Assessment of Human Factor Performance Using Bayesian Inference and Inherent Safety

Abstract

Simply attributing incidents to human error is not adequate; human factors aspects should be investigated such that lessons are learnt and the true root causes are established in order to prevent recurrence. Whilst many petroleum and allied industry businesses have investigated and analyzed incidents – whether with major hazards or occupational injuries potential – human factors aspects are rarely addressed sufficiently. Therefore, this paper presents a hybrid methodology that combines a conventional Swiss Cheese model with Bayesian inference to predict the failure probability of human factors. An inherent safety concept associated with human factor is proposed and utilized as preventive measures to overcome the identified root causes. This approach is then applied to offshore safety assessment study. As a result, the failure probability of human factor can be monitored with time and the best preventive measure can be prioritized once human performance is degraded. It is proven that the approach has the ability to act as predictive tool that provides early warnings toward human deficiency. A preventive measure can then be taken to enhance the overall human performance and ultimately to reduce the likelihood of major incidents.