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Article

SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets

1
Departamento de Automática, Universidad de Alcalá, 28801 Madrid, Spain
2
Centro de Investigación TIC (CITIC), Universidade da Coruña, 15008 A Coruña, Spain
3
CESADAR-CENTRAL, Armada Española, 30201 Cartagena, Spain
4
INDRA, 28108 Madrid, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Benoit Iung
Appl. Sci. 2021, 11(16), 7322; https://doi.org/10.3390/app11167322
Received: 15 July 2021 / Revised: 26 July 2021 / Accepted: 28 July 2021 / Published: 9 August 2021
(This article belongs to the Special Issue Overcoming the Obstacles to Predictive Maintenance)
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. View Full-Text
Keywords: predictive maintenance; behavioural anomaly detection; machine learning; deep learning; warships predictive maintenance; behavioural anomaly detection; machine learning; deep learning; warships
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MDPI and ACS Style

Fernández-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/app11167322

AMA Style

Fernández-Barrero D, Fontenla-Romero O, Lamas-López F, Novoa-Paradela D, R-Moreno MD, Sanz D. SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets. Applied Sciences. 2021; 11(16):7322. https://doi.org/10.3390/app11167322

Chicago/Turabian Style

Fernández-Barrero, David, Oscar Fontenla-Romero, Francisco Lamas-López, David Novoa-Paradela, María D. R-Moreno, and David Sanz. 2021. "SOPRENE: Assessment of the Spanish Armada’s Predictive Maintenance Tool for Naval Assets" Applied Sciences 11, no. 16: 7322. https://doi.org/10.3390/app11167322

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