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An approach to Symbolic Modelling: a Railway Case study for Maintenance Recovery Level Identification
Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
2017 (English)In: Proceedings of MPMM 2016: 6th International Conference on Maintenance Performance Measurement and Management, 28 November 2016, Luleå, Sweden / [ed] Diego Galar, Dammika Seneviratne, Luleå: Luleå tekniska universitet, 2017, 187- p.Conference paper, Abstract (Refereed)
Abstract [en]

Increasing demand for quality and reliability of the asset is progressively seen as a motivation for improved maintenance procedure and management. Always the role of qualitative maintenance data is neglected in the maintenance recovery level identification. Human factor parameter in the maintenance and qualitative technical data, for instance, maintenance experience, maintenance knowledge, training, quality before maintenance, number of previous maintenance, maintenance documentation and environmental condition can be collected and evaluated to increase the accuracy of maintenance recovery estimation. This information always expressed linguistically and considering their effect in the recovery model is challenging. The aim of this study is to propose a symbolic model to capture the effect of above qualitative factor on maintenance recovery level. Fuzzy inference systems are applied to qualitative expert knowledge to extract the percentage effect which can be incorporated in the recovery level model. The tamping railway case study is considered to validate the model. The results show that the maintenance experience and environmental condition are playing main role in maintenance quality. The application of above method can be extended to asset condition assessment in combination with data driven and physical model

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2017. 187- p.
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-63920ISBN: 978-91-7583-841-0 (electronic)OAI: oai:DiVA.org:ltu-63920DiVA: diva2:1108276
Conference
Maintenance Performance and Measurement and Management 2016(MPMM 2016). November 28, Luleå, Sweden
Available from: 2017-06-12 Created: 2017-06-12 Last updated: 2017-06-12Bibliographically approved

Open Access in DiVA

Proceedings(22302 kB)34 downloads
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File name FULLTEXT01.pdfFile size 22302 kBChecksum SHA-512
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Type fulltextMimetype application/pdf

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
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  • Other style
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Language
  • de-DE
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More languages
Output format
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