Applying the Cognitive Analysis of Reliability and Errors (CREAM) Model to Estimate the Probability of Human Error during Engine Room Fire Suppression Operations on Ships

Abstract

The present study aimed to apply the Cognitive Reliability and Error Analysis Method (CREAM) to estimate human error probability during ship engine room firefighting operations. The study was conducted in light of the increasing importance of human factors in critical maritime operations, particularly during emergency response to engine room fