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Lookup NU author(s): Ikenna Okaro, Professor Longbin Tao
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
This paper proposes an enhanced Weibull-Corrosion Covariate model for reliability assessment of a system facing operational stresses. The newly developed model is applied to a Subsea Gas Compression System planned for offshore West Africa to predict its reliability index. System technical failure was modelled by developing a Weibull failure model incorporating a physically tested corrosion profile as stress in order to quantify the survival rate of the system under additional operational covariates including marine pH, temperature and pressure. Using Reliability Block Diagrams and enhanced Fusell-Vesely formulations, the whole system was systematically decomposed to subsystems to analyse the criticality of each component and optimise them. Human reliability was addressed using an enhanced barrier weighting method. A rapid degradation curve is obtained on a subsea system relative to the base case subjected to a time-dependent corrosion stress factor. It reveals that subsea system components failed faster than their Mean time to failure specifications from Offshore Reliability Database as a result of cumulative marine stresses exertion. The case study demonstrated that the reliability of a subsea system can be systematically optimised by modelling the system under higher technical and organisational stresses, prioritising the critical sub-systems and making befitting provisions for redundancy and tolerances.
Author(s): Okaro IA, Tao L
Publication type: Article
Publication status: Published
Journal: Reliability Engineering and System Safety
Year: 2016
Volume: 156
Pages: 159-174
Print publication date: 01/12/2016
Online publication date: 02/08/2016
Acceptance date: 25/07/2016
Date deposited: 12/08/2016
ISSN (print): 0951-8320
ISSN (electronic): 1879-0836
Publisher: Elsevier
URL: http://dx.doi.org/10.1016/j.ress.2016.07.018
DOI: 10.1016/j.ress.2016.07.018
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