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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/10/3344 |
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| author | Alberto Martínez-Gutiérrez Javier Díez-González Rubén Ferrero-Guillén Paula Verde Rubén Álvarez Hilde Perez |
| author_facet | Alberto Martínez-Gutiérrez Javier Díez-González Rubén Ferrero-Guillén Paula Verde Rubén Álvarez Hilde Perez |
| author_sort | Alberto Martínez-Gutiérrez |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T11:30:37Z |
| format | Article |
| id | doaj.art-5bf084c6f3da4608bc142d3bf3f4ac44 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T11:30:37Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5bf084c6f3da4608bc142d3bf3f4ac442023-11-21T19:15:08ZengMDPI AGSensors1424-82202021-05-012110334410.3390/s21103344Digital Twin for Automatic Transportation in Industry 4.0Alberto Martínez-Gutiérrez0Javier Díez-González1Rubén Ferrero-Guillén2Paula Verde3Rubén Álvarez4Hilde Perez5Department of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainDepartment of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainDepartment of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainDepartment of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainDepartment of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainDepartment of Mechanical, Computer and Aerospace Engineering, Universidad de León, 24071 León, SpainIndustry 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.https://www.mdpi.com/1424-8220/21/10/3344Digital TwinAGVIndustry 4.0simulationsmart manufacturingcloud computing |
| spellingShingle | Alberto Martínez-Gutiérrez Javier Díez-González Rubén Ferrero-Guillén Paula Verde Rubén Álvarez Hilde Perez Digital Twin for Automatic Transportation in Industry 4.0 Sensors Digital Twin AGV Industry 4.0 simulation smart manufacturing cloud computing |
| 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 | Digital Twin AGV Industry 4.0 simulation smart manufacturing cloud computing |
| url | https://www.mdpi.com/1424-8220/21/10/3344 |
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