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Manufacturing maps, a novel tool for smart factory management based on Petri nets and big data mini-terms

Title: Manufacturing maps, a novel tool for smart factory management based on Petri nets and big data mini-terms
metadata.dc.creator: Llopis Ballester, Javier.
Lacasa Corral, Antonio.
García Magraner, Eduardo Andrés.
Montés Sánchez, Nicolás.
Hilario Pérez, Lucía.
Vizcaíno Hilario, Judith.
Latorre Iranzo, Juan Carlos.
Keywords: Petri nets.Datos masivo - Aplicaciones en industria del automóvil.Petri, Redes de.Automobile industry and trade - Automation.Automóviles - Fabricación - Teledetección.Automóviles - Producción.Industria del automóvil - Producción.Big data in Automobile industry and trade.Automobiles - Production.Automobile industry and trade - Production.Automobiles - Manufacturing - Remote sensing.Industria del automóvil - Automatización.
Publisher: MDPI
Citation: Llopis, J., Lacasa, A., Garcia, E., Montés, N., Hilario, L., Vizcaíno, J., Vilar, C., et al. (2022). Manufacturing maps, a novel tool for smart factory management based on Petri nets and big data mini-terms. Mathematics, vol. 10, i. 14 (08 jul.), art. 398. DOI:
Abstract: This article defines a new concept for real-time factory management—manufacturing maps. Manufacturing maps are generated from two fundamental elements, mini-terms and Petri nets. Mini-terms are sub-times of a technical cycle, the time it takes for any component to perform its task. A mini-term, by definition, is a sub-cycle time and it would only make sense to use the term in connection with production improvement. Previous studies have shown that when the sub-cycle time worsens, this indicates that something unusual is happening, enabling anticipation of line failures. As a result, a mini-term has dual functionality, since, on the one hand, it is a production parameter and, on the other, it is a sensor used for predictive maintenance. This, combined with how easy and cheap it is to extract relevant data from manufacturing lines, has resulted in the mini-term becoming a new paradigm for predictive maintenance, and, indirectly, for production analysis. Applying this parameter using big data for machines and components can enable the complete modeling of a factory using Petri nets. This article presents manufacturing maps as a hierarchical construction of Petri nets in which the lowest level network is a temporary Petri net based on mini-terms, and in which the highest level is a global view of the entire plant. The user of a manufacturing map can select intermediate levels, such as a specific production line, and perform analysis or simulation using real-time data from the mini-term database. As an example, this paper examines the modeling of the 8XY line, a multi-model welding line at the Ford factory in Almussafes (Valencia), where the lower layers are modeled until the mini-term layer is reached. The results, and a discussion of the possible applications of manufacturing maps in industry, are provided at the end of this article.
Description: Este artículo se encuentra disponible en la siguiente URL:
Este artículo de investigación pertenece al número especial "Industrial Big Data and Process Modelling for Smart Manufacturing".
En este artículo de investigación también participan: Cristina Vilar, Judit Vilar y Laura Sánchez.
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ISSN: 2227-7390 (Electrónico)
Language: es
Issue Date: 8-Jul-2022
Center : Universidad Cardenal Herrera-CEU
Appears in Collections:Dpto. Matemáticas, Física y Ciencias Tecnológicas

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