Manoharan, H., Teekaraman, Y. orcid.org/0000-0003-4297-3460, Kuppusamy, R. et al. (2 more authors) (2022) Examining the effect of cyber twin and blockchain technologies for industrial applications using AI. Mathematical Problems in Engineering, 2022. 3048038. pp. 1-10. ISSN 1024-123X
Abstract
In current generation the concept of cyber twin technology has been emerging as an improved platform for different applications. This paper emphasize on examining the effect of cyber twin technology for manufacturing equipment in Industry 4.0 applications by solving three different elementary objectives. For the proposed conception a new system model is identified for integrating triobjective cases with artificial intelligence algorithm. In addition, high security measures are also incorporated using blockchain technology which is one basic requirement for industrial applications for creating real twins. Both system model and algorithm have been combined for providing effective performance in real time using a physical entity. The effectiveness of the proposed model is tested with sensor prototype and simulated with four scenarios where the projected model provides better performance for more than 72% when compared with existing methodologies.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (http://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 04 May 2022 07:04 |
Last Modified: | 04 May 2022 07:04 |
Status: | Published |
Publisher: | Hindawi Limited |
Refereed: | Yes |
Identification Number: | 10.1155/2022/3048038 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186139 |