Jundishapur Journal of Health Sciences

Published by: Kowsar

Failure Occurrence Probability Assessment of Claus Furnace Package in Sulfur Recovery Unit Using Fault Tree Analysis Based on Conventional and Fuzzy-Based Approach

Abbas Bakbaki 1 , Nader Nabhani 1 , Bagher Anvaripour 1 , * and Gholamabbas Shirali 2
Authors Information
1 Department of Safety and Protection Engineering, Abadan Faculty of Petroleum Engineering, Petroleum University of Technology, Abadan, IR Iran
2 Department of Occupational Health Engineering, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Article information
  • Jundishapur Journal of Health Sciences: April 2018, 10 (2); e58162
  • Published Online: February 17, 2018
  • Article Type: Research Article
  • Received: September 1, 2017
  • Revised: December 19, 2017
  • Accepted: January 7, 2018
  • DOI: 10.5812/jjhs.58162

To Cite: Bakbaki A, Nabhani N, Anvaripour B, Shirali G. Failure Occurrence Probability Assessment of Claus Furnace Package in Sulfur Recovery Unit Using Fault Tree Analysis Based on Conventional and Fuzzy-Based Approach, Jundishapur J Health Sci. 2018 ; 10(2):e58162. doi: 10.5812/jjhs.58162.

Copyright © 2018, Jundishapur Journal of Health Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited
1. Background
2. Objectives
3. Methods
4. Results
5. Discussion
6. Conclusions
  • 1. Barua S, Gao X, Pasman H, Mannan MS. Bayesian network based dynamic operational risk assessment. J Loss Prevent Process Indust. 2016;41:399-410. doi: 10.1016/j.jlp.2015.11.024.
  • 2. Bakbaki A, Nabhani N, Anvaripour B, Shirali G. Probabilistic risk assessment using fuzzy fault tree analysis based on two types of failure possibility distributions in process industries. J Occup Hyg Eng. 2017;4(2):41-52.
  • 3. Lees F. Lees' Loss prevention in the process industries: Hazard identification, assessment and control. Butterworth-Heinemann; 2012.
  • 4. Mohsendokht M. Risk assessment of uranium hexafluoride release from a uranium conversion facility by using a fuzzy approach. J Loss Prevent Process Indust. 2017;45:217-28. doi: 10.1016/j.jlp.2017.01.004.
  • 5. Shi L, Shuai J, Xu K. Fuzzy fault tree assessment based on improved AHP for fire and explosion accidents for steel oil storage tanks. J Hazard Mater. 2014;278:529-38. doi: 10.1016/j.jhazmat.2014.06.034. [PubMed: 25010458].
  • 6. Rajakarunakaran S, Maniram Kumar A, Arumuga Prabhu V. Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station. J Loss Prevent Process Indust. 2015;33:109-23. doi: 10.1016/j.jlp.2014.11.016.
  • 7. Zadeh LA. Fuzzy sets. Inf Control. 1965;8(3):338-53. doi: 10.1016/s0019-9958(65)90241-x.
  • 8. Sa'idi E, Anvaripour B, Jaderi F, Nabhani N. Fuzzy risk modeling of process operations in the oil and gas refineries. J Loss Prevent Process Indust. 2014;30:63-73. doi: 10.1016/j.jlp.2014.04.002.
  • 9. Tanaka H, Fan LT, Lai FS, Toguchi K. Fault-Tree Analysis by Fuzzy Probability. IEEE Transact Reliabil. 1983;R-32(5):453-7. doi: 10.1109/tr.1983.5221727.
  • 10. Cooke RM, ElSaadany S, Huang X. On the performance of social network and likelihood-based expert weighting schemes. Reliabil Engin System Safety. 2008;93(5):745-56. doi: 10.1016/j.ress.2007.03.017.
  • 11. Omidvari M, Lavasani SMR, Mirza S. Presenting of failure probability assessment pattern by FTA in Fuzzy logic (case study: Distillation tower unit of oil refinery process). J Chem Health Safety. 2014;21(6):14-22. doi: 10.1016/j.jchas.2014.06.003.
  • 12. Miller GA. The magical number seven plus or minus two: some limits on our capacity for processing information. Psychol Rev. 1956;63(2):81-97. [PubMed: 13310704].
  • 13. Chen SJ, Hwang CL, Hwang FP. Fuzzy multiple attribute decision making(methods and applications. Berlin: Springer-Verlag; 2011.
  • 14. Purba JH, Lu JIE, Zhang G, Ruan DA. An Area Defuzzification Technique to Assess Nuclear Event Reliability Data from Failure Possibilities. Int J Comput Intelligence Applicat. 2012;11(4):1250022. doi: 10.1142/s1469026812500228.
  • 15. SINTEF. OREDA. Offshore reliability data handbook. OREDA; 1984.
  • 16. Komal Chang D, Lee S. Fuzzy reliability analysis of dual-fuel steam turbine propulsion system in LNG carriers considering data uncertainty. J Nat Gas Sci Engin. 2015;23:148-64. doi: 10.1016/j.jngse.2015.01.030.

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