Abstract
Accidents occur due to the release of hazard energy along a network of human factors (HF) until unwanted occurrences. To avoid the hazard energy to propagate, interventions are implemented in the project phase, based on the organizational and technological human elements. This paper presents a dynamic relationship of HF and an assessment of the barriers efficiency to avoid energy passage. The methodology involves analysis of the operational context, Bayesian Network and analysis of the hazard energy accumulated. The database of technological and operational information, management and operator’s discourse suggests a validated network with the results of the task and indicators of production and safety. By the application of this exercise, based on the real case of a chemical industry, hypothesis are suggested in relation to the HFs existing, which confirms the indirect probability of accidents and that disaster is almost impossible, although failures, deviations and low operational control are evident.
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References
Ashrafi, M., Anzabi Zadeh, S.: Lifecycle risk assessment of a technological system using dynamic Bayesian networks. Qual. Reliab. Eng. Int. 33 (2017). https://doi.org/10.1002/qre.2213
Lorenzo, D.K.: API770. A Manager’s Guide to Reducing Human Errors Improving Human Performance in the Process Industries. American Petroleum Institute, Inc. (2001)
Ávila, S.F.: Emergency decision model: accident analysis of history. In: 8th Center for Chemical Process Safety – CCPS. Universidad Católica Argentina (2018)
Ávila, S., Mrugalska, B., Ahumada, C., Ávila, J.: Relationship between human-managerial and social-organizational factors for industry safeguards project: dynamic bayesian networks. In: 22nd Annual International Symposium Mary Kay O’Connor Process Safety Center, College Station, Texas (2010)
Zhou, Q., Wong, Y., Loh, H.S., Yuen, K.F.: A fuzzy and Bayesian network CREAM model for human reliability analysis – the case of tanker shipping. Saf. Sci. 105, 149–157 (2018). https://doi.org/10.1016/j.ssci.2018.02.011
Blackman, D.G.H., Smith, J.M.J.B.: The SPAR-H Human Reliability Analysis Method. Idaho National Laboratory Battelle Energy Alliance Idaho Falls, ID 83415 (2005)
Boring, R., Blackman, H.: The origins of SPAR-H method’s performance shaping factors multipliers. Idaho – EUA, August 2007
Cerqueira, I., Drigo, E., Ávila, S., Gagliano, M.: C4t: safe behaviour performance tool. In: Karwowski, W., Trzcielinski, S., Mrugalska, B., Di Nicolantonio, M., Rossi, E. (eds.) Advances in Manufacturing, Production Management and Process Control. AHFE 2018. Advances in Intelligent Systems and Computing, vol. 793, pp. 343–353. Springer, Cham (2019)
Ávila, S., Mrugalska, B., Wyrwicka, M., Souza, M., Ávila, J., Cayres, E., Ávila, J.: Cognitive and organizational criteria for workstation design. In: 10th International Conference on Applied HFs and Ergonomics (AHFE) and the Affiliated Conferences, Washington D.C. Conference Proceedings Springer; International Conference on Applied HFs and Ergonomics (2019)
Jackson, L.A.J., Alt, J.K.: Bayesian Networks for the HE (2010)
Hollnagel, E.: A cognitive task analysis of the SGTR scenario. Final Draft. Version 1.0, November 1995
Mosleh, A., Groth, K.: Deriving causal Bayesian networks from human reliability analysis data: a methodology and example model. J. Risk Reliab. 226, 361–379 (2012). https://doi.org/10.1177/1748006x11428107
CCPS, Center for Chemical Process Safety: Guidelines for Investigating Chemical Process Incidents, 2nd edn. American Institute of Chemical Engineers, Wiley Inter-Science, New York (2003)
Reason, J.: Human Error. Cambridge University Press, Cambridge (2003)
Penkey, S.P., Siddiqui, N.A.: A review on accident pyramid and its empirical interpretation in oil & gas industry (upstream). Int. J. Sci. Res. Publ. 5(1), 1–3 (2015)
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Ávila, S., Ávila, J., Pereira, L., Lima, E.R.F. (2020). Dynamic View of Human Elements Design and Projection of Human Factors in Critical Task Operation Using Bayesian Networks. In: Mrugalska, B., Trzcielinski, S., Karwowski, W., Di Nicolantonio, M., Rossi, E. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1216. Springer, Cham. https://doi.org/10.1007/978-3-030-51981-0_25
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DOI: https://doi.org/10.1007/978-3-030-51981-0_25
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