Analyzing human error contributions to maritime environmental risk in oil/chemical tanker ship

References

• Afenyo M, Khan F, Veitch B, Yang M. 2017. A probabilistic ecological risk model for Arctic marine oil spills. J Environ Chem Eng. 5(2):1494–1503. doi:10.1016/j.jece.2017.02.021
   Web of Science ®Google Scholar
• Akyuz E. 2015. Quantification of human error probability towards the gas inerting process on-board crude oil tankers. Saf Sci. 80:77–86. doi:10.1016/j.ssci.2015.07.018
   Web of Science ®Google Scholar
• Akyuz E. 2017. A marine accident analysing model to evaluate potential operational causes in cargo ships. Saf Sci. 92:17–25. doi:10.1016/j.ssci.2016.09.010
   Web of Science ®Google Scholar
• Akyuz E, Arslan O, Turan O. 2020. Application of fuzzy logic to fault tree and event tree analysis of the risk for cargo liquefaction on board ship. Appl Ocean Res. 101:102238. doi:10.1016/j.apor.2020.102238
   Web of Science ®Google Scholar
• Akyuz E, Celik M. 2016. A hybrid human error probability determination approach: the case of cargo loading operation in oil/chemical tanker ship. J Loss Prev Process Ind. 43:424–431. doi:10.1016/j.jlp.2016.06.020
   Web of Science ®Google Scholar
• Akyuz E, Celik E. 2018a. A quantitative risk analysis by using interval type-2 fuzzy FMEA approach: the case of oil spill. Marit Policy Manage. 45(8):979–994. doi:10.1080/03088839.2018.1520401
   Web of Science ®Google Scholar
• Akyuz E, Celik E. 2018b. The role of human factor in maritime environment risk assessment: a practical application on Ballast Water Treatment (BWT) system in ship. Hum Ecol Risk Assess Int J. 24(3):653–666. doi:10.1080/10807039.2017.1396184
   Web of Science ®Google Scholar
• Antao P, Soares CG. 2006. Fault-tree models of accident scenarios of RoPax vessels. Int J Autom Comput. 3:107–116.
   Google Scholar
• Apostolakis GE, Bier VM, Mosleh A. 1988. A critique of recent models for human error rate assessment. Reliab Eng Syst Saf. 22(1-4):201–217. doi:10.1016/0951-8320(88)90074-9
   Web of Science ®Google Scholar
• Arici SS, Akyuz E, Arslan O. 2020. Application of fuzzy bow-tie risk analysis to maritime transportation: the case of ship collision during the STS operation. Ocean Eng. 217:107960. doi:10.1016/j.oceaneng.2020.107960
   Web of Science ®Google Scholar
• Arslan O. 2009. Quantitative evaluation of precautions on chemical tanker operations. Process Saf Environ Protect. 87(2):113–120. doi:10.1016/j.psep.2008.06.006
   Web of Science ®Google Scholar
• Arslan O, Er ID. 2008. SWOT analysis for safer carriage of bulk liquid chemicals in tankers. J Hazard Mater. 154(1-3):901–913. doi:10.1016/j.jhazmat.2007.10.113
   PubMed Web of Science ®Google Scholar
• Cheliyan A, Bhattacharyya S. 2018. Fuzzy fault tree analysis of oil and gas leakage in subsea production systems. J Ocean Eng Sci. 3(1):38–48. doi:10.1016/j.joes.2017.11.005
   Web of Science ®Google Scholar
• Fan S, Zhang J, Blanco-Davis E, Yang Z, Yan X. 2020. Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS. Ocean Eng. 210(107544):107544. doi:10.1016/j.oceaneng.2020.107544
   Google Scholar
• Graziano A, Teixeira AP, Soares CG. 2016. Classification of human errors in grounding and collision accidents using the TRACEr taxonomy. Saf Sci. 86:245–257. doi:10.1016/j.ssci.2016.02.026
   Web of Science ®Google Scholar
• Gul M, Ak MF, Guneri AF. 2017. Occupational health and safety risk assessment in hospitals: a case study using two-stage fuzzy multi-criteria approach. Hum Ecol Risk Assess Int J. 23(2):187–202. doi:10.1080/10807039.2016.1234363
   Web of Science ®Google Scholar
• He X, Wang Y, Shen Z, Huang X. 2008. A simplified CREAM prospective quantification process and its application. Reliab Eng Syst Saf. 93(2):298–306. doi:10.1016/j.ress.2006.10.026
   Web of Science ®Google Scholar
• Hollnagel E. 1993. Human reliability analysis: context and control. London: Academic Press.
