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A Reliability Decision Framework for Multiple Repairable Units
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.ORCID iD: 0000-0003-2976-5229
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.
Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ.
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2016 (English)In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 150, p. 78-88Article in journal (Refereed) Published
Abstract [en]

In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplines. This paper presents a decision framework to identify an appropriate reliability model for massive multiple repairable units. It splits non-homogeneous failure data into homogeneous groups and classifies them based on their failure trends using statistical tests. The framework discusses different scenarios for analysing multiple repairable units, according to trend, intensity, and dependency of the units’ failure data. The proposed framework has been verified in a fleet of aircraft and in two simulated data sets. The results show a reliability model of multiple repairable units may contain a mixture of different stochastic models. Considering single reliability models for such populations may cause erroneous calculation of the time to failure of a particular unit, which can, in turn, lead to faulty conclusions and decisions. When dealing with massive and non-homogeneous multiple repairable units, the application of the proposed framework can facilitate the selection of an appropriate reliability model.

Place, publisher, year, edition, pages
2016. Vol. 150, p. 78-88
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
URN: urn:nbn:se:ltu:diva-16337DOI: 10.1016/j.ress.2016.01.020ISI: 000373553800008Scopus ID: 2-s2.0-84957998942Local ID: ff71273c-c01e-473a-8fbf-892f4c195fe4OAI: oai:DiVA.org:ltu-16337DiVA, id: diva2:989313
Note
Validerad; 2016; Nivå 2; 20160204 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved

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Garmabaki, AmirAhmadi, AlirezaBlock, JanKumar, Uday

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