Dynamic reliability assessment of a complex recovery system using fault tree, fuzzy inference and discrete event simulation

• Autorzy: Nobakhti Abolghasem , Raissi Sadigh , Damghani Kaveh Khalili , Soltani Roya

Identyfikatory

DOI

10.17531/ein.2021.4.1

• Języki publikacji: EN

Abstrakty

EN

Any failure on the recovery system will cause a lot of environmental damage as well as energy loss. Hereof two types of alternatives; fast opening valve system (FOVS) and seal drum system (SDS) may be installed. The focus of this article is on the decision stage to choose the most preferred option in terms of reliability assessment. The major challenge in the research problem is on changing the pressure and temperature during operational cycles, which significantly affect the reliability. In addition, the lack of historical data complicates the reliability assessment method. Hence, we proposed a hybrid approach using fault tree analysis (FTA) and the Mamdani fuzzy inference to estimate reliability response as a function of a few frequently operating pressure and temperature. Also, discrete-event simulation helped us to evaluate the system reliability at different operating conditions. The comparisons reveals that the FOVs outperforms on average of 22.4% than the SDS and it is recommended for putting into practice for purchasing.

Słowa kluczowe

EN

dynamic reliability assessment; Fault Tree Analysis (FTA); Mamdani Fuzzy Inference Method; discrete event simulation; flare gas recovery system

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2021
• Tom: Vol. 23, no. 4
• Strony: 593--604
• Opis fizyczny: Bibliogr. 22 poz., rys., tab.

Twórcy

autor

Nobakhti Abolghasem

• School of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran

autor

Raissi Sadigh

• School of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran
• Research Center for Modeling and Optimization in Science and Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran

