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Processing mining for maintenance decision support
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-1938-0985
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, p. 179-Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Process mining is gaining importance for the classification, clustering, workflow models, process discovery, predictions and planning and scheduling in a process or events in especially business oriented fields. On the other hand, there are several events that are required to perform a maintenance action in various industries. There is a need to understand the process flow of events to reduce the delays to increase the performance of the maintenance action. This paper applies the concept of process mining to understand the events in a typical maintenance action (repair or replacement,). We implemented the process mining for administrative, logistic and repair delays for one section in Swedish Railway. We identified the bottlenecks in this process fordifferent subsystems for productive feedback to the railway industry.

Place, publisher, year, edition, pages
Luleå: Luleå tekniska universitet, 2017. p. 179-
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-63905ISBN: 978-91-7583-841-0 (electronic)OAI: oai:DiVA.org:ltu-63905DiVA, id: diva2:1108184
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: 2017-11-24Bibliographically approved

Open Access in DiVA

Proceedings(22302 kB)44 downloads
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File name FULLTEXT01.pdfFile size 22302 kBChecksum SHA-512
710a395ad10e685ab0840cb31fd069a1b7f4fd2e571fd2bccd2bd52c3eabccde86d840e2ed0c10f3f90e48a4d8ff7c62988987c3e654540b96e3d990c5bac465
Type fulltextMimetype application/pdf

Authority records BETA

Thaduri, AdithyaFamurewa, Stephen Mayowa

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • de-DE
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  • Other locale
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Output format
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