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Digital Twin for Smart Manufacturing
- 1st Edition - August 24, 2023
- Editors: Rajesh Kumar Dhanaraj, Ali Kashif Bashir, Rajasekar Vani, Balamurugan Balusamy, Pooja Malik
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 9 2 0 5 - 3
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 8 4 0 - 0
Digital Twin for Smart Manufacturing: Emerging Approaches and Applications provides detailed descriptions on how to integrate and optimize novel digital technologies for smart man… Read more
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Request a sales quoteDigital 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.
- Includes detailed case studies that show how digital twins have been successfully implemented
- Shows how digital twins can be used to improve sustainability through superior energy usage management
- Outlines potential future uses of the digital twin, thus pointing the way for future research directions
Advanced students, researchers, and manufacturing engineers with an interest in Industry 4.0, smart factories, and digital twins
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Chapter 1. Digital twin and digital twin–driven manufacturing
- Abstract
- 1.1 Origin of digital twin
- References
- Chapter 2. Knowledge-Driven Digital Twin Manufacturing
- Abstract
- 2.1 Introduction
- 2.2 A service-oriented model for the Industrial Internet
- 2.3 A technological architecture of a service-oriented digital twin
- 2.4 A flexible ontology-based knowledge structure
- 2.5 A technological solution for advanced ubiquitous knowledge fruition
- 2.6 Conclusions and further research
- References
- Chapter 3. Digital twin and artificial intelligence in industries
- Abstract
- 3.1 Introduction
- 3.2 Methodology
- 3.3 Conclusion
- References
- Chapter 4. Artificial intelligence–driven digital twins in Industry 4.0
- Abstract
- 4.1 Introduction
- 4.2 Digital twin and artificial intelligence in smart manufacturing
- 4.3 Digital twins in the intelligentization of automotive autonomous driving
- 4.4 Digital twins in intelligent urban transportation
- 4.5 Conclusion
- References
- Chapter 5. Industry 4.0: survey of digital twin in smart manufacturing and smart cities
- Abstract
- 5.1 Introduction
- 5.2 Digital twin—an introduction
- 5.3 Types of digital twin
- 5.4 Digital twin and base technologies
- 5.5 Smart cities—an introduction
- 5.6 Smart manufacturing—an introduction
- 5.7 Digital twin—use cases in additive manufacturing
- 5.8 Digital twin—use cases in ship-building industry
- 5.9 Digital twin—use cases in automotive industry
- 5.10 Applications of digital twin in smart manufacturing
- 5.11 Applications of digital twin technology in smart city projects
- 5.12 Summary
- References
- Chapter 6. Digital twins and artificial intelligence: transforming industrial operations
- Abstract
- 6.1 Introduction
- 6.2 Digital twin in industry
- 6.3 Data acquisition in digital twin using Internet of Things
- 6.4 Manufacturing process digital twin model
- 6.5 Industrial machinery maintenance
- 6.6 Case study JSC 120A digital twin in artificial intelligence manufacturing
- 6.7 Challenges and future work
- 6.8 Future work
- 6.9 Conclusion
- References
- Chapter 7. The convergence of digital twin, Internet of Things, and artificial intelligence: digital smart farming
- Abstract
- 7.1 Inroduction
- 7.2 Internet of Things in agriculture
- 7.3 Digital twin smart farming
- 7.4 Digital smart farming system
- 7.5 First result and analysis
- 7.6 Conclusion
- References
- Chapter 8. Digital twin meets artificial intelligence: AI-augmented industrial automation systems using intelligent digital twins
- Abstract
- 8.1 Introduction
- 8.2 Artificial intelligence in industrial automation (IA)
- 8.3 Digital twin with intelligence
- 8.4 Artificial intelligence agents—digital twin
- 8.5 Digital twin for smart manufacturing
- 8.6 Conclusion
- References
- Chapter 9. Digital twin technologies for automated vehicles in smart healthcare systems
- Abstract
- 9.1 Introduction
- 9.2 Autonomous vehicles
- 9.3 Industry 4.0 in the healthcare industry
- 9.4 Significant technologies related to Industry 4.0 in the healthcare sector
- 9.5 Cloud computing
- 9.6 Importance of artificial intelligence in industry 4.0
- 9.7 Additive manufacturing
- 9.8 Benefits of additive manufacturing (AM) in Industry 4.0
- 9.9 Advanced robotics
- 9.10 Conclusions
- References
- Chapter 10. Impact of internet of things and digital twin on manufacturing era
- Abstract
- 10.1 Internet of Things
- 10.2 Importance of Internet of Things
- 10.3 Norms and framework for the Internet of Things
- 10.4 The following are the Internet of Things frameworks
- 10.5 Benefits of Internet of Things
- 10.6 What is the Internet of Things in the workplace?
