Study on Bayesian network evaluation method for human reliability analysis in ship control room

Reducing human error can improve the human-machine operation reliability of ship digital systems. Accurately evaluating the human reliability level of a ship’s digital system has an important impact on reducing the occurrence of human error. In this study, a method was developed to assess the human reliability of ship operators. First, this research constructed a human reliability model of a ship operator by analysing the correlation between the common performance conditions (CPCs) of the Cognitive Reliability and Error Analysis Methods (CREAM) method, and then constructed a Bayesian network model based on the constructed human reliability model. Second, the Delphi method was used to determine the conditional probability distribution of intermediate nodes in the Bayesian network model. A human reliability evaluation was performed based on the Bayesian network model. The validation results showed that the developed method was consistent with the results of the CREAM. This indicates the effectiveness of the developed method for evaluating the human reliability level. Therefore, the developed method can be used to assess the reliability of ship operators.