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

@article{Hamada2004AFB,
  title={A fully Bayesian approach for combining multilevel failure information in fault tree quantification and optimal follow-on resource allocation},
  author={Michael S. Hamada and Harry F. Martz and C. Shane Reese and Todd L. Graves and Val Johnson and Alyson G. Wilson},
  journal={Rel. Eng. & Sys. Safety},
  year={2004},
  volume={86},
  pages={297-305}
}
Abstract 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… CONTINUE READING

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