- 10.7 Internet of Things device management
- 10.8 Internet of Things connectivity and networking
- 10.9 Application of Internet of Things
- 10.10 Qualities of Internet of Things
- References
- Chapter 11. Fault diagnosis in digital twin manufacturing
- Abstract
- 11.1 Introduction
- 11.2 Fault diagnosis in digital twin
- 11.3 Assistive technologies in digital twin
- 11.4 Cyber physical system and digital twin
- 11.5 Digital twin in fault diagnosis
- References
- Chapter 12. Potential applications of digital twin technology in virtual factory
- Abstract
- 12.1 Introduction
- 12.2 Digital model
- 12.3 Digital shadow
- 12.4 Digital twin
- 12.5 Foundational concept
- 12.6 Crucial technical components of VR
- 12.7 Types of digital twin
- 12.8 Working of digital twin
- 12.9 Components of digital twin
- 12.10 Simulation
- 12.11 Simulation versus digital twin
- 12.12 Literature review
- 12.13 Potential applications of digital twin
- 12.14 Incorporating technologies
- 12.15 The general architecture of Internet of Things
- 12.16 Pros and cons of digital twin technology
- 12.17 Future scope of digital twin
- 12.18 Conclusion
- Further reading
- Chapter 13. Digital twins in precision agriculture monitoring using artificial intelligence
- Abstract
- 13.1 Introduction
- 13.2 Background
- 13.3 Existing methodology
- 13.4 Proposed methodology
- 13.5 Conclusion
- References
- Chapter 14. Digital twins and cyber-physical system architecture for smart factory
- Abstract
- 14.1 Introduction to digital twins and cyber-physical system
- 14.2 Digital twin-based smart factory cyber-physical system modeling
- 14.3 Digital twin in cyber-physical system-based production systems
- 14.4 Case studies
- Index
- No. of pages: 350
- Language: English
- Edition: 1
- Published: August 24, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780323992053
- eBook ISBN: 9780323958400
RD
Rajesh Kumar Dhanaraj
Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, 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 member 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).
Affiliations and expertise
Professor, Symbiosis International (Deemed University), Pune, IndiaAB
Ali Kashif Bashir
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.
Affiliations and expertise
Metropolitan University, UKRV
Rajasekar Vani
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.
Affiliations and expertise
Assistant Professor, M.Tech( Information and Cyberwarefare), Kongu Engineering College, IndiaBB
Balamurugan Balusamy
Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar Institution of Eminence, Delhi-NCR. He is part of the Top 2% Scientists Worldwide 2023 by Stanford University in the area of Data Science/AI/ML. He is also an Adjunct Professor, Department of Computer Science and Information Engineering, Taylor University, Malaysia. His contributions focus on engineering education, block chain, and data sciences.
Affiliations and expertise
Shiv Nadar University, Delhi-NCR, IndiaPM
Pooja Malik
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.
Affiliations and expertise
Assistant Professor, Department of Computer Science and Engineering, Shiv Nadar University, IndiaRead Digital Twin for Smart Manufacturing on ScienceDirect