Enhanced Bayesian THERP: Lessons learnt from HRA benchmarking
2010 (English)In: Proc. of PSAM 10 — International Probabilistic Safety Assessment & Management Conference, 7–11 June 2010, Seattle, Washington, USA, IAPSAM — International Association of Probabilistic Safety Assessment and Management, International Association for Probabilistic Safety Assessment and Managemen , 2010, 52- p.Conference paper (Refereed)
The Enhanced Bayesian THERP (Technique for Human Reliability Analysis) method usesas its basis the time-reliability curve introduced in the Swain’s human reliability analysis (HRA)handbook. It differs from the Swain's Handbook via a transparent adjustment of the time-dependenthuman error probabilities by use of five performance shaping factors (PSFs): (1) support fromprocedures, (2) support from training, (3) feedback from process, (4) need for co-ordination andcommunication, (5) mental load, decision burden. In order to better know the characteristics of theEnhanced Bayesian THERP from a more international perspective, the method has been subject toevaluation within the framework of the international “HRA Methods Empirical Study Using SimulatorData”. Without knowledge of the crews’ performances, several HRA analysis teams from differentcountries, using different methods, performed predictive analyses of four scenarios. This paper givesan overview of the method with major findings from the benchmarking. The empirical comparisongives confidence that the time reliability curve is a feasible and cost effective method to estimatehuman error probabilities when the time window is well defined and relatively short. The comparisonof empirical observations with predictions was found as a useful exercise to identify areas ofimprovements in the HRA method.
Place, publisher, year, edition, pages
International Association for Probabilistic Safety Assessment and Managemen , 2010. 52- p.
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:kth:diva-77622OAI: oai:DiVA.org:kth-77622DiVA: diva2:491858
PSAM 10 — International Probabilistic Safety Assessment & Management Conference
QC 201202072012-02-072012-02-072012-02-07Bibliographically approved