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Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H

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  • Groth, Katrina M.
  • Swiler, Laura P.

Abstract

The shortcomings of Human Reliability Analysis (HRA) have been a topic of discussion for over two decades. Repeated attempts to address these limitations have resulted in over 50 HRA methods, and the HRA research community continues to develop new methods. However, there remains a gap between the methods developed by HRA researchers and those actually used by HRA practitioners. Bayesian Networks (BNs) have become an increasingly popular part of the risk and reliability analysis framework over the past decade. BNs provide a framework for addressing many of the shortcomings of HRA from a researcher perspective and from a practitioner perspective. Several research groups have developed advanced HRA methods based on BNs, but none of these methods has been adopted by HRA practitioners in the U.S. nuclear power industry or at the U.S. Nuclear Regulatory Commission. In this paper we bridge the gap between HRA research and HRA practice by building a BN version of the widely used SPAR-H method. We demonstrate how the SPAR-H BN can be used by HRA practitioners, and we also demonstrate how it can be modified to incorporate data and information from research to advance HRA practice. The SPAR-H BN can be used as a starting point for translating HRA research efforts and advances in scientific understanding into real, timely benefits for HRA practitioners.

Suggested Citation

  • Groth, Katrina M. & Swiler, Laura P., 2013. "Bridging the gap between HRA research and HRA practice: A Bayesian network version of SPAR-H," Reliability Engineering and System Safety, Elsevier, vol. 115(C), pages 33-42.
    • Handle: RePEc:eee:reensy:v:115:y:2013:i:c:p:33-42
    DOI: 10.1016/j.ress.2013.02.015
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    References listed on IDEAS

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    1. Lu, Tsai-Ching & Druzdzel, Marek J., 2009. "Interactive construction of graphical decision models based on causal mechanisms," European Journal of Operational Research, Elsevier, vol. 199(3), pages 873-882, December.
    2. De Ambroggi, Massimiliano & Trucco, Paolo, 2011. "Modelling and assessment of dependent performance shaping factors through Analytic Network Process," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 849-860.
    3. Mohaghegh, Zahra & Kazemi, Reza & Mosleh, Ali, 2009. "Incorporating organizational factors into Probabilistic Risk Assessment (PRA) of complex socio-technical systems: A hybrid technique formalization," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 1000-1018.
    4. Katrina M Groth & Ali Mosleh, 2012. "Deriving causal Bayesian networks from human reliability analysis data: A methodology and example model," Journal of Risk and Reliability, , vol. 226(4), pages 361-379, August.
    5. Kim, Man Cheol & Seong, Poong Hyun & Hollnagel, Erik, 2006. "A probabilistic approach for determining the control mode in CREAM," Reliability Engineering and System Safety, Elsevier, vol. 91(2), pages 191-199.
    6. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    7. Groth, Katrina & Wang, Chengdong & Mosleh, Ali, 2010. "Hybrid causal methodology and software platform for probabilistic risk assessment and safety monitoring of socio-technical systems," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1276-1285.
    8. Groth, Katrina M. & Mosleh, Ali, 2012. "A data-informed PIF hierarchy for model-based Human Reliability Analysis," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 154-174.
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