Bottom to Top Approach for Railway KPI Generation
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 o...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Sciendo
2017-09-01
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| Series: | Management Systems in Production Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/mspe-2017-0028 |
| _version_ | 1811303162874691584 |
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| author | Villarejo Roberto Johansson Carl-Anders Leturiondo Urko Simon Victor Seneviratne Dammika Galar Diego |
| author_facet | Villarejo Roberto Johansson Carl-Anders Leturiondo Urko Simon Victor Seneviratne Dammika Galar Diego |
| author_sort | Villarejo Roberto |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T07:41:56Z |
| format | Article |
| id | doaj.art-e6119863891342d295be399646828add |
| institution | Directory Open Access Journal |
| issn | 2450-5781 |
| language | English |
| last_indexed | 2024-04-13T07:41:56Z |
| publishDate | 2017-09-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Management Systems in Production Engineering |
| spelling | doaj.art-e6119863891342d295be399646828add2022-12-22T02:55:51ZengSciendoManagement Systems in Production Engineering2450-57812017-09-0125319119810.1515/mspe-2017-0028Bottom to Top Approach for Railway KPI GenerationVillarejo Roberto0Johansson Carl-Anders1Leturiondo Urko2Simon Victor3Seneviratne Dammika4Galar Diego5Luleå University of Technology, 971 87 Luleå, SwedenLuleå University of Technology, 971 87 Luleå, SwedenLuleå University of Technology 971 87, Luleå, SwedenLuleå University of Technology, 971 87 Luleå, SwedenLuleå University of Technology, 971 87 Luleå, SwedenLuleå University of Technology, 971 87 Luleå, SwedenRailway 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.https://doi.org/10.1515/mspe-2017-0028railway assetsfusionhierarchyaggregationkpiperformancecondition monitoringcmms |
| spellingShingle | Villarejo Roberto Johansson Carl-Anders Leturiondo Urko Simon Victor Seneviratne Dammika Galar Diego Bottom to Top Approach for Railway KPI Generation Management Systems in Production Engineering railway assets fusion hierarchy aggregation kpi performance condition monitoring cmms |
| title | Bottom to Top Approach for Railway KPI Generation |
| title_full | Bottom to Top Approach for Railway KPI Generation |
| title_fullStr | Bottom to Top Approach for Railway KPI Generation |
| title_full_unstemmed | Bottom to Top Approach for Railway KPI Generation |
| title_short | Bottom to Top Approach for Railway KPI Generation |
| title_sort | bottom to top approach for railway kpi generation |
| topic | railway assets fusion hierarchy aggregation kpi performance condition monitoring cmms |
| url | https://doi.org/10.1515/mspe-2017-0028 |
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