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Digital Twin for Automatic Transportation in Industry 4.0
Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151569/ https://www.ncbi.nlm.nih.gov/pubmed/34065011 http://dx.doi.org/10.3390/s21103344 |
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author | Martínez-Gutiérrez, Alberto Díez-González, Javier Ferrero-Guillén, Rubén Verde, Paula Álvarez, Rubén Perez, Hilde |
author_facet | Martínez-Gutiérrez, Alberto Díez-González, Javier Ferrero-Guillén, Rubén Verde, Paula Álvarez, Rubén Perez, Hilde |
author_sort | Martínez-Gutiérrez, Alberto |
collection | PubMed |
description | Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper. |
format | Online Article Text |
id | pubmed-8151569 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81515692021-05-27 Digital Twin for Automatic Transportation in Industry 4.0 Martínez-Gutiérrez, Alberto Díez-González, Javier Ferrero-Guillén, Rubén Verde, Paula Álvarez, Rubén Perez, Hilde Sensors (Basel) Article Industry 4.0 is the fourth industrial revolution consisting of the digitalization of processes facilitating an incremental value chain. Smart Manufacturing (SM) is one of the branches of the Industry 4.0 regarding logistics, visual inspection of pieces, optimal organization of processes, machine sensorization, real-time data adquisition and treatment and virtualization of industrial activities. Among these tecniques, Digital Twin (DT) is attracting the research interest of the scientific community in the last few years due to the cost reduction through the simulation of the dynamic behaviour of the industrial plant predicting potential problems in the SM paradigm. In this paper, we propose a new DT design concept based on external service for the transportation of the Automatic Guided Vehicles (AGVs) which are being recently introduced for the Material Requirement Planning satisfaction in the collaborative industrial plant. We have performed real experimentation in two different scenarios through the definition of an Industrial Ethernet platform for the real validation of the DT results obtained. Results show the correlation between the virtual and real experiments carried out in the two scenarios defined in this paper with an accuracy of 97.95% and 98.82% in the total time of the missions analysed in the DT. Therefore, these results validate the model created for the AGV navigation, thus fulfilling the objectives of this paper. MDPI 2021-05-11 /pmc/articles/PMC8151569/ /pubmed/34065011 http://dx.doi.org/10.3390/s21103344 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Martínez-Gutiérrez, Alberto Díez-González, Javier Ferrero-Guillén, Rubén Verde, Paula Álvarez, Rubén Perez, Hilde Digital Twin for Automatic Transportation in Industry 4.0 |
title | Digital Twin for Automatic Transportation in Industry 4.0 |
title_full | Digital Twin for Automatic Transportation in Industry 4.0 |
title_fullStr | Digital Twin for Automatic Transportation in Industry 4.0 |
title_full_unstemmed | Digital Twin for Automatic Transportation in Industry 4.0 |
title_short | Digital Twin for Automatic Transportation in Industry 4.0 |
title_sort | digital twin for automatic transportation in industry 4.0 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8151569/ https://www.ncbi.nlm.nih.gov/pubmed/34065011 http://dx.doi.org/10.3390/s21103344 |
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