An integrated FTA-FMEA model for risk analysis of engineering systems : a case study of subsea blowout preventers

Shafiee, Mahmood and Enjema, Evenye and Kolios, Athanasios (2019) An integrated FTA-FMEA model for risk analysis of engineering systems : a case study of subsea blowout preventers. Applied Sciences, 9 (6). 1192. ISSN 2076-3417 (https://doi.org/10.3390/app9061192)

[thumbnail of Shafiee-etal-AS-2019-An-integrated-FTA-FMEA-model-for-risk-analysis-of-engineering-systems]
Preview
Text. Filename: Shafiee_etal_AS_2019_An_integrated_FTA_FMEA_model_for_risk_analysis_of_engineering_systems.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (2MB)| Preview

Abstract

Engineering systems such as energy production facilities, aviation systems, maritime vessels, etc. continue to grow in size and complexity. This growth has made the identification, quantification and mitigation of risks associated with the failure of such systems so complicated. To solve this problem, several advanced techniques such as Fault Tree Analysis (FTA), Failure Mode and Effects Analysis (FMEA), Reliability-Block Diagram (RBD), Reliability-Centered Maintenance (RCM), Monte-Carlo Simulation (MCS), Markov Analysis (MA) and Bayesian Networks (BN) have been developed in the literature. In order to improve the strengths and eliminate the drawbacks of classical techniques, some hybrid models have been recently developed. In this paper, an integrated FTA and FMEA model is proposed for risk analysis of safety-critical systems. Minimal cut sets derived from the fault trees are weighted based on Birnbaum’s measure of importance and then the weights are used to revise Risk Priority Numbers (RPNs) obtained from the use of traditional FMEA techniques. The proposed model is applied to a Blowout Preventer (BOP) system operating under erratic and extreme conditions in a subsea oil and gas field. Though those failures caused by kill valves and hydraulic lines remain among the top risks in the BOP system, significant differences are revealed in risk rankings when the results from the hybrid approach are compared with those obtained from the classical risk analysis methods.