autor

Damghani Kaveh Khalili

• School of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran

autor

Soltani Roya

• Department of Industrial Engineering, KHATAM University, Tehran, Iran

Bibliografia

• 1. Attar Ahmad, Raissi Sadigh, Khalili-Damghani Kaveh. A simulation-based optimization approach for free distributed repairable multistate availability-redundancy allocation problems, Reliability Engineering & System Safety. 2017; 157: 177-191, https://doi.org/10.1016/j.ress.2016.09.006.
• 2. Azadeh A, Ebrahimipour V, Bavar P. A fuzzy inference system for pump failure diagnosis to improve maintenance process: The case of a petrochemical industry. Expert Systems with Applications 2010; 37(1): 627-639, https://doi.org/10.1016/j.eswa.2009.06.018.
• 3. Baig AA, Ruzli R. Estimation of failure probability using fault tree analysis and fuzzy logic for CO2 transmission. International Journal of Environmental Science and Development 2014; 5(1): 26.
• 4. Briš R, Praaks P. Simulation approach for modeling of dynamic reliability using time dependent acyclic graph. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2006; (2): 26-38.
• 5. Choi IH, Chang D. Reliability and availability assessment of seabed storage tanks using fault tree analysis. Ocean Engineering 2016; 120:1- 14, https://doi.org/10.1016/j.oceaneng.2016.04.021.
• 6. Elsayed T. Fuzzy inference system for the risk assessment of liquefied natural gas carriers during loading/offloading at terminals. Applied Ocean Research 2009; 31(3): 179-185, https://doi.org/10.1016/j.apor.2009.08.004.
• 7. Elvidge CD, Bazilian MD, Zhizhin M, Ghosh T, Baugh K, Hsu F-C. The potential role of natural gas flaring in meeting greenhouse gas mitigation targets. Energy Strategy Reviews 2018; 20:156-162, https://doi.org/10.1016/j.esr.2017.12.012.
• 8. Khodayee SM, Chiacchio F, Papadopoulos Y. A Novel Approach Based on Stochastic Hybrid Fault Tree to Compare Alternative Flare Gas Recovery Systems. IEEE Access 2021; 9: 51029-49, https://doi.org/10.1109/ACCESS.2021.3069807.
• 9. Nematkhah Farnam, Raissi Sadigh, Ghezavati Vahidreza. An Integrated Fuzzy DEMATEL-Fuzzy ANP Approach to Nominate Diagnostic Method and Measuring Total Predictive Performance Score, Safety and Reliability 2017; 37(1): 37-42, https://doi.org/10.1080/09617353.2017.1411676.
• 10. Pietrusiak D. Evaluation of large-scale load-carrying structures of machines with the application of the dynamic effects factor. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19(4) :542-551, https://doi.org/10.17531/ein.2017.4.7.
• 11. Pourhassan MR, Raissi S, Apornak A. Modeling multi-state system reliability analysis in a power station under fatal and nonfatal shocks: a simulation approach. International Journal of Quality & Reliability Management 2021, https://doi.org/10.1108/IJQRM-07-2020-0244.
• 12. Pourhassan Mohammad Reza, Raissi Sadigh, Hafezalkotob Ashkan. A simulation approach on reliability assessment of complex system subject to stochastic degradation and random shock. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (2): 370-379, https://doi.org/10.17531/ein.2020.2.20.
• 13. Purba JH. A fuzzy-based reliability approach to evaluate basic events of fault tree analysis for nuclear power plant probabilistic safety assessment. Annals of Nuclear Energy 2014; 70: 21-9, https://doi.org/10.1016/j.anucene.2014.02.022.
• 14. Raissi Sadigh, Ebadi Shiva. A Computer Simulation Model for Reliability Estimation of a Complex System. International Journal of Research in Industrial Engineering 2018; 7(1): 19-31, https://doi.org/10.22105/RIEJ.2018.109017.1032.
• 15. Rajakarunakaran S, Kumar AM, Prabhu VA. Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refueling station. Journal of Loss Prevention in the Process Industries 2015; 33: 109-23, https://doi.org/10.1016/j.jlp.2014.11.016.
• 16. Ratnayake Chandima R.M., Application of a fuzzy inference system for functional failure risk rank estimation: RBM of rotating equipment and instrumentation. Journal of Loss Prevention in the Process Industries. 2014; 29: 216-224, https://doi.org/10.1016/j.jlp.2014.03.002.
• 17. Renjith V, Madhu G, Nayagam VLG, Bhasi A. Two-dimensional fuzzy fault tree analysis for chlorine release from a chlor-alkali industry using expert elicitation. Journal of Hazardous Materials 2010; 183(1-3): 103-110, https://doi.org/10.1016/j.jhazmat.2010.06.116.
• 18. Saeidi RG, Amin GR, Raissi S, Gattoufi S. An efficient DEA method for ranking woven fabric defects in textile manufacturing. International Journal of Advanced Manufacturing Technology 2013; 68 (1-4): 349-354, https://doi.org/10.1007/s00170-013-4732-4.
• 19. Selech J, Andrzejczak K. An aggregate criterion for selecting a distribution for times to failure of components of rail vehicles. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (1): 102-111, https://doi.org/10.17531/ein.2020.1.12.
• 20. Wang D, Zhang P, Chen L. Fuzzy fault tree analysis for fire and explosion of crude oil tanks. Journal of Loss Prevention in the Process Industries 2013; 26(6): 1390-1398, https://doi.org/10.1016/j.jlp.2013.08.022.
• 21. Yazdani E, Asadi J, Dehaghani YH, Kazempoor P. Flare gas recovery by liquid ring compressors-system design and simulation. Journal of Natural Gas Science and Engineering 2020; 84: 103627, https://doi.org/10.1016/j.jngse.2020.103627.
• 22. Zhang X, Sun L, Sun H, Guo Q, Bai X. Floating offshore wind turbine reliability analysis based on system grading and dynamic FTA. Journal of Wind Engineering and Industrial Aerodynamics 2016; 154: 21-33, https://doi.org/10.1016/j.jweia.2016.04.005.