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Bottom to Top Approach for Railway KPI Generation
Luleå tekniska universitet, Drift, underhåll och akustik.
Luleå tekniska universitet, Drift, underhåll och akustik.
Luleå tekniska universitet, Drift, underhåll och akustik.
Luleå tekniska universitet, Drift, underhåll och akustik.
Vise andre og tillknytning
Ansvarlig organisasjon
2017 (engelsk)Inngår i: Management Systems in Production Engineering, ISSN 2299-0461, Vol. 25, nr 3, s. 191-198, artikkel-id 28Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Railway 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 key performance indicators (KPIs) linked to punctuality or capacity can help planned and scheduled 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 hierarchized 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 decision-making tool for asset managers at different hierarchical levels.

sted, utgiver, år, opplag, sider
Walter de Gruyter , 2017. Vol. 25, nr 3, s. 191-198, artikkel-id 28
Emneord [en]
railway assets, fusion, hierarchy, aggregation, KPI, performance, condition monitoring, CMMS
HSV kategori
Forskningsprogram
FOI-portföljer, Strategiska initiativ
Identifikatorer
URN: urn:nbn:se:trafikverket:diva-5962DOI: 10.1515/mspe-2017-0028ISI: 000408931800008OAI: oai:DiVA.org:trafikverket-5962DiVA, id: diva2:1741006
Prosjekter
JVTC
Forskningsfinansiär
Swedish Transport Administration, TRV 2011/58769
Merknad

Validerad;2017;Nivå 2;2017-10-03 (rokbeg)

Tilgjengelig fra: 2017-09-12 Laget: 2023-03-02

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Villarejo, RobertoJohansson, Carl-andersUrko, LeturiondoSimon, VictorSeneviratne, DammikaGalar, Diego

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Villarejo, RobertoJohansson, Carl-andersUrko, LeturiondoSimon, VictorSeneviratne, DammikaGalar, Diego

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