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Monitoring and prediction of maintenance operations for aircraft engines repair

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dc.contributor.authorMendonça, Leonardo
dc.contributor.authorPires, Flávia
dc.contributor.authorDuarte, Miguel
dc.contributor.authorBarbosa, José
dc.contributor.authorLeitão, Paulo
dc.date.accessioned2026-03-26T16:24:41Z
dc.date.available2026-03-26T16:24:41Z
dc.date.issued2025
dc.description.abstractAccurately estimating the hours required for maintenance, repair and overhaul (MRO) operations in the aviation sector frequently depends on the experience and personal judgment of engineers, can lead to introducing errors, increased operating costs, and time-consuming decision-making. This work presents the development of a cost-effective application to monitor and predict MRO operations in an aeronautical company. The application integrates data-driven algorithms, particularly Machine Learning (ML), with Power BI to provide a dynamic and user-friendly visualisation of historical and predicted data, improving decisionmaking time and facilitating operational planning. The simple linear regression model was the most effective algorithm to predict MRO operation for the case study with a B? of 0.81, balancing simplicity and performance compared to other analysed models.eng
dc.description.sponsorshipThis work was supported by national funds: UID/05757 - Research Centre in Digitalization and Intelligent Robotics (CeDRI); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020). Additionally, this work is co-financed by Component 5 - Capitalization and Business Innovation, integrated in the Resilience Dimension of the Recovery and Resilience Plan within the scope of the Recovery and Resilience Mechanism (MRR) of the European Union (EU), framed in the Next Generation EU, for the period 2021 - 2026, within project Produtech R3, with reference 60.
dc.identifier.citationMendonça, Leonardo; Pires, Flávia; Duarte, Miguel; Barbosa, José; Leitão, Paulo (2025). Monitoring and prediction of maintenance operations for aircraft engines repair. In 15th IFAC Workshop on Intelligent Manufacturing Systems IMS 2025. Koszalin, Poland. 59:2, p. 161-166. ISSN 2405-8963. DOI: 10.1016/j.ifacol.2025.11.858
dc.identifier.doi10.1016/j.ifacol.2025.11.858
dc.identifier.issn2405-8963
dc.identifier.urihttp://hdl.handle.net/10198/36330
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relation.hasversionhttps://www.sciencedirect.com/science/article/pii/S2405896325025790
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectMonitoring
dc.subjectPrediction
dc.subjectMachine Learning
dc.subjectMaintenance
dc.subjectAircraft Engines
dc.titleMonitoring and prediction of maintenance operations for aircraft engines repaireng
dc.typeconference object
dspace.entity.typePublication
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.conferenceDate2025
oaire.citation.conferencePlaceKoszalin, Poland
oaire.citation.endPage166
oaire.citation.issue24
oaire.citation.startPage161
oaire.citation.title15th IFAC Workshop on Intelligent Manufacturing Systems IMS 2025
oaire.citation.volume59
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNamePires
person.familyNameBarbosa
person.familyNameLeitão
person.givenNameFlávia
person.givenNameJosé
person.givenNamePaulo
person.identifierhttps://scholar.google.pt/citations?user=an9quSsAAAAJ&hl=pt-PT
person.identifier609187
person.identifierA-8390-2011
person.identifier.ciencia-idA119-72AB-6255
person.identifier.ciencia-id021B-4191-D8A5
person.identifier.ciencia-id8316-8F13-DA71
person.identifier.orcid0000-0001-7899-3020
person.identifier.orcid0000-0003-3151-6686
person.identifier.orcid0000-0002-2151-7944
person.identifier.ridA-5468-2011
person.identifier.scopus-author-id57200412919
person.identifier.scopus-author-id48360905400
person.identifier.scopus-author-id35584388900
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication3ac8f73e-ecb2-44b6-9c6f-1ee99474e00f
relation.isAuthorOfPublication0c76a063-ff3c-4db3-b6e7-36885020b399
relation.isAuthorOfPublication68d9eb25-ad4f-439b-aeb2-35e8708644cc
relation.isAuthorOfPublication.latestForDiscovery3ac8f73e-ecb2-44b6-9c6f-1ee99474e00f
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