   Google Scholar
• Hollnagel E. 1998. Cognitive reliability and error analysis method. Amsterdam: Elsevier.
   Google Scholar
• Hsu HM, Chen CT. 1994. Fuzzy hierarchical weight analysis model for multicriteria decision problem. J Chin Inst Ind Eng. 11(3):126–136.
   Google Scholar
• Hu J, Zhang L, Wang Q, Tian B. 2019. A structured hazard identification method of human error for shale gas fracturing operation. Hum Ecol Risk Assess Int J. 25(5):1189–1206. doi:10.1080/10807039.2018.1461008
   Web of Science ®Google Scholar
• IMO. 2020. International convention for the prevention of pollution from ships (MARPOL). London: IMO.
   Google Scholar
• Islam R, Abbassi R, Garaniya V, Khan FI. 2016. Determination of human error probabilities for the maintenance operations of marine engines. J Ship Prod Des. 32(04):226–234. doi:10.5957/jspd.2016.32.4.226
   Google Scholar
• Johannsdottir L, Cook D. 2019. Systemic risk of maritime-related oil spills viewed from an Arctic and insurance perspective. Ocean Coast Manage. 179:104853. doi:10.1016/j.ocecoaman.2019.104853
   Web of Science ®Google Scholar
• Khan FI, Abbasi SA. 2000. Analytical simulation and PROFAT II: a new methodology.
   Google Scholar
• Kuzu AC, Akyuz E, Arslan O. 2019. Application of fuzzy fault tree analysis (FFTA) to maritime industry: a risk analysing of ship mooring operation. Ocean Eng. 179:128–134. doi:10.1016/j.oceaneng.2019.03.029
   Web of Science ®Google Scholar
• Lavasani SM, Ramzali N, Sabzalipour F, Akyuz E. 2015. Utilisation of fuzzy fault tree analysis (FFTA) for quantified risk analysis of leakage in abandoned oil and natural-gas wells. Ocean Eng. 108:729–737. doi:10.1016/j.oceaneng.2015.09.008
   Web of Science ®Google Scholar
• Liang G-S, Wang M-JJ. 1993. Fuzzy fault-tree analysis using failure possibility. Microelectron Reliab. 33(4):583–597. doi:10.1016/0026-2714(93)90326-T
   Web of Science ®Google Scholar
• Marques WC, Stringari CE, Kirinus EP, Möller OO, Jr, Toldo EE, Jr, Andrade MM. 2017. Numerical modeling of the Tramandaí beach oil spill, Brazil—case study for January 2012 event. Appl Ocean Res. 65:178–191. doi:10.1016/j.apor.2017.04.007
   Web of Science ®Google Scholar
• Mukherjee S. 2019. Introduction to tectonics and structural geology: Indian context. Germany: Springer.
   Google Scholar
• Noroozi A, Khan F, MacKinnon S, Amyotte P, Deacon T. 2014. Determination of human error probabilities in maintenance procedures of a pump. Process Saf Environ Protect. 92(2):131–141. doi:10.1016/j.psep.2012.11.003
   Web of Science ®Google Scholar
• Onisawa T. 1990. An application of fuzzy concepts to modelling of reliability analysis. Fuzzy Set Syst. 37(3):267–286. doi:10.1016/0165-0114(90)90026-3
   Web of Science ®Google Scholar
• Rajakarunakaran S, Kumar AM, Prabhu VA. 2015. Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station. J Loss Prev Process Ind. 33:109–123. doi:10.1016/j.jlp.2014.11.016
   Web of Science ®Google Scholar
• Ramamoorthy S, Springthorpe S, Kushner D. 1977. Competition for mercury between river sediment and bacteria. Bull Environ Contam Toxicol. 17(5):505–511. doi:10.1007/BF01685971
   PubMed Web of Science ®Google Scholar
• Rozuhan H, Muhammad M, Niazi UM. 2020. Probabilistic risk assessment of offshore installation hydrocarbon releases leading to fire and explosion, incorporating system and human reliability analysis. Appl Ocean Res. 101(102282):102282. doi:10.1016/j.apor.2020.102282
   Google Scholar
