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dc.creatorSánchez Herguedas, Antonio Jesúses
dc.creatorMena Nieto, Angel Isidroes
dc.creatorRodrigo Muñoz, Franciscoes
dc.creatorVillalba Díez, Javieres
dc.creatorOrdieres Meré, Joaquínes
dc.date.accessioned2022-03-25T19:02:59Z
dc.date.available2022-03-25T19:02:59Z
dc.date.issued2022-02
dc.identifier.citationSánchez-Herguedas, A.J., Mena Nieto, A.I., Rodrigo Muñoz, F., Villalba Díez, J. y Ordieres Meré, J. (2022). Optimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approach. sensors, 22 (4), 1432.
dc.identifier.issn1424-8220es
dc.identifier.urihttps://hdl.handle.net/11441/131304
dc.description.abstractThis paper exposes the existing problems for optimal industrial preventive maintenance intervals when decisions are made with right-censored data obtained from a network of sensors or other sources. A methodology based on the use of the z transform and a semi-Markovian approach is presented to solve these problems and obtain a much more consistent mathematical solution. This methodology is applied to a real case study of the maintenance of large marine engines of vessels dedicated to coastal surveillance in Spain to illustrate its usefulness. It is shown that the use of right-censored failure data significantly decreases the value of the optimal preventive interval calculated by the model. In addition, that optimal preventive interval increases as we consider older failure data. In sum, applying the proposed methodology, the maintenance manager can modify the preventive maintenance interval, obtaining a noticeable economic improvement. The results obtained are relevant, regardless of the number of data considered, provided that data are available with a duration of at least 75% of the value of the preventive interval.es
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades (MICINN). España RTI2018-094614-B-I00 (SMASHING)es
dc.formatapplication/vnd.oasis.opendocument.spreadsheetes
dc.formatapplication/vnd.oasis.opendocument.presentationes
dc.formatapplication/vnd.oasis.opendocument.databasees
dc.formatimage/jpeges
dc.format.extent17 p.es
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSensors, 22 (4), 1432.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMaintenance intervales
dc.subjectMaintenance modeles
dc.subjectSemi-Markov processes
dc.subjectRight-censored dataes
dc.subjectFinite horizones
dc.subjectMaintenance costes
dc.titleOptimisation of Maintenance Policies Based on Right-Censored Failure Data Using a Semi-Markovian Approaches
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas Ies
dc.relation.projectIDRTI2018-094614-B-I00 (SMASHING)es
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/22/4/1432es
dc.identifier.doi10.3390/s22041432es
dc.contributor.groupUniversidad de Sevilla.TEP134: Organizacion Industriales
dc.journaltitlesensorses
dc.publication.volumen22es
dc.publication.issue4es
dc.publication.initialPage1432es
dc.contributor.funderAgencia Estatal de Investigación. Españaes

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