<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Bottom to Top Approach for Railway KPI Generation

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"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...

Bottom to Top Approach for Railway KPI Generation

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Published Online: Aug 01, 2017

Page range: 191 - 198

Received: Oct 01, 2016

Accepted: Apr 01, 2017

DOI: https://doi.org/10.1515/mspe-2017-0028

Keywords
railway assets, fusion, hierarchy, aggregation, KPI, performance, condition monitoring, CMMS

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Bottom to Top Approach for Railway KPI Generation

Article Category: Special Issue Title: Maintenance Performance Measurement and Management Challenges: from Sensing to Decision Support

Published Online: Aug 01, 2017

Page range: 191 - 198

Received: Oct 01, 2016

Accepted: Apr 01, 2017

DOI: https://doi.org/10.1515/mspe-2017-0028

Keywordsrailway assets, fusion, hierarchy, aggregation, KPI, performance, condition monitoring, CMMS

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
railway assets, fusion, hierarchy, aggregation, KPI, performance, condition monitoring, CMMS