• Şakar C, Zorba Y. 2017. A study on safety and risk assessment of dangerous cargo operations in oil/chemical tankers. J ETA Maritime Sci. 5(4):396–413. doi:10.5505/jems.2017.09226
   Google Scholar
• Salihoglu E, Beşikçi EB. 2021. The use of functional resonance analysis method (FRAM) in a maritime accident: a case study of Prestige. Ocean Eng. 219:108223. doi:10.1016/j.oceaneng.2020.108223
   Web of Science ®Google Scholar
• Sarıalioğlu S, Uğurlu Ö, Aydın M, Vardar B, Wang J. 2020. A hybrid model for human-factor analysis of engine-room fires on ships: HFACS-PV&FFTA. Ocean Eng. 217:107992. doi:10.1016/j.oceaneng.2020.107992
   Web of Science ®Google Scholar
• Shafiee M, Enjema E, Kolios A. 2019. An integrated FTA-FMEA model for risk analysis of engineering systems: a case study of subsea blowout preventers. Appl Sci. 9(6):1192. doi:10.3390/app9061192
   Google Scholar
• Sormunen O-VE, Goerlandt F, Häkkinen J, Posti A, Hänninen M, Montewka J, Ståhlberg K, Kujala P. 2015. Uncertainty in maritime risk analysis: extended case study on chemical tanker collisions. Proc IMECHE. 229(3):303–320. doi:10.1177/1475090213515640
   Web of Science ®Google Scholar
• Sugeno M. 1985. Industrial applications of fuzzy control. Netherland: Elsevier Science Inc.
   Google Scholar
• Trucco P, Cagno E, Ruggeri F, Grande O. 2008. A Bayesian belief network modelling of organisational factors in risk analysis: a case study in maritime transportation. Reliab Eng Syst Saf. 93(6):845–856. doi:10.1016/j.ress.2007.03.035
   Web of Science ®Google Scholar
• Ung ST. 2019. Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian network based CREAM. Ocean Eng. 179:159–172. doi:10.1016/j.oceaneng.2019.03.031
   Web of Science ®Google Scholar
• Walker K, Macrae D, Ronald P. 2008. Carriage of Drilling Fluids and Brines-Implications for the Offshore Industry. Paper presented at: SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production. Society of Petroleum Engineers, Nice, France. doi:10.2118/111978-MS
   Google Scholar
• Wang J, Wang F, Chen S, Wang J, Hu L, Yin Y, Wu Y. 2016. Fault-tree-based instantaneous risk computing core in nuclear power plant risk monitor. Ann Nucl Energy. 95:35–41. doi:10.1016/j.anucene.2016.02.024
   Web of Science ®Google Scholar
• Wang W-J. 1997. New similarity measures on fuzzy sets and on elements. Fuzzy Set Syst. 85:305–309.
   Web of Science ®Google Scholar
• Wu B, Yan X, Wang Y, Soares CG. 2017. An evidential reasoning-based CREAM to human reliability analysis in maritime accident process. Risk Anal. 37(10):1936–1957. doi:10.1111/risa.12757
   PubMed Web of Science ®Google Scholar
• Xi YT, Yang ZL, Fang QG, Chen WJ, Wang J. 2017. A new hybrid approach to human error probability quantification–applications in maritime operations. Ocean Eng. 138:45–54. doi:10.1016/j.oceaneng.2017.04.018
   Web of Science ®Google Scholar
• Yang M, Khan FI, Lye L. 2013. Precursor-based hierarchical Bayesian approach for rare event frequency estimation: a case of oil spill accidents. Process Saf Environ Protect. 91(5):333–342. doi:10.1016/j.psep.2012.07.006
   Web of Science ®Google Scholar
• Yuhua D, Datao Y. 2005. Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis. J Loss Prev Process Ind. 18(2):83–88. doi:10.1016/j.jlp.2004.12.003
   Web of Science ®Google Scholar
• Zadeh LA. 1965. Fuzzy sets. Inf Contr. 8(3):338–353. doi:10.1016/S0019-9958(65)90241-X
   Google Scholar
• Zhou T, Wu C, Zhang J, Zhang D. 2017. Incorporating CREAM and MCS into fault tree analysis of LNG carrier spill accidents. Saf Sci. 96:183–191. doi:10.1016/j.ssci.2017.03.015
   Web of Science ®Google Scholar