Share This Article:

Comparing SLIM, SPAR-H and Bayesian Network Methodologies

Abstract Full-Text HTML Download Download as PDF (Size:334KB) PP. 31-41
DOI: 10.4236/ojsst.2013.32004    5,034 Downloads   7,452 Views   Citations

ABSTRACT

Human factors always affect maintenance performance, and in some cases, it’s critical to systems availability and reliability. Despite such importance, in so many cases, there’s no human reliability method applied to analyze maintenance tasks in order to understand better human factors influence in maintenance performance. There are several human analysis methodologies and regarding human factors, SLIM (Successes Likelihood Methods), SPAR-H (Standardized Plant Analysis Risk-Human Reliability Analysis Method) and Bayesian Net take into account such factors and may be a good approach to minimize human error. In order to propose a human reliability methodology to analyze maintenance tasks taking into account human factors, a case study about turbine star up tasks will be carried out. Therefore, different human reliability methods will be performed based on specialist opinion. Finally, the human error probability as well as drawbacks and advantages from different methods will be discussed to get a final conclusion.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

E. Calixto, G. Lima and P. Firmino, "Comparing SLIM, SPAR-H and Bayesian Network Methodologies," Open Journal of Safety Science and Technology, Vol. 3 No. 2, 2013, pp. 31-41. doi: 10.4236/ojsst.2013.32004.

References

[1] A. D. Swain and H. E. Guttmann, “Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications,” Draft, NUREG/CR-1278, 1980.
[2] V. A. Silva, “O Planejamento de Emergências em Refinarias de Petróleo Brasileiras: Um Estudo dos Planos de Refinarias Brasileiras e uma Análise de Acidentes em Refinarias no Mundo e a Apresentação de uma Proposta de Relação de Canários Acidentais para Planejamento,” Dissertação (Mestrado em Sistemas de Gestão) Universidade Federal Fluminense, Niterói, 2003.
[3] L. J. Bellamy, T. A. W. Geyer and J. A. Astley, “Evaluation of the Human Contribution to Pipework and In-Line Equipment Failure Frequencies,” Health and Safety, London, 1989.
[4] M. Grozdanovic, “Usage of Human Reliability Quantification Methods,” International Journal of Occupational Safety and Ergonomics (JOSE), Vol. 11, No. 2, 2005, pp. 153-159.
[5] A. D. Swain and H. E. Guttmann, “Handbook of Human Reliability Analysis with Emphasis on Nuclear Power Plant Applications,” US Nuclear Regulatory Commission, Washington DC, 1983.
[6] “The SPAR-H Human. Reliability Analysis Method,” NUREG/CR-6883, INL/EXT-05-00509, Idaho National Laboratory, US Nuclear Regulatory Commission, Washington DC, 2005.
[7] D. E. Embrey, P. Humphreys, E. A. Rosa, B. Kirwan and K. Rea, “SLIM-MAUD: An Approach to Assessing Human Error Probabilities Using Structured Expert Judgment, Volume 2: Detailed Analysis of the Technical Issues,” NUREG/CR-3518, Brookhaven National Laboratory, Upton, 1984.
[8] R. da C. L. Menezes, “Uma Metodologia para Avaliação da Confiabilidade Humana em Atividades de Substituição de Cadeias de Isoladores em Linhas de Transmissão,” Dissertação de Mestrado, UFPE, Recife, 2005.
[9] K. B. Korb and A. E. Nicholson, “Bayesian Artificial Intelligence,” Chapman & Hall/CRC, Boca Raton, 2003.
[10] D. E. Lopez, “Análise da Confiabilidade Humana via Redes Bayesianas: Uma Aplicação à Manutenção de Linhas de Transmissão,” Produção, Vol. 17, No. 1, 2007, pp. 162-185. doi:10.1590/S0103-65132007000100012

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.