A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation Academic Article uri icon


  • This paper presents a fully Bayesian approach that simultaneously combines non-overlapping (in time) basic event and higher-level event failure data in fault tree quantification. Such higher-level data often correspond to train, subsystem or system failure events. The fully Bayesian approach also automatically propagates the highest-level data to lower levels in the fault tree. A simple example illustrates our approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm. Published by Elsevier Ltd.

published proceedings

  • Reliability Engineering & System Safety

author list (cited authors)

  • Hamada, M., Martz, H. F., Reese, C. S., Graves, T., Johnson, V., & Wilson, A. G.

citation count

  • 89

complete list of authors

  • Hamada, M||Martz, HF||Reese, CS||Graves, T||Johnson, V||Wilson, AG

publication date

  • January 2004