MOSPPA: monitoring system for palletised packaging recognition and tracking
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Título: | MOSPPA: monitoring system for palletised packaging recognition and tracking |
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Autor/es: | Castaño Amorós, Julio | Fuentes, Francisco | Gil, Pablo |
Grupo/s de investigación o GITE: | Automática, Robótica y Visión Artificial |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal |
Palabras clave: | Manufacturing automation | Cardboard packaging | Pallets recognition and tracking | Pallets workflow control |
Fecha de publicación: | 23-feb-2023 |
Editor: | Springer Nature |
Cita bibliográfica: | The International Journal of Advanced Manufacturing Technology. 2023, 126: 179-195. https://doi.org/10.1007/s00170-023-11098-6 |
Resumen: | The paper industry manufactures corrugated cardboard packaging, which is unassembled and stacked on pallets to be supplied to its customers. Human operators usually classify these pallets according to the physical features of the cardboard packaging. This process can be slow, causing congestion on the production line. To optimise the logistics of this process, we propose a visual recognition and tracking pipeline that monitors the palletised packaging while it is moving inside the factory on roller conveyors. Our pipeline has a two-stage architecture composed of Convolutional Neural Networks, one for oriented pallet detection and recognition, and another with which to track identified pallets. We carried out an extensive study using different methods for the pallet detection and tracking tasks and discovered that the oriented object detection approach was the most suitable. Our proposal recognises and tracks different configurations and visual appearance of palletised packaging, providing statistical data in real time with which to assist human operators in decision-making. We tested the precision-performance of the system at the Smurfit Kappa facilities. Our proposal attained an Average Precision (AP) of 0.93 at 14 Frames Per Second (FPS), losing only 1% of detections. Our system is, therefore, able to optimise and speed up the process of logistic distribution. |
Patrocinador/es: | Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Research work was partially funded by the private project (SMURFITKAPPA-21), supported by Smurfit Kappa Iberoamericana S.A. and University of Alicante. |
URI: | http://hdl.handle.net/10045/132264 |
ISSN: | 0268-3768 (Print) | 1433-3015 (Online) |
DOI: | 10.1007/s00170-023-11098-6 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1007/s00170-023-11098-6 |
Aparece en las colecciones: | INV - AUROVA - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Castano-Amoros_etal_2023_IntJAdvManufTechnol.pdf | 5,32 MB | Adobe PDF | Abrir Vista previa | |
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