Application of fuzzy fault tree analysis based on modified fuzzy AHP and fuzzy TOPSIS for fire and explosion in the process industry

References

• Yazdi M. The application of bow-tie method in hydrogen sulfide risk management using layer of protection analysis (LOPA). J Fail Anal Prev. 2017;17(2):291–303. doi:doi: 10.1007/s11668-017-0247-x
   Web of Science ®Google Scholar
• Zarei E, Azadeh A, Khakzad N, et al. Dynamic safety assessment of natural gas stations using Bayesian network. J Hazard Mater. 2017;321:830–840. doi: 10.1016/j.jhazmat.2016.09.074
   PubMed Web of Science ®Google Scholar
• Yazdi M, Daneshvar S, Setareh H. An extension to fuzzy developed failure mode and effects analysis (FDFMEA) application for aircraft landing system. Saf Sci. 2017;98:113–123. doi:doi: 10.1016/j.ssci.2017.06.009
   Web of Science ®Google Scholar
• International Electrotechnical Commission (IEC). Fault tree analysis. Geneva: IEC; 2006. Standard No. IEC 61025:2006.
   Google Scholar
• Kabir S, Walker M, Papadopoulos Y, et al. Fuzzy temporal fault tree analysis of dynamic systems. Int J Approx Reason. 2016;77:20–37. doi:doi: 10.1016/j.ijar.2016.05.006
   Web of Science ®Google Scholar
• Kabir S. An overview of fault tree analysis and its application in model based dependability analysis. Expert Syst Appl. 2017;77:114–135. doi:doi: 10.1016/j.eswa.2017.01.058
   Web of Science ®Google Scholar
• Yazdi M, Kabir S. A Fuzzy Bayesian network approach for risk analysis in process industries. Process Saf Environ Prot. 2017;111:507–519. doi: 10.1016/j.psep.2017.08.015
   Web of Science ®Google Scholar
• Zadeh LA. Fuzzy sets. Inf Control. 1965;8:338–353. doi:doi: 10.1109/2.53
   Web of Science ®Google Scholar
• Markowski AS, Mannan MS. Fuzzy logic for piping risk assessment (pfLOPA). J Loss Prev Process Ind. 2009;22(6):921–927. doi:doi: 10.1016/j.jlp.2009.06.011
   Web of Science ®Google Scholar
• Markowski AS, Sam Mannan M. ExSys-LOPA for the chemical process industry. J Loss Prev Process Ind. 2010;23(6):688–696. doi:doi: 10.1016/j.jlp.2010.05.011
   Web of Science ®Google Scholar
• Atanassov KT. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 1986;20:87–96. doi:doi: 10.1016/S0165-0114(86)80034-3
   Web of Science ®Google Scholar
• Yazdi M, Zarei E. Uncertainty handling in the safety risk analysis: an integrated approach based on fuzzy fault tree analysis. J Fail Anal Prev. 2018;2:392–404. https://doi.org/10.1007/s11668-018-0421-9
   Google Scholar
• Atanassov KT. On the concept of intuitionistic fuzzy sets. Berlin: Springer; 2012. Chapter 1, On intuitionistic fuzzy sets theory; p. 1–16. doi: 10.1007/978-3-642-29127-2_1
   Google Scholar
• Nadjafi M, Farsi MA, Jabbari H. Reliability analysis of multi-state emergency detection system using simulation approach based on fuzzy failure rate. Int J Syst Assur Eng Manag. 2017;8(3):532–541. doi: 10.1007/s13198-016-0563-7
   Web of Science ®Google Scholar
• Guan Y, Zhao J, Shi T, et al. Fault tree analysis of fire and explosion accidents for dual fuel (diesel/natural gas) ship engine rooms. J Marine Sci Appl. 2016;15(3):331–335. doi:doi: 10.1007/s11804-016-1366-6
   Web of Science ®Google Scholar
• Ramzali N, Lavasani MRM, Ghodousi J. Safety barriers analysis of offshore drilling system by employing fuzzy event tree analysis. Saf Sci. 2015;78:49–59. doi:doi: 10.1016/j.ssci.2015.04.004
   Web of Science ®Google Scholar
• 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 Prev Process Ind. 2015;33:109–123. doi:doi: 10.1016/j.jlp.2014.11.016
   Web of Science ®Google Scholar
• Mahmood YA, Ahmadi A, Verma AK, et al. Fuzzy fault tree analysis: a review of concept and application. Int J Syst Assur Eng Manag. 2013;4(1):19–32. doi: 10.1007/s13198-013-0145-x
   Google Scholar
• Aiyou W, Shiliang S, Runqiu L, et al. City fire risk analysis based on coupling fault tree method and triangle fuzzy theory. Procedia Eng. 2014;84:204–212. doi:doi: 10.1016/j.proeng.2014.10.427
   Google Scholar
• 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 Heal Saf. 2014;21:14–22. doi: 10.1016/j.jchas.2014.06.003
   Google Scholar
• Sarkar A, Panja SC, Das D. Fault tree analysis of Rukhia gas turbine power plant. HKIE Trans. 2015;22:32–56. doi: 10.1080/1023697X.2015.1008394
   Google Scholar
• Komal. Fuzzy fault tree analysis for patient safety risk modeling in healthcare under uncertainty. Appl Soft Comput. 2015;37:942–951. doi: 10.1016/j.asoc.2015.08.005
   Web of Science ®Google Scholar
