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A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing
The recent COVID-19 outbreak impact on the world economy has boosted the increasing business needs to force manufacturing plants adapting to unpredictable changes and ensuring the continuity of industrial production. The demand for asset monitoring solutions and specialised support at the shop floor...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758418/ https://www.ncbi.nlm.nih.gov/pubmed/36569781 http://dx.doi.org/10.1016/j.cie.2021.107896 |
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author | García, Álvaro Bregon, Anibal Martínez-Prieto, Miguel A. |
author_facet | García, Álvaro Bregon, Anibal Martínez-Prieto, Miguel A. |
author_sort | García, Álvaro |
collection | PubMed |
description | The recent COVID-19 outbreak impact on the world economy has boosted the increasing business needs to force manufacturing plants adapting to unpredictable changes and ensuring the continuity of industrial production. The demand for asset monitoring solutions and specialised support at the shop floor has become an increasingly important digital priority in industry that pushes human–machine technological upgrades leading to digital workforce skills assessment. In the case of traditional manufacturing, Small and Medium-sized Enterprises (SMEs) face the challenge of managing digital technologies and Industry 4.0 (I4.0) maturity models with a low adoption rate. In this digital context very few SMEs with traditional means have anticipated the latest advances in maintenance strategies impeded by technical and economical barriers. This work presents a human–machine technological integration solution in traditional manufacturing based on a non-intrusive retrofitting development with interoperable I4.0 tools. The method provides a common and rapidly deployable hardware and software architecture supporting an HMI-based legacy maintenance approach and addresses its evaluation focused on the physical-digital convergence of older industrial systems. A case study applying a digital process approach integrated with condition-based maintenance (CBM) techniques, has been carried out on a CNC milling machine and reproduced in an injection moulding machine during COVID-19 alert state. These already existing scenarios served to deploy digital retrofitting and communication strategies without interfering in working conditions. Patterns extracted from the machines were monitored in real-time interacting with the operational knowledge of the experienced staff. In this way, we provided an original contribution to confront human–machine challenges with improvements applied in traditional manufacturing, where workers and industrial systems were collaboratively updated with augmented digital strategies and proactive CBM environments. |
format | Online Article Text |
id | pubmed-9758418 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97584182022-12-19 A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing García, Álvaro Bregon, Anibal Martínez-Prieto, Miguel A. Comput Ind Eng Article The recent COVID-19 outbreak impact on the world economy has boosted the increasing business needs to force manufacturing plants adapting to unpredictable changes and ensuring the continuity of industrial production. The demand for asset monitoring solutions and specialised support at the shop floor has become an increasingly important digital priority in industry that pushes human–machine technological upgrades leading to digital workforce skills assessment. In the case of traditional manufacturing, Small and Medium-sized Enterprises (SMEs) face the challenge of managing digital technologies and Industry 4.0 (I4.0) maturity models with a low adoption rate. In this digital context very few SMEs with traditional means have anticipated the latest advances in maintenance strategies impeded by technical and economical barriers. This work presents a human–machine technological integration solution in traditional manufacturing based on a non-intrusive retrofitting development with interoperable I4.0 tools. The method provides a common and rapidly deployable hardware and software architecture supporting an HMI-based legacy maintenance approach and addresses its evaluation focused on the physical-digital convergence of older industrial systems. A case study applying a digital process approach integrated with condition-based maintenance (CBM) techniques, has been carried out on a CNC milling machine and reproduced in an injection moulding machine during COVID-19 alert state. These already existing scenarios served to deploy digital retrofitting and communication strategies without interfering in working conditions. Patterns extracted from the machines were monitored in real-time interacting with the operational knowledge of the experienced staff. In this way, we provided an original contribution to confront human–machine challenges with improvements applied in traditional manufacturing, where workers and industrial systems were collaboratively updated with augmented digital strategies and proactive CBM environments. Elsevier Ltd. 2022-02 2021-12-23 /pmc/articles/PMC9758418/ /pubmed/36569781 http://dx.doi.org/10.1016/j.cie.2021.107896 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 García, Álvaro Bregon, Anibal Martínez-Prieto, Miguel A. A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title | A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title_full | A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title_fullStr | A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title_full_unstemmed | A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title_short | A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
title_sort | non-intrusive industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758418/ https://www.ncbi.nlm.nih.gov/pubmed/36569781 http://dx.doi.org/10.1016/j.cie.2021.107896 |
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