Please use this identifier to cite or link to this item: https://hdl.handle.net/10316.2/33365
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dc.contributor.authorVillarejo, Roberto
dc.contributor.authorJohansson, Carl-Anders
dc.contributor.authorLeturiondo, Urko
dc.contributor.authorSimon, Victor
dc.contributor.authorGalar, Diego
dc.date.accessioned2014-09-09T11:14:02Z
dc.date.accessioned2020-09-10T09:00:33Z-
dc.date.available2014-09-09T11:14:02Z
dc.date.available2020-09-10T09:00:33Z-
dc.date.issued2014-
dc.identifier.urihttps://hdl.handle.net/10316.2/33365-
dc.description.abstractRailway maintenance especially on infrastructure produces a vast amount of data. However, having data is not synonymous with having information; rather, data must be processed to extract information. In railway maintenance, the development of KPIs linked to punctuality or capacity can help plan and schedule maintenance, thus aligning the maintenance department with corporate objectives. There is a need for an improved method to analyse railway data to find the relevant KPIs. The system should support maintainers, answering such questions as what maintenance should be done, where and when. The system should equip the user with the knowledge of the infrastructure's condition and configuration, and the traffic situation so maintenance resources can be targeted to only those areas needing work. The amount of information is vast, so it must be hierarchised and aggregated; users must filter out the useless indicators. Data are fused by compiling several individual indicators into a single index; the resulting composite indicators measure multidimensional concepts which cannot be captured by a single index. The paper describes a method of monitoring a complex entity. In this scenario, a plurality of use indices and weighting values are used to create a composite and aggregated use index from a combination of lower level use indices and weighting values. The resulting composite and aggregated indicators can be a decisionmaking tool for asset managers at different hierarchical levels.eng
dc.language.isoeng-
dc.publisherImprensa da Universidade de Coimbrapor
dc.publisherFaculdade de Ciências e Tecnologia da Universidade de Coimbra, Departamento de Engenharia Mecânicapor
dc.relation.ispartofColecao:http://hdl.handle.net/10316.2/33309por
dc.rightsopen access-
dc.subjectmaximum railway assetseng
dc.subjectfusioneng
dc.subjecthierarchyeng
dc.subjectgranularityeng
dc.subjectaggregationeng
dc.subjectKPIeng
dc.subjectperformanceeng
dc.subjectDSSeng
dc.titleBottom to top approach for railway KPI generationpor
dc.typebookPartpor
uc.publication.firstPage171-
uc.publication.lastPage177-
uc.publication.locationCoimbrapor
dc.identifier.doi10.14195/978-972-8954-42-0_25-
uc.publication.digCollectionPBpor
uc.publication.orderno26-
uc.publication.areaCiências da Engenharia e Tecnologiaspor
uc.publication.bookTitleProceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014-
uc.publication.manifesthttps://dl.uc.pt/json/iiif/10316.2/33365/212151/manifest?manifest=/json/iiif/10316.2/33365/212151/manifest-
uc.publication.thumbnailhttps://dl.uc.pt/retrieve/11181626-
uc.publication.parentItemId53866-
uc.itemId70466-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Proceedings of Maintenance Performance Measurement and Management (MPMM) Conference 2014
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