Quantification of human error rates using a SLIM-based approach

The authors present an application of the success likelihood index methodology (SLIM) for quantifying dynamic scenario-related human actions for use in PRA (probabilistic risk assessment). The application is structured to make the assumptions, bases, and calculations leading to the quantitative evaluation of human error rates under plant transient conditions both scrutable and useful for use in risk management. It provides a structure in which assessment teams of operators and PRA analysts can provide feedback on the problems operators face and a means to prioritize corrective action. The set of forms and instructions to explain and implement the procedure enables its consistent application on a long-term basis and provides the flexibility to update and add actions as additional insight into operator actions is gained.<>