A PARAMETRIC MIXTURE-MODEL FOR COMMON-CAUSE FAILURE DATA

This paper introduces a statistical reliability model for common-cause failure data from the nuclear industry. To achieve target reliability , many components in power plants are placed in parallel systems. The benefits of redundancy can be negated if multiple component failures o ccur due to a common external event. To model the possibility of multi ple failures, a mixture-model based on the binomial failure-rate model is derived using reasonable assumptions of multiple failure events at a nuclear power plant (NPP). In many applications, the original binom ial failure-rate model fits failure data poorly, and the model has not typically been applied to probabilistic risk assessments in the nucle ar industry. This mixture-model fits better. This paper presents a lea st-squares solution to the mixture-model parameters, and the model fit is investigated. Methods developed here are motivated by, and illustr ated with, discrete failure data collected from several US NPP since a bout 1980.