor Electronics for Digital Twin
Abstract
For building a digital twin, sensors and associated electronic components will be at the core as they would sense and gather necessary information from the physical machine.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 3. Signal Processing for Digital Twin
Abstract
The previous chapter discussed the importance and role of sensors in manufacturing. With the data in hand, one needs to process it for extracting meaningful information.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 4. Image Processing for Digital Twin
Abstract
Improvement of product quality by reducing downtime is the ultimate aim in manufacturing. The product quality can be monitored from the process signals or images acquired at the time of manufacturing. For example, in machining, damage or wear of cutting tool causes degradation in product quality. This damage or wear can be monitored from the process signals such as force, acoustic emission, power, vibration etc. acquired during machining.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 5. Data Communication-Edge, Fog, and Cloud Computing
Abstract
Industry 4.0 is aimed at connecting the machine, materials, and other infrastructure through data collected from the sensors. The data acquired from the sensors will be utilised to monitor, diagnose, predict, control, optimize plant operations, etc. Because the number of connected devices is going to be huge, the amount of data will also be large.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 6. Artificial Intelligence and Machine Learning in Manufacturing
Abstract
The diagnosis of manufacturing processes and systems, prediction of machine health for corrective measures are mainly achieved through various machine learning techniques. In the previous chapters, discussions were held around the signal and image processing techniques, using which meaningful information was gathered from the raw data. The results are validated by correlating with the experiments.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Chapter 7. Digital Twin Application
Abstract
This chapter introduces the concept of digital twin in details. The explanations given in Chap. 1 about building a digital twin model are revisited and the ideas are elaborated. Digital twins proposed in different routes of manufacturing are also discussed.
Surjya Kanta Pal, Debasish Mishra, Arpan Pal, Samik Dutta, Debashish Chakravarty, Srikanta Pal
Metadata
Title
Digital Twin – Fundamental Concepts to Applications in Advanced Manufacturing
Authors
Prof. Dr. Surjya Kanta Pal
Debasish Mishra
Dr. Arpan Pal
Prof. Dr. Samik Dutta
Prof. Dr. Debashish Chakravarty
Dr. Srikanta Pal
Copyright Year
2022
Electronic ISBN
978-3-030-81815-9
Print ISBN
978-3-030-81814-2
DOI
https://doi.org/10.1007/978-3-030-81815-9

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