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dc.contributor.authorFernández Barrero, David
dc.contributor.authorFontenla-Romero, Óscar
dc.contributor.authorLamas-López, Francisco
dc.contributor.authorNovoa-Paradela, David
dc.contributor.authorR-Moreno, María
dc.contributor.authorSanz, David
dc.date.accessioned2021-09-10T14:17:19Z
dc.date.available2021-09-10T14:17:19Z
dc.date.issued2021
dc.identifier.citationFernández-Barrero, D.; Fontenla-Romero, O.; Lamas-López, F.; Novoa-Paradela, D.; R-Moreno, M.D.; Sanz, D. SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets. Appl. Sci. 2021, 11, 7322. https://doi.org/10.3390/app11167322es_ES
dc.identifier.urihttp://hdl.handle.net/2183/28448
dc.description.abstract[Abstract] Predictive maintenance has lately proved to be a useful tool for optimizing costs, performance and systems availability. Furthermore, the greater and more complex the system, the higher the benefit but also the less applied: Architectural, computational and complexity limitations have historically ballasted the adoption of predictive maintenance on the biggest systems. This has been especially true in military systems where the security and criticality of the operations do not accept uncertainty. This paper describes the work conducted in addressing these challenges, aiming to evaluate its applicability in a real scenario: It presents a specific design and development for an actual big and diverse ecosystem of equipment, proposing an semi-unsupervised predictive maintenance system. In addition, it depicts the solution deployment, test and technological adoption of real-world military operative environments and validates the applicability.es_ES
dc.description.sponsorshipThis research was funded by DGAM-PLATIN (General Directorate of Armament and Material—Spanish Ministry of Defence) with project funding number ‘2018/1003218001400’.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.urihttps://doi.org/10.3390/app11167322es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)es_ES
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectPredictive maintenancees_ES
dc.subjectBehavioural anomaly detectiones_ES
dc.subjectMachine learninges_ES
dc.subjectDeep learninges_ES
dc.subjectWarshipses_ES
dc.titleSOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assetses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleApplied Scienceses_ES
UDC.volume11es_ES
UDC.startPage7322es_ES
dc.identifier.doi10.3390/app11167322


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