• Lavasani SM, Ramzali N, Sabzalipour F, et al. Utilisation of fuzzy fault tree analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells. Ocean Eng. 2015;108:729–737. doi: 10.1016/j.oceaneng.2015.09.008
   Web of Science ®Google Scholar
• Lavasani SM, Zendegani A, Celik M. An extension to fuzzy fault tree analysis (FFTA) application in petrochemical process industry. Process Saf Environ Prot. 2015;93:75–88. doi: 10.1016/j.psep.2014.05.001
   Web of Science ®Google Scholar
• Wang H, Lu X, Du Y, et al. Fault tree analysis based on TOPSIS and triangular fuzzy number. Int J Syst Assur Eng Manag. 2014;8(Suppl 4):2064–2070. doi: 10.1007/s13198-014-0323-5
   Google Scholar
• Dunjó J, Fthenakis V, Vílchez JA, et al. Hazard and operability (HAZOP) analysis. A literature review. J Hazard Mater. 2010;173:19–32. doi: 10.1016/j.jhazmat.2009.08.076
   PubMed Web of Science ®Google Scholar
• Yazdi M, Nikfar F, Nasrabadi M. Failure probability analysis by employing fuzzy fault tree analysis. Int J Syst Assur Eng Manag. 2017;8(Suppl 2):1177–1193. doi: 10.1007/s13198-017-0583-y
   Web of Science ®Google Scholar
• Preyssl C. Safety risk assessment and management – the ESA approach. Reliab Eng Syst Saf. 1995;49:303–309. doi: 10.1016/0951-8320(95)00047-6
   Web of Science ®Google Scholar
• Ford DN, Sterman JD. Expert knowledge elicitation to improve formal and mental models. Syst Dyn Rev. 1998;14:309–340. https://doi.org/10.1002/(SICI)1099-1727(199824)14:4<309::AID-SDR154>3.0.CO;2-5 doi: 10.1002/(SICI)1099-1727(199824)14:4<309::AID-SDR154>3.0.CO;2-5
   Web of Science ®Google Scholar
• Buckley JJ. Fuzzy hierarchical analysis. Fuzzy Sets Syst. 1985;17(3):233–247. doi: 10.1016/0165-0114(85)90090-9
   Web of Science ®Google Scholar
• Kabir G, Hasin MAA. Integrating modified Delphi method with fuzzy AHP for optimal power substation location selection. Int J Multicriteria Decis Mak. 2013;3(4):381–398. doi: 10.1504/IJMCDM.2013.056654
   Google Scholar
• Lin C-T, Wang M-JJ. Hybrid fault tree analysis using fuzzy sets. Reliab Eng Syst Saf. 1997;58:205–213. doi: 10.1016/S0951-8320(97)00072-0
   Web of Science ®Google Scholar
• 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;278:529–538. doi: 10.1016/j.jhazmat.2014.06.034
   PubMed Web of Science ®Google Scholar
• Hsu H-M, Chen C-T. Aggregation of fuzzy opinions under group decision making. Fuzzy Sets Syst. 1996;79:279–285. doi: 10.1016/0165-0114(95)00185-9
   Web of Science ®Google Scholar
• Yazdi M. Hybrid probabilistic risk assessment using fuzzy FTA and fuzzy AHP in a process industry. J Fail Anal Prev. 2017;17(4):756–764. doi: 10.1007/s11668-017-0305-4
   Web of Science ®Google Scholar
• Yazdi M. An extension of fuzzy improved risk graph and fuzzy analytical hierarchy process for determination of chemical complex safety integrity levels. Int J Occup Saf Ergon. 2018:1–11. doi: 10.1080/10803548.2017.1419654
   PubMed Web of Science ®Google Scholar
• Onisawa T. An approach to human reliability in man–machine systems using error possibility. Fuzzy Sets Syst. 1988;27(2):87–103. doi: 10.1016/0165-0114(88)90140-6
   Web of Science ®Google Scholar
• Yazdi M. Risk assessment based on novel intuitionistic fuzzy-hybrid-modified TOPSIS approach. Saf Sci. Forthcoming. [cited 2018 Apr 04]:[11 p]. Corrected proof available at doi: 10.1016/j.ssci.2018.03.005
   Web of Science ®Google Scholar
• Sahin B. Consistency control and expert consistency prioritization for FFTA by using extent analysis method of trapezoidal FAHP. Appl Soft Comput. 2017;56:46–54. doi: 10.1016/j.asoc.2017.02.027
   Web of Science ®Google Scholar
• Onisawa T. An application of fuzzy concepts to modelling of reliability analysis. Fuzzy Sets Syst. 1990;37(3):267–286. doi: 10.1016/0165-0114(90)90026-3
   Web of Science ®Google Scholar
• Chen SJJ, Hwang CL. Fuzzy multiple attribute decision making: methods and applications. New York (NY): Springer; 1992. Chapter 5, Fuzzy multiple attribute decision making methods; p. 289–450.
   Google Scholar
• Vahdani B, Mousavi SM, Tavakkoli-Moghaddam R. Group decision making based on novel fuzzy modified TOPSIS method. Appl Math Model. 2011;35:4257–4269. doi: 10.1016/j.apm.2011.02.040
   Web of Science ®Google Scholar
• Iranian Offshore Oil Company. Moarrefie sherkate nafte daryayi Irani [Introduction to Iranian Offshore Oil Company (IOOC)]. Kharg Island: Kharg Island Publication Center; 2015. (KII publication; no. 1393-0021). Persian.
   Google Scholar
• Chang WL, Pang LM, Tay KM. Application of self-organizing map to failure modes and effects analysis methodology. Neurocomputing. 2017;249:314–320. doi: 10.1016/j.neucom.2016.04.073
   Web of Science ®Google Scholar