Application of a CREAM based framework to assess human reliability in emergency response to engine room fires on ships

Abstract

For a human reliability assessment in the maritime domain, the main question is how we correctly understand the human factors in the maritime situation in a practical manner. This paper introduces a new approach based on Cognitive Reliability and Error Analysis Method (CREAM). The key to the method is to provide a framework for evaluating specific scenarios associated with maritime human errors and for conducting an assessment of the context, in which human actions take place. The output of the context assessment is, then, to be applied for the procedure assessment as model inputs for reflection of the context effect. The proposed approach can be divided into two parts: processing context assessment and modelling human error quantification. Fuzzy multiple attributive group decision-making method, Bayesian networks and evidential reasoning are employed for enhancing the reliability of human error quantification. Fuzzy conclusion of the context assessment is utilised by the model input in CREAM basic method and weighting factors in CREAM extended method respectively for considering human failure probability which varies depending on external conditions. This paper is expected to contribute to the improvement of safety by identifying frequently occurred human errors during the maritime operating for minimising of human failures.