Determining performance shaping factors to assess human error in the emergency response team in chemical process industries: a case study

References

• Eyvazlou M, Dadashpour Ahangar A, Rahimi A, et al. Human reliability assessment in a 99Mo/99mTc generator production facility using the standardized plant analysis risk–human (SPAR-H) technique. Int J Occup Saf Ergon. 2019;25(2):321–330. doi:10.1080/10803548.2017.1415832
   PubMed Web of Science ®Google Scholar
• Pan X, Wu Z. Performance shaping factors in the human error probability modification of human reliability analysis. Int J Occup Saf Ergon. 2020;26(3):538–550. doi:10.1080/10803548.2018.1498655
   PubMed Web of Science ®Google Scholar
• Blackman HS, Gertman DI, Boring RL. Human error quantification using performance shaping factors in the SPAR-H method. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting; Published September 1, 2008. Los Angeles (CA): SAGE.
   Google Scholar
• Lees F. Lees’ loss prevention in the process industries: hazard identification, assessment and control. Texas A&M University, Texas:  USA: Butterworth-Heinemann; 2012.
   Google Scholar
• Sujan MA, Embrey D, Huang H. On the application of human reliability analysis in healthcare: opportunities and challenges. Reliab Eng Syst Saf. 2020;194:106189. doi:10.1016/j.ress.2018.06.017
   Web of Science ®Google Scholar
• Aghaei H, Mirzaei Aliabadi M, Mollabahrami F, et al. Human reliability analysis in de-energization of power line using HEART in the context of Z-numbers. Plos One. 2021;16(7):e0253827. doi:10.1371/journal.pone.0253827
   PubMed Web of Science ®Google Scholar
• Zarei E, Khan F, Abbassi R. Importance of human reliability in process operation: a critical analysis. Reliab Eng Syst Saf. 2021;211:107607. doi:10.1016/j.ress.2021.107607
   Web of Science ®Google Scholar
• Rooney JJ, Heuvel LNV, Lorenzo DK. Reduce human error. Qual Prog. 2002;35(9):27–36.
   Google Scholar
• Whittingham R. The blame machine: why human error causes accidents. London: Routledge; 2004.
   Google Scholar
• Kim JW, Jung W. A taxonomy of performance influencing factors for human reliability analysis of emergency tasks. J Loss Prev Process Indus. 2003;16(6):479–495. doi:10.1016/S0950-4230(03)00075-5
   Web of Science ®Google Scholar
• Kirwan B. A guide to practical human reliability assessment. London:  CRC Press; 2017.
   Google Scholar
• Pan X, Lin Y, He C. A review of cognitive models in human reliability analysis. Qual Reliab Eng Int. 2017;33(7):1299–1316. doi:10.1002/qre.2111
   Web of Science ®Google Scholar
• Petrillo A, Falcone D, De Felice F, et al. Development of a risk analysis model to evaluate human error in industrial plants and in critical infrastructures. Int J Disaster Risk Reduction. 2017;23:15–24. doi:10.1016/j.ijdrr.2017.03.012
   Web of Science ®Google Scholar
• Flin R., Arjen B, Uri R, et al. Decision making in crises: the Piper Alpha disaster. In: Managing crises: Threats, dilemmas, opportunities, United States, Charles C Thomas. 2001. p. 103–118.
   Google Scholar
• Alkhaldi M, Pathirage C, Kulatunga U. The role of human error in accidents within oil and gas industry in Bahrain. In: 13th International Postgraduate Research Conference (IPGRC): conference proceedings. University of Salford, UK; 14-15 September 2017.
