Learning from accidents: Interactions between human factors, technology and organisations as a central element to validate risk studies

Safety Science - Tập 99 - Trang 196-214 - 2017
Raphael Moura1,2, Michael Beer3,1,4, Edoardo Patelli1, John Lewis1, Franz Knoll5
1Institute for Risk and Uncertainty, University of Liverpool, Chadwick Building, Peach Street, Liverpool L69 7ZF, United Kingdom
2National Agency for Petroleum, Natural Gas and Biofuels (ANP), Av. Rio Branco, 65, CEP: 20090-004, Centro, Rio de Janeiro, RJ, Brazil
3Institute for Risk and Reliability, Leibniz Universität Hannover, Callinstr. 34, 30167 Hannover, Germany
4Tongji University, Shanghai, China
5NCK Inc., 1200 Avenue McGill College, Montreal, Quebec H3B 4G7, Canada

Tài liệu tham khảo

Arstad, 2017, Managing major accident risk: concerns about complacency and complexity in practice, Safe. Sci., 91, 114, 10.1016/j.ssci.2016.08.004 Aven, 2013, On the meaning of the black swan concept in a risk context, Safe. Sci., 57, 44, 10.1016/j.ssci.2013.01.016 Aven, 2015, Implications of black swans to the foundations and practice of risk assessment and management, Reliab. Eng. Syst. Safe., 134, 83, 10.1016/j.ress.2014.10.004 Baysari, 2008, Understanding the human factors contribution to railway accidents and incidents in Australia, Accid. Anal. Prev., 40, 1750, 10.1016/j.aap.2008.06.013 Bellamy, 2007, Storybuilder—a tool for the analysis of accident reports, Reliab. Eng. Syst. Safe., 92, 735, 10.1016/j.ress.2006.02.010 Bellamy, 2013, Analysis of underlying causes of investigated loss of containment incidents in Dutch Seveso plants using the Storybuilder method, J. Loss Prev. Process Ind., 26, 1039, 10.1016/j.jlp.2013.03.009 Bills, 2009 Blajev, 2002 British Petroleum, 2010. Deepwater Horizon – Accident Investigation Report, 8 September 2010. Available from: <http://www.bp.com/content/dam/bp/pdf/sustainability/issue-reports/Deepwater_Horizon_Accident_Investigation_Report.pdf> (Accessed 25 September 2016). Bureau of Ocean Energy, Management, Regulation and Enforcement (BOMRE), 2011. Report regarding the causes of the April 20, 2010 Macondo well blowout. Available at: <https://www.bsee.gov/sites/bsee.gov/files/reports/blowout-prevention/dwhfinaldoi-volumeii.pdf> (Accessed 25 September 2016). Center for Catastrophic Risk Management (CCRM), 2011. Final Report on the Investigation of the Macondo Well Blowout. Available at: <http://ccrm.berkeley.edu/pdfs_papers/bea_pdfs/dhsgfinalreport-march2011-tag.pdf> (Accessed 25 September 2016). Cohen, 1972, A garbage-can model of organisational choice, Adm. Sci. Q., 17, 1, 10.2307/2392088 Cottrell, M., Olteanu, M., Rossi, F., Villa-Vialaneix, N., 2016. Theoretical and Applied Aspects of the Self-Organizing Maps. In: Proceedings of the 11th International Workshop WSOM 2016, Houston, Texas, USA, January 6–8, 2016. Cuny, 2003, Statistical modelling and risk assessment, Safe. Sci., 41, 29, 10.1016/S0925-7535(01)00056-X Davis, 1988 Doell, C., Held, P., Moura, R., Kruse, R., Beer, M., 2015. Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces. In: Proceedings of the International Probabilistic Workshop (IPW2015), Liverpool, UK, November 4–6, 2015. European Safety, Reliability and Data Association (ESReDA), 2015. Barriers to learning from incidents and accidents [Online]. Available from: <http://esreda.org/wp-content/uploads/2016/03/ESReDA-barriers-learning-accidents-1.pdf> (Accessed 25 September 2016). Evans, 2011, Fatal train accidents on Europe's railways: 1980–2009, Accid. Anal. Prev., 43, 391, 10.1016/j.aap.2010.09.009 Goerlandt, 2017, Validity and validation of safety-related quantitative risk analysis: a review, Safety Sci., 99, 127, 10.1016/j.ssci.2016.08.023 Grabowski, 1997, Risk mitigation in large-scale systems: lessons from high reliability organisations, Calif. Manage. Rev., 39, 152, 