Reliability evaluation of repairable systems considering component heterogeneity using frailty model
Brown, Bodunrin and Liu, Bin and McIntyre, Stuart and Revie, Matthew (2022) Reliability evaluation of repairable systems considering component heterogeneity using frailty model. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 237 (4). pp. 654-670. ISSN 1748-006X (https://doi.org/10.1177/1748006X221109341)
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Abstract
The failure processes of heterogeneous repairable systems with minimal repair assumption can be modelled by nonhomogeneous Poisson processes. One approach to describe an unobserved heterogeneity between systems is to multiply the intensity function by a positive random variable (frailty term) with a gamma distribution. This approach assumes that the relative frailty distribution among survivors is independent of age. Where systems are being continuously repaired and modified, the frailty distribution may be dependent on the system’s age. This paper investigates the application of the inverse Gaussian (IG) frailty model for modelling the failure processes of heterogeneous repairable systems. The IG frailty model, which combines the power law model and inverse Gaussian distribution, assumes that the relative frailty distribution among survivors becomes increasingly homogeneous over time. We develop the maximum likelihood for the IG frailty model, a method for event prediction, and investigate the effect of accuracy of the IG estimator and mis-specification of the frailty distribution through a simulation study. The mean estimates of the scale and shape parameters of the intensity function are examined for bias and efficiency loss. We find that the developed estimator is robust to changes in the input parameters for a relatively large sample sizes. We investigate the robustness of selecting an IG compared with a gamma frailty model. The developed IG model is applied to real data for illustration showing an improvement on existing models.
ORCID iDs
Brown, Bodunrin, Liu, Bin ORCID: https://orcid.org/0000-0002-3946-8124, McIntyre, Stuart ORCID: https://orcid.org/0000-0002-0640-7544 and Revie, Matthew ORCID: https://orcid.org/0000-0002-0130-8109;-
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Item type: Article ID code: 80746 Dates: DateEvent3 August 2022Published3 August 2022Published Online24 April 2022AcceptedSubjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management Department: Strathclyde Business School > Management Science
Strategic Research Themes > Ocean, Air and Space
Strategic Research Themes > Innovation Entrepreneurship
Strathclyde Business School > EconomicsDepositing user: Pure Administrator Date deposited: 17 May 2022 09:23 Last modified: 03 Oct 2024 04:02 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/80746