   Google Scholar
• Wears RL, Leape LL. Human error in emergency medicine. Ann Emergency Med. 1999;34(3):370–372. doi:10.1016/S0196-0644(99)70133-2
   PubMed Web of Science ®Google Scholar
• Paltrinieri N, Massaiu S, Matteini A. Human reliability analysis in the petroleum industry: tutorial and examples. In: Dynamic risk analysis in the chemical and petroleum industry. Elsevier; 2016. p. 181–192. doi:10.1016/B978-0-12-803765-2.00015-9
   Google Scholar
• Laumann K, Rasmussen M. Suggested improvements to the definitions of standardized plant analysis of risk–human reliability analysis (SPAR-H) performance shaping factors,: their levels and multipliers and the nominal tasks. Reliab Eng Syst Saf. 2016;145:287–300. doi:10.1016/j.ress.2015.07.022
   Web of Science ®Google Scholar
• Li J, Yu M, Wang H. A taxonomy of performance shaping factors for shield tunnel construction. Eng Construct Architectural Manage. 2018;25(4)):574–596.
   Web of Science ®Google Scholar
• Franciosi C, Di Pasquale V, Iannone R, et al. A taxonomy of performance shaping factors for human reliability analysis in industrial maintenance. J Indus Eng Manage. 2019;12(1):115–132. doi:10.3926/jiem.2702
   Google Scholar
• Kyriakidis M, Majumdar A, Ochieng WY. Data based framework to identify the most significant performance shaping factors in railway operations. Safety Science. 2015;78:60–76. doi:10.1016/j.ssci.2015.04.010
   Web of Science ®Google Scholar
• Khan FI, Amyotte PR, DiMattia DG. HEPI: a new tool for human error probability calculation for offshore operation. Saf Sci. 2006;44(4):313–334. doi:10.1016/j.ssci.2005.10.008
   Web of Science ®Google Scholar
• Amesz J. Trend and pattern analyses of operational data from nuclear power plants. Vol. 22. Luxembourg : Commission of the European Communities; 1990.
   Google Scholar
• Whalley S. Minimising the cause of human error National Centre of Systems Reliability, Culcheth, Warrington, Cheshire, UK10th Advances in Reliability Technology Symposium. Springer; 1988.
   Google Scholar
• Boring RL. How many performance shaping factors are necessary for human reliability analysis?. Idaho falls, USA: Idaho National Laboratory (INL); 2010.
   Google Scholar
• Gibson W.. 1998. Development of the CORE-DATA database in collection and classification of human reliability data for use in probabilistic safety assessments. Int Atomic Energy Assoc. 
   Google Scholar
• Groth K, Mosleh A. A data-informed model of performance shaping factors and their interdependencies for use in human reliability analysis. In: Reliability, risk and safety, three volume set. London: CRC Press; 2009;3:265–272.
   Google Scholar
• Macwan A, Mosleh A. A methodology for modeling operator errors of commission in probabilistic risk assessment. Reliability Engineering & System Safety. 1994;45(1–2):139–157. doi:10.1016/0951-8320(94)90082-5
   Web of Science ®Google Scholar
• Gerdes VGJ. Identification and analysis of cognitive errors: application to control room operators. 1998.
   Google Scholar
• Kirwan B, Basra G, Taylor-Adams S. CORE-DATA: a computerised human error database for human reliability support. Orlando, FL, USA. Proceedings of the 1997 IEEE Sixth Conference on Human Factors and Power Plants. Global perspectives of human factors in power generation. IEEE; 8-13 June1997.
   Google Scholar
• Dhillon B, Liu Y. Human error in maintenance: a review. J Qual Maintenance Eng. 2006;12:21–36. https://doi.org/10.1108/13552510610654510. Emerald Group Publishing Limited.
   Google Scholar
• Deaconu A, Raşcă L. Human Error and Organizational Management. Economics and Applied Informatics. 2009;1(2):147–154.
   Google Scholar
• Kirwan B. Human error identification in human reliability assessment. Part 1: overview of approaches. Appl Ergon. 1992;23(5):299–318. doi:10.1016/0003-6870(92)90292-4
   PubMed Web of Science ®Google Scholar
• Gertman DI, Blackman HS, Haney LN, et al. INTENT: a method for estimating human error probabilities for decision-based errors. Reliability Engineering & System Safety. 1992;35(2):127–136. doi:10.1016/0951-8320(92)90032-G
   Web of Science ®Google Scholar
• Cooper SE, Ramey-Smith A, Wreathall J, et al. A technique for human error analysis (ATHEANA). Nuclear Regulatory Commission; 1996.
   Google Scholar
• Kontogiannis T. A framework for the analysis of cognitive reliability in complex systems: a recovery centred approach. Reliab Eng Syst Saf. 1997;58(3):233–248. doi:10.1016/S0951-8320(97)00078-1
   Web of Science ®Google Scholar
• Gertman D, Blackman H, Marble J, et al. The SPAR-H human reliability analysis method. US Nucl Regul Commission. 2005;230(4):35.
   Google Scholar
• Julius J, Jorgenson E, Parry G, et al. A procedure for the analysis of errors of commission in a probabilistic safety assessment of a nuclear power plant at full power. Reliab Eng Syst Saf. 1995;50(2):189–201. doi:10.1016/0951-8320(95)00075-D
   Web of Science ®Google Scholar
• Kalatpour O, Farhadi S. The content analysis of emergency scenarios: thematic survey of the context in the process industries. Safety Science. 2017;92:257–261. doi:10.1016/j.ssci.2016.11.004
   Web of Science ®Google Scholar
• Adler M, Ziglio E. Gazing into the oracle: the Delphi method and its application to social policy and public health. United Kingdom: Jessica Kingsley; 1996.
   Google Scholar
• Roy TK, Garai A.. Intuitionistic Fuzzy Delphi Method: More realistic and interactive forecasting tool. Notes on IFS. 2012;18(2):37–50.
   Google Scholar
• [39-42].
   Google Scholar
• Chang P-L, Hsu C-W, Chang P-C. Fuzzy Delphi method for evaluating hydrogen production technologies. Int J Hydrogen Energy. 2011;36(21):14172–14179. doi:10.1016/j.ijhydene.2011.05.045
   Web of Science ®Google Scholar
• Weir JP. Quantifying test–retest reliability using the intraclass correlation coefficient and the SEM. J Strength Conditioning Res. 2005;19(1):231–240.
   PubMed Web of Science ®Google Scholar
• Almanasreh E, Moles R, Chen TF. Evaluation of methods used for estimating content validity. Res Social Admin Pharm. 2019;15(2):214–221. doi:10.1016/j.sapharm.2018.03.066
   PubMed Web of Science ®Google Scholar
• Bevilacqua M, Ciarapica FE. Human factor risk management in the process industry: a case study. Reliab Eng Syst Saf. 2018;169:149–159. doi:10.1016/j.ress.2017.08.013
   Web of Science ®Google Scholar
• Bell J, Holroyd J. Review of human reliability assessment methods: prepared by the Health and Safety Laboratory for the Health and Safety Executive 2009 [Internet]; 2009. (Research Report 679). Available from: http://www.hse.gov.uk/research/rrpdf/rr679.pdf
   Google Scholar
• Griffith CD, Mahadevan S. Human reliability under sleep deprivation: derivation of performance shaping factor multipliers from empirical data. Reliabil Eng Syst Saf. 2015;144:23–34. doi:10.1016/j.ress.2015.05.004
   Web of Science ®Google Scholar
• Lee SW, Kim AR, Ha JS, et al. Development of a qualitative evaluation framework for performance shaping factors (PSFs) in advanced MCR HRA. Ann Nucl Energy. 2011;38(8):1751–1759. doi:10.1016/j.anucene.2011.04.006
   Web of Science ®Google Scholar
• Wang L, Wang Y, Cao Q, et al. A framework for human error risk analysis of coal mine emergency evacuation in China. J Loss Prev Process Indus. 2014;30:113–123. doi:10.1016/j.jlp.2014.05.007
   Web of Science ®Google Scholar
• Abbassinia M, Kalatpour O, Motamedzade M, et al. Dynamic human error assessment in emergency using fuzzy Bayesian CREAM. J Res Health Sci. 2020;20(1):e00468. doi:10.34172/jrhs.2020.03
   PubMed Web of Science ®Google Scholar
• Boring RL. Fifty years of THERP and human reliability analysis. Idaho Falls, ID (United States): Idaho National Laboratory (INL); 2012.
   Google Scholar
• Embrey D, Humphreys P, Rosa E, et al. SLIM-MAUD: an approach to assessing human error probabilities using structured expert judgment. Volume I. Overview of SLIM-MAUD. Upton (NY): Brookhaven National Lab.; 1984.
   Google Scholar
• DiMattia DG, Khan FI, Amyotte PR. Determination of human error probabilities for offshore platform musters. Journal of Loss Prevention in the Process Industries. 2005;18(4–6):488–501. doi:10.1016/j.jlp.2005.07.021
   Web of Science ®Google Scholar
• Diaconeasa M, Mosleh A. Branching rules and quantification based on human behavior in the ADS-IDAC dynamic PRA platform. In: Safety and reliability – safe societies in a changing world. 1. London: CRC Press; 2018. p. 1749–1756.
   Google Scholar
• Groth K, Mosleh A. A performance shaping factors causal model for nuclear power plant human reliability analysis. In: College Park, MD, USA.10th International Probabilistic Safety Assessment and Management Conference; 2010.
   Google Scholar
• Rasmussen M, Standal MI, Laumann K. Task complexity as a performance shaping factor: a review and recommendations in standardized plant analysis risk–human reliability analysis (SPAR-H) adaption. Saf Sci. 2015;76:228–238. doi:10.1016/j.ssci.2015.03.005
   Web of Science ®Google Scholar
• Musharraf M. Bayesian network approach to human reliability analysis (HRA) at offshore operations. Memorial University of Newfoundland; 2014.
   Google Scholar
• Boring RL, Blackman HS. The origins of the SPAR-H method’s performance shaping factor multipliers, 26-31 Aug. Monterey, CA, USA. 2007 IEEE 8th Human Factors and Power Plants and HPRCT 13th Annual Meeting. IEEE; 2007.
   Google Scholar
• Bercha FG, Brooks CJ, Leafloor F. Human performance in Arctic offshore escape , evacuation, and rescue. May 2003; Honolulu, Hawaii, USAThe Thirteenth International Offshore and Polar Engineering Conference. OnePetro; 2003.
   Google Scholar
• Luciano M, Huhtaniemi IT. Encyclopedia of endocrine diseases. 2nd ed. Michigan, USA: Academic Press; 2018.
   Google Scholar
• Liu W-K. Application of the fuzzy Delphi method and the fuzzy analytic hierarchy process for the managerial competence of multinational corporation executives. Int J e-Educ, e-Business, e-Manage e-Learn. 2013;3(4):313.
   Google Scholar
• Park J, Jung W, Kim J. Inter-relationships between performance shaping factors for human reliability analysis of nuclear power plants. Nucl Eng Technol. 2020;52(1):87–100. doi:10.1016/j.net.2019.07.004
   Web of Science ®Google Scholar
• Mahdinia M, Mohammadfam I, Mirzaei Aliabadi M, et al. The mediating effect of workers’ situation awareness on the relationship between work-related factors and human error: a path analysis approach. Int J Occup Saf Ergon. 2021;27:1–9.
   PubMedGoogle Scholar
• Boring RL, Griffith CD, Joe JC. The measure of human error: direct and indirect performance shaping factors. In: 26-31 Aug. 2007Monterey, CA, USA IEEE 8th Human Factors and Power Plants and HPRCT 13th Annual Meeting. IEEE; 2007.
   Google Scholar
• Kovacevic S, Papic L, Janackovic G, et al. The analysis of human error as causes in the maintenance of machines: a case study in mining companies. South Afr J Indus Eng. 2016;27(4):193–202. doi:10.7166/27-4-1493
   Web of Science ®Google Scholar
• Farhadi S, Mohammadfam I, Kalatpur O. Introducing a pattern for developing emergency scenarios in industries and studying the conformity of the exercised scenarios in the process industries with the presented pattern. Iran Occup Health. 2017;14(2):72–81.
   Google Scholar
• Waterson P, Le Coze J-C, Andersen HB. Recurring themes in the legacy of Jens Rasmussen. Appl Ergon. 2017;59(Pt B):471–482. doi:10.1016/j.apergo.2016.10.002
   PubMedGoogle Scholar
• Sugimoto F, Toyabe T, Sato A. An analysis of human error in skill task and visual recognition under auditory interruption. In: 12-15 Oct. 1997, Orlando, FL, USA IEEE  ,International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation. IEEE; 1997.
   Google Scholar
• Lindell MK, Perry RW, Prater C, et al. Fundamentals of emergency management. Washington (DC): FEMA; 2006.
   Google Scholar
• Bubb H. Human reliability: a key to improved quality in manufacturing. Human Factors Ergon Manuf Serv Indus. 2005;15(4):353–368. doi:10.1002/hfm.20032
   Google Scholar
• Kim JW, Jung W, Ha J. AGAPE-ET: a methodology for human error analysis of emergency tasks. Risk Anal Int J. 2004;24(5):1261–1277. doi:10.1111/j.0272-4332.2004.00524.x
   PubMed Web of Science ®Google Scholar
• Mohammadfam I, Bastani S, Esaghi M, et al. Evaluation of coordination of emergency response team through the social network analysis. Case study: oil and gas refinery. Saf Health Work. 2015;6(1):30–34. doi:10.1016/j.shaw.2014.09.004
   PubMed Web of Science ®Google Scholar
• Soomaroo L, Murray V. Weather and environmental hazards at mass gatherings. PLoS Currents. 2012;4:1–13. https://doi.org/10.1371/4fca9ee30afc4.
   Google Scholar
• Haghani A, Yang S. Real-time emergency response fleet deployment: concepts, systems, simulation & case studies. Dynamic fleet management. Vol. 38. Boston, MA: Springer; 2007. p. 133–162.
   Google Scholar
• Sattler DN, Kaiser CF, Hittner JB. Disaster preparedness: relationships among prior experience, personal characteristics, and distress 1. J Appl Social Psychol. 2000;30(7):1396–1420. doi:10.1111/j.1559-1816.2000.tb02527.x
   Web of Science ®Google Scholar
• Mahdinia M, Mohammadfam I, Soltanzadeh A, et al. A fuzzy-BN DEMATEL model for predicting safety behavior. Int J Occup Saf Ergon. 2021. (just-accepted):1–25. https://doi.org/10.1080/10803548.2021.2015741.
   Google Scholar
• Liu Y, Fan Z-P, Yuan Y, et al. A FTA-based method for risk decision-making in emergency response. Comp Oper Res. 2014;42:49–57. doi:10.1016/j.cor.2012.08.015
   PubMed Web of Science ®Google Scholar
• Nassereddine M, Azar A, Rajabzadeh A, et al. Decision making application in collaborative emergency response: a new PROMETHEE preference function. Int J Disaster Risk Reduc. 2019;38:101221. doi:10.1016/j.ijdrr.2019.101221
   Web of Science ®Google Scholar
• Sneddon A, Mearns K, Flin R. Situation awareness and safety in offshore drill crews. Cogn Technol Work. 2006;8(4):255–267. doi:10.1007/s10111-006-0040-1
   Google Scholar
• French S, Bedford T, Pollard SJ, et al. Human reliability analysis: a critique and review for managers. Saf Sci. 2011;49(6):753–763. doi:10.1016/j.ssci.2011.02.008
   Web of Science ®Google Scholar
• Ghasemi F, Ghasemi A, Kalatpour O. Prediction of human error probability during the hydrocarbon road tanker loading operation using a hybrid technique of fuzzy sets: Bayesian network and CREAM. Int J Occup Saf Ergon. 2021: 1–11. https://doi.org/10.1080/10803548.2021.1889877.
   Google Scholar