10.2307/41165914 Graeber, 1999 Heinrich, 1980 Hollnagel, 1998 Hollnagel, 2011 Hopkins, A., 2002. Working Paper 7 - Safety culture, mindfulness and safe behaviour: Converging ideas? National Research Centre for OHS Regulation. Available at: <http://regnet.anu.edu.au/sites/default/files/publications/attachments/2015-05/WorkingPaper_7_0.pdf> (Accessed on 15 February 2017). Hollywell, 1996, Incorporating human dependent failures in risk assessments to improve estimates of actual risk, Safe. Sci., 22, 177, 10.1016/0925-7535(96)00014-8 Kohonen, 2001 Kohonen, 2013, Essentials of the self-organizing map, Neural Networks, 37, 52, 10.1016/j.neunet.2012.09.018 La Porte, 1998, Theoretical and operational challenges of high reliability organisations: air traffic control and aircraft carriers, Int. J. Public Admin., 21, 847, 10.1080/01900699808525320 Leveson, 2004, A new accident model for engineering safer systems, Safe. Sci. J., 42, 237, 10.1016/S0925-7535(03)00047-X Leveson, 2011, Applying systems thinking to analyse and learn from events, Safe. Sci. J., 49, 55, 10.1016/j.ssci.2009.12.021 Leveson, 2012 Licu, 2007, Systemic Occurrence Analysis Methodology (SOAM) - a “Reason”-based organisational methodology for analysing incidents and accidents, Reliab. Eng. Syst. Safe., 92, 1162, 10.1016/j.ress.2006.08.010 McLaughlin, 2000 Moura, R., Beer, M., Patelli, E., Lewis, J., Knoll, F., 2015. Learning from Accidents: Analysis and Representation of Human Errors in Multi-attribute Events. In: Proceedings of the 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP12, Vancouver, Canada, July 12–15, 2015. Moura, R., Beer, M., Doell, C., Kruse, R. 2015. A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors. In: Proceedings of the 2015 IEEE Symposium Series on Computational Intelligence (SSCI2015), Cape Town, South Africa, December 8–10, 2015. Moura, 2016, Learning from major accidents to improve system design, Safe. Sci., 84, 37, 10.1016/j.ssci.2015.11.022 Moura, 2017, Learning from major accidents: graphical representation and analysis of multi-attribute events to enhance risk communication, Safe. Sci., 99, 58, 10.1016/j.ssci.2017.03.005 National Transportation Safety Board (NTSB), 2013. Crash Following Loss of Engine Power Due to Fuel Exhaustion, Air Methods Corporation, Eurocopter AS350 B2, N352LN, Near Mosby, Missouri, August 26, 2011. Aircraft Accident Report AAR-13/02. Washington, DC: NTSB. Nielsen, DS. 1971. The cause/consequence diagram method as a basis for quantitative accident analysis. Risø-M 1374. Paté-Cornell, 2012, On “Black Swans” and “Perfect Storms”: risk analysis and management when statistics are not enough, Risk Anal., 32, 1823, 10.1111/j.1539-6924.2011.01787.x Perrow, 1984 Rasmussen, 1997, Risk management in a dynamic society: a modelling problem, Safe. Sci., 27, 183, 10.1016/S0925-7535(97)00052-0 Reason, 1990 Reason, 1997 Roberts, 1990, Some characteristics of one type of high reliability organizations, Organ. Sci., 1, 160, 10.1287/orsc.1.2.160 Sagan, 1993 Shappell, 2007, Human Error and Commercial Aviation Accidents: an analysis using the human factors analysis and classification system, Hum. Factors, 49, 227, 10.1518/001872007X312469 Skogdalen, 2011, Quantitative risk analysis offshore - human and organizational factors, Reliab. Eng. Syst. Safe., 96, 468, 10.1016/j.ress.2010.12.013 Skogdalen, 2012, Quantitative risk analysis of oil and gas drilling, using Deepwater Horizon as case study, Reliab. Eng. Syst. Safe., 100, 58, 10.1016/j.ress.2011.12.002 Taleb, 2007 Ultsch, 1993, Self-organizing neural networks for visualization and classification, 307 United States Chemical Safety Board (US-CSB) United States Coast Guard (USCG) Zuijderduijn, C., 2000. Risk management by Shell Refinery/Chemicals at Pernis, The Netherlands. EU Joint Research Centre Conference on Seveso II Safety Cases, Athens.