Failure distributions in multicomponent systems with imperfect repairs

Richard Arnold; Stefanka Chukova; Yu Hayakawa

doi:10.1177/1748006X15584853

Failure distributions in multicomponent systems with imperfect repairs

Richard Arnold^*, Stefanka Chukova, Yu Hayakawa

^*Corresponding author for this work

School of International Liberal Studies

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

We present a model for correlated failures in multicomponent systems where failed components are repaired. Due to these repairs multiple failures of each component are observable. Repair is instantaneous, but imperfect: in general the component is not returned to the good-as-new condition. Correlation amongst failures and the overall ageing of the system are modelled by treating each component failure as a shock which damages the other components in the system. We construct the likelihood for observations generated by such a system, and show how to simulate from this model. We demonstrate inference of the model parameters with simulated data and two real-world examples.

Original language	English
Pages (from-to)	4-17
Number of pages	14
Journal	Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Volume	230
Issue number	1
DOIs	https://doi.org/10.1177/1748006X15584853
Publication status	Published - 2016 Feb 1

Keywords

Multi-component system
dependent components
imperfect repairs
inference
simulation

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality

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10.1177/1748006X15584853

Cite this

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abstract = "We present a model for correlated failures in multicomponent systems where failed components are repaired. Due to these repairs multiple failures of each component are observable. Repair is instantaneous, but imperfect: in general the component is not returned to the good-as-new condition. Correlation amongst failures and the overall ageing of the system are modelled by treating each component failure as a shock which damages the other components in the system. We construct the likelihood for observations generated by such a system, and show how to simulate from this model. We demonstrate inference of the model parameters with simulated data and two real-world examples.",

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author = "Richard Arnold and Stefanka Chukova and Yu Hayakawa",

note = "Funding Information: This work is supported by the Japan Society for the Promotion of Science (grant number L13540) and Waseda University ,Grant for Special Projects (grant number 2014B-443).",

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AU - Arnold, Richard

AU - Chukova, Stefanka

AU - Hayakawa, Yu

N1 - Funding Information: This work is supported by the Japan Society for the Promotion of Science (grant number L13540) and Waseda University ,Grant for Special Projects (grant number 2014B-443).

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N2 - We present a model for correlated failures in multicomponent systems where failed components are repaired. Due to these repairs multiple failures of each component are observable. Repair is instantaneous, but imperfect: in general the component is not returned to the good-as-new condition. Correlation amongst failures and the overall ageing of the system are modelled by treating each component failure as a shock which damages the other components in the system. We construct the likelihood for observations generated by such a system, and show how to simulate from this model. We demonstrate inference of the model parameters with simulated data and two real-world examples.

AB - We present a model for correlated failures in multicomponent systems where failed components are repaired. Due to these repairs multiple failures of each component are observable. Repair is instantaneous, but imperfect: in general the component is not returned to the good-as-new condition. Correlation amongst failures and the overall ageing of the system are modelled by treating each component failure as a shock which damages the other components in the system. We construct the likelihood for observations generated by such a system, and show how to simulate from this model. We demonstrate inference of the model parameters with simulated data and two real-world examples.

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KW - imperfect repairs

KW - inference

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Failure distributions in multicomponent systems with imperfect repairs

Abstract

Keywords

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