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A critical review of Information Assurance (IA) framework forcondition-based maintenance of railway tracks
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.
Number of Authors: 2
2016 (English)In: Proceedings of Esrel 2016 Glasgow, Scotland, 25-29 September 2016 / [ed] Walls, Lesley, London: CRC Press, 2016, Vol. 1, 1072-1078 p.Conference paper (Refereed)
Abstract [en]

Railway maintenance is faced with increasing demands, including the need to improve service.Data measuring the track state and suitable models or applications are needed to make good maintenancedecisions. This critical review paper investigates many research papers on the use of information assurance (IA)within condition-based maintenance (CBM) on a railway track. An IA framework sheds light on the data andinformation used to make maintenance decisions. The paper considers work on data processing and decisionmakingin CBM. The results show condition monitoring suffers from an inability to determine exact positioningon the track; some data are inaccurate or unavailable. Existing studies have not adequately dealt with data contentor the various technologies used. They focus on integrity, availability, authentication, authorisation and accuracy,but do not consider other IA principles important to understand data.CBMmodels and algorithms have difficultyunderstanding degradation models, and data problems mean it is difficult to make good decisions. There is alack of long term maintenance plans. Models also need to be integrated for more realistic but not necessarilyoptimum solutions and to ensure practical predictions of maintenance. Some models focus on degradation, othersconsider prediction, and still others calculate the maintenance cost; it is difficult to combine these. Overall, dataare inaccurate, there is no testing phase using realistic data, and existing models are insufficient. This has anegative impact on maintenance decisions.

Place, publisher, year, edition, pages
London: CRC Press, 2016. Vol. 1, 1072-1078 p.
National Category
Information Systems Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-38175Local ID: c7c4730e-2cd0-4de0-808d-08e4869ca931ISBN: 978-1-138-02997-2OAI: oai:DiVA.org:ltu-38175DiVA: diva2:1011674
Conference
European Safety and Reliability Conference (ESREL 2016), Glasgow, 25/09/2016 - 29/09/2016
Note

Upprättat; 2016; 20160626 (yamald)

Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2016-12-01Bibliographically approved

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A review paper(150 kB)1 downloads
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