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Miniatura
Fecha
2023-04-07
Derechos de acceso
info:eu-repo/semantics/openAccess
Título de la revista
ISSN de la revista
Título del volumen
Editorial
MDPI

Citas

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Resumen
Through the construction of parametric simulation models in which possible storage space distributions and positioning logics are also considered as variables, it is possible to build scenarios that allow analyzing the changing reality of storage needs in order to minimize material movements in each case, optimize internal transportation, and increase the efficiency of production processes. This article shows a particular analysis of a restricted storage space in height, typical to when it comes to logistics associated with raw material in a “big bag” format made of recycled and easily deteriorated material. In conjunction, a location management solution based on passive RFID (radio-frequency identification) tags has been chosen. The process is carried out through simulations with object-oriented discrete event software, where the optimization of the internal transport associated with the layout is carried out considering network theory to define the shortest path between warehouse nodes. The combination of both approaches allows, on the one hand, the evaluation of alternatives in terms of distribution and positioning logics, while the implemented system enables the possibility of making agile changes in the physical configuration of this type of storage space.
Descripción
The registered version of this article, first published in Applied Sciences, is available online at the publisher's website: MDPI, https://doi.org/10.3390/app13084652
La versión registrada de este artículo, publicado por primera vez en Applied Sciences, está disponible en línea en el sitio web del editor: MDPI, https://doi.org/10.3390/app13084652
Categorías UNESCO
Palabras clave
multivariate simulation, RFID, digital twin, warehouse, internal transport
Citación
Félix-Cigalat, J.S.; Domingo, R. Towards a Digital Twin Warehouse through the Optimization of Internal Transport. Applied Sciences 2023, 13, 4652. https://doi.org/10.3390/app13084652
Centro
E.T.S. de Ingenieros Industriales
Departamento
Ingeniería de Construcción y Fabricación
Grupo de investigación
Grupo de innovación
Programa de doctorado
Cátedra
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