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eMaintenance solution through online data analysis for railway maintenance decision-making
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-0734-0959
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-3827-0295
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0002-0055-2740
2014 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 20, no 3, p. 262-275Article in journal (Refereed) Published
Abstract [en]

Purpose – The purpose of this paper is to demonstrate how research within the railway sector is developing eMaintenance solutions using the cloud and web-based applications for improved condition monitoring, better maintenance and increased uptime. This eMaintenance solution is based on the on-line data acquisition, integration and analysis leading to effective maintenance decision making.Design/methodology/approach – In the proposed methodology, data are acquired from railway measurement stations to the eMaintenance cloud, where they are filtered, fused, integrated and analyzed to assist maintenance decisions. Extensive consultation with stakeholders has resulted in the analysis of railway data.Findings – The paper provides a concept for a web-based eMaintenance solution for railway maintenance stakeholders for making fact-based decisions and develops more efficient and economically sound maintenance policies. Train wheels reaching their maintenance and safety limits are visualised in grids and graphs to assist stakeholders in making the appropriate maintenance decisions.Practical implications – In this paper the authors have demonstrated that the wheel profile and force data can be remotely collected through cloud utilization. The information generated can be used for maintenance decision making. Similarly, other measurable data can also be utilized for maintenance decision making.Originality/value – This paper describes the importance of eMaintenance solution through online data analysis to make effective and efficient railway maintenance decisions, as a case study.

Place, publisher, year, edition, pages
2014. Vol. 20, no 3, p. 262-275
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-6590DOI: 10.1108/JQME-05-2014-0026Scopus ID: 2-s2.0-84907104624Local ID: 4d6fb407-484b-4a78-8e0f-f5c79e24757aOAI: oai:DiVA.org:ltu-6590DiVA, id: diva2:979476
Note
Validerad; 2014; 20140629 (ravkou)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Kour, RavdeepTretten, PhillipKarim, Ramin

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