The analysis of common cause failure based on impact vector considering human factor diversity

In the redundant system, Common Cause Failure (CCF) can result in failures of more than one module. Human Error is one of the most important causes among all the causes of CCF. Human factor diversity is an effective method against CCF due to human error. Although there is clear evidence that diversity can bring benefits, these benefits can be difficult to quantify. The current methods of human reliability analysis (HRA) almost never take into account the effect of human factor diversity on system reliability. Therefore a new method which can quantify the benefits of human factor diversity from the component degradation state point of view is proposed in this paper. The key idea of the new method is to build a fuzzy logic model based on an extended CREAM for the estimation of the probability of an erroneous human action which is then mapped into component degradation valve (CDV). The relationship between CCF rate and human factor diversity is studied by performing CCF analysis based on impact vectors which can be calculated from CDV. Finally, an illustrative example is presented, which shows the application process of the novel method.