Link and effect model for performance improvement of railway infrastructure

Stenström, Christer; Parida, Aditya; Galar, Diego; Kumar, Uday

doi:10.1177/0954409713492956

Cited by 22 publications

(21 citation statements)

References 22 publications

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“…The health and maintenance of these assets is critical to the effectiveness, efficiency and security of humans, processes and products [1]. Any improvement in the condition or maintenance management and the technology involved in maintenance tasks can have a substantial influence on the operation to provide higher asset revenue.…”

Section: Disparate Data Sources For Asset Health Assessmentmentioning

confidence: 99%

Context awareness for maintenance decision making: A diagnosis and prognosis approach

et al. 2015

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Section: Disparate Data Sources For Asset Health Assessmentmentioning

confidence: 99%

Context awareness for maintenance decision making: A diagnosis and prognosis approach

et al. 2015

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“…However, further parameters and cost modelling is considered in an extension of the case study in Section 10.4.3. Further information regarding the data collection in railways can be found in Stenström et al (2012) and Stenström et al (2013).…”

Section: Data Collectionmentioning

confidence: 99%

Measuring performance of linear assets considering their spatial extension

Stenström

Parida

2014

J of Qual in Maintenance Eng

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Purpose -In this study, linear assets performance are examined regarding analysis and presentation, considering both the technical asset and the user context, to simplify cognitive tasks of planning and decision-making. Design/methodology/approach -Linear, or continuous assets, such as roads, railways, electrical grids and pipelines, are large, geographically spread out technical systems. Linear assets are comprised of system, subsystem and component levels. Thus, asset managers are involved with each level of the linear asset; asset management has strategic, tactical and operational levels. A method is developed to link together the technical and organisational levels and to measure asset performance considering their spatial extension. Geographical location and time are used as independent variables. Findings -For performance measurement of linear assets, it is found that the spatial extension is an equally generic dimension as time is for technical assets in general. Furthermore, as linear assets actually are combinations of linear and point assets; separate analysis of these assets is a prerequisite. Asset performance has been studied in a case study in terms failures and cost; the results indicate that the method visualise poor, as well as good, performance in an easy to interpret manner. Besides, the results indicate that other parameters related to dependability can be presented in a similar way. Practical implications -This study highlights the importance of including the spatial/geographical extension of linear assets in infrastructure managers' performance measurement. It is believed that the method can make planning and decision making more effective by pointing out improvement areas in technical assets, in a way that is intuitive to both technicians and managers. Social implications -As infrastructure managers are improving their analysis and visualisation of performance, the public's interest of following the information increases, which in turn contributes to the connection between infrastructure managers and the public. Originality/value -The presented method and case study analysed performance in function of both the technical and organisational levels, including the spatial component. It is believed that the method for analysing and visualising performance of linear assets is distinctive.

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“…This is commonly done by starting from the business goal and working in a bottom-up manner [19,20]. Hundreds of indicators can be spread throughout the various organisational units on the operational level, but the top management level may have only a few indicators, depending on the structure of the organisation, e.g.…”

Section: Scorecards and Aggregation Of Performance In-dicatorsmentioning

confidence: 99%

Bottom to Top Approach for Railway KPI Generation

Villarejo

Johansson

Leturiondo

et al. 2017

Management Systems in Production Engineering

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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.

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Link and effect model for performance improvement of railway infrastructure

Cited by 22 publications

References 22 publications

Context awareness for maintenance decision making: A diagnosis and prognosis approach

Context awareness for maintenance decision making: A diagnosis and prognosis approach

Measuring performance of linear assets considering their spatial extension

Bottom to Top Approach for Railway KPI Generation

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