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Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems

The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among...

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Autores principales: Leng, Jiewu, Zhou, Man, Xiao, Yuxuan, Zhang, Hu, Liu, Qiang, Shen, Weiming, Su, Qianyi, Li, Longzhang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740749/
https://www.ncbi.nlm.nih.gov/pubmed/35035124
http://dx.doi.org/10.1016/j.jclepro.2021.127278
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author Leng, Jiewu
Zhou, Man
Xiao, Yuxuan
Zhang, Hu
Liu, Qiang
Shen, Weiming
Su, Qianyi
Li, Longzhang
author_facet Leng, Jiewu
Zhou, Man
Xiao, Yuxuan
Zhang, Hu
Liu, Qiang
Shen, Weiming
Su, Qianyi
Li, Longzhang
author_sort Leng, Jiewu
collection PubMed
description The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among cities become difficult for engineers and equipment. Consequently, the costly physical commissioning of a new manufacturing system is greatly hindered. As an emerging technology, digital twins can achieve semi-physical simulation to avoid the vast cost of physical commissioning of the manufacturing system. Therefore, this paper proposes a digital twins-based remote semi-physical commissioning (DT-RSPC) approach for open architecture flow-type smart manufacturing systems. A digital twin system is developed to enable the remote semi-physical commissioning. The proposed approach is validated through a case study of digital twins-based remote semi-physical commissioning of a smartphone assembly line. The results showed that combining the open architecture design paradigm with the proposed digital twins-based approach makes the commissioning of a new flow-type smart manufacturing system more sustainable.
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spelling pubmed-87407492022-01-10 Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems Leng, Jiewu Zhou, Man Xiao, Yuxuan Zhang, Hu Liu, Qiang Shen, Weiming Su, Qianyi Li, Longzhang J Clean Prod Article The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among cities become difficult for engineers and equipment. Consequently, the costly physical commissioning of a new manufacturing system is greatly hindered. As an emerging technology, digital twins can achieve semi-physical simulation to avoid the vast cost of physical commissioning of the manufacturing system. Therefore, this paper proposes a digital twins-based remote semi-physical commissioning (DT-RSPC) approach for open architecture flow-type smart manufacturing systems. A digital twin system is developed to enable the remote semi-physical commissioning. The proposed approach is validated through a case study of digital twins-based remote semi-physical commissioning of a smartphone assembly line. The results showed that combining the open architecture design paradigm with the proposed digital twins-based approach makes the commissioning of a new flow-type smart manufacturing system more sustainable. Elsevier Ltd. 2021-07-15 2021-04-26 /pmc/articles/PMC8740749/ /pubmed/35035124 http://dx.doi.org/10.1016/j.jclepro.2021.127278 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Leng, Jiewu
Zhou, Man
Xiao, Yuxuan
Zhang, Hu
Liu, Qiang
Shen, Weiming
Su, Qianyi
Li, Longzhang
Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title_full Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title_fullStr Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title_full_unstemmed Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title_short Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
title_sort digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740749/
https://www.ncbi.nlm.nih.gov/pubmed/35035124
http://dx.doi.org/10.1016/j.jclepro.2021.127278
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