Digital Twin for Automatic Transportation in Industry 4.0

[EN] 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, machin...

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Detalhes bibliográficos
Autores: Martínez Gutiérrez, Alberto, Díez González, Javier, Ferrero Guillén, Rubén, Verde García, Paula, Álvarez, Rubén, Pérez García, Hilde
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Recursos:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/20238
Acesso em linha:https://www.mdpi.com/1424-8220/21/10/3344
https://hdl.handle.net/10612/20238
Access Level:acceso abierto
Palavra-chave:Ingeniería de sistemas
Ingeniería industrial
Digital twin
AGV
Industry 4.0
Simulation
Smart manufacturing
Cloud computing
Hhyperconnectivity
MIR100
ROS
Industrial ethernet
3310.03 Procesos Industriales
1203.17 Informática
1203.22 Sistema de Control de Producción
Descrição
Resumo:[EN] 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.