Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
An adaptive opportunistic maintenance model based on railway track condition prediction
Machine Design and Production Engineering Unit, Research Institute for the Science and Management of Risks, University of Mons.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-3266-2434
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
Machine Design and Production Engineering Unit, Research Institute for the Science and Management of Risks, University of Mons.
Number of Authors: 42016 (English)In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 49, no 28, p. 120-125Article in journal (Refereed) Published
Abstract [en]

Maintaining a track line in a good condition is a continuous challenge since it has to deal with various track line heterogeneities that contribute to accelerate its degradation. As a result, railway tracks should be inspected regularly to detect geometry faults and to plan maintenance actions in consequence. A maintenance plan that minimizes track maintenance cost is highly desirable by infrastructure managers. This paper presents an adaptive maintenance scheduling based on track condition prediction. The degradation indicator is the standard deviation of the longitudinal (SDL) level that is sampled on every 200m-long track section. Standards define some thresholds on this indicator that correspond to different levels of severity and related penalty costs. From collected data, a degradation model that uses a random coefficient Wiener degradation-based process is built. A probabilistic model to simulate the recovery effect after the maintenance action (tamping) is also used. Based on this degradation and recovery models, a cost model is built to find the optimal time for tamping on a single track section. After that we use a Monte Carlo approach to assess the performance of the cost model for the whole track line, considering both calendar based and adaptive opportunistic tamping actions. The results show that the adaptive opportunistic maintenance strategy has a lower cost per unit of time than the systematic preventive maintenance.

Place, publisher, year, edition, pages
2016. Vol. 49, no 28, p. 120-125
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-30901DOI: 10.1016/j.ifacol.2016.11.021ISI: 000401258400021Scopus ID: 2-s2.0-85006371622Local ID: 4e369732-ec6c-439c-bbc6-de538df1578fOAI: oai:DiVA.org:ltu-30901DiVA, id: diva2:1004130
Conference
IFAC Workshop on Advanced Maintenance Engineering, Service and Technology : 19/10/2016 - 21/10/2016
Note

Konferensartikel i tidskrift

Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-07-10Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Soleimanmeigouni, ImanAhmadi, Alireza

Search in DiVA

By author/editor
Soleimanmeigouni, ImanAhmadi, Alireza
By organisation
Operation, Maintenance and Acoustics
Other Civil Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 202 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf