Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

Human Reliability Analysis (HRA) is an important part in safety assessment of a large complex system. Human Cognitive Reliability (HCR) model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time, which is widely used in HRA. In the application of this method, cognitive patterns of humans are required to be considered and classified, and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain. How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR. In this paper, a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR. First, an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns, and mapping them to fuzzy numbers and unit intervals. Second, based on the evaluation panel, different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments. Finally, the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory (DSET), and the fused results were applied to the HCR model to obtain the Human Error Probability (HEP). A case study was used to demonstrate the procedure and effectiveness of the proposed method.

Automated summary

This paper proposes a new model to handle uncertain information in HCR, aiming to improve the accuracy and applicability of HCR by constructing an evaluation panel and using the DSET theory.