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Reliability analysis and growth curves modelling of fielded road systems

Reliability analysis and growth curves modelling of fielded road systems

Tee, Kong Fah ORCID: 0000-0003-3202-873X and Ekpiwhre, Ejiroghene Onome (2018) Reliability analysis and growth curves modelling of fielded road systems. World Review of Intermodal Transportation Research, 7 (2). pp. 168-194. ISSN 1749-4729 (Print), 1749-4737 (Online) (doi:https://doi.org/10.1504/WRITR.2018.091255)

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Abstract

The instantaneous and cumulative effect of failure rate for repairable fielded systems depletes the reliability of road network systems. This paper bridges the rationale and statistical techniques employed in the reliability analysis and growth curve modelling for application to road assets with defects/failure events obtained from fielded systems. Real-time user operational data is analysed to enable preventive and predictive maintenance insight be adapted from its growth trends and curves. Samples from carriageway fielded population are analysed, and models are developed using statistical assessment of goodness of fit for Poisson, right censored parametric distribution analysis and parametric growth trend. The reliability behaviour of the samples is evaluated using reliability estimates of its mean time to failure (MTTF) for instantaneous failure time of event and mean time between failure (MTBF) for cumulative times of events. The growth trend and parametric growth curves of the homogeneous Poisson process (HPP) and non-homogeneous Poisson process (NHPP) power law are presented using maximum likelihood and least square estimation as well as the mean cumulative function (MCF) of failure time of events.

Item Type: Article
Uncontrolled Keywords: Reliability Analysis; Road Systems; Mean Time Between Failure; Homogeneous Poisson Process
Subjects: T Technology > TE Highway engineering. Roads and pavements
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Last Modified: 29 Oct 2018 15:30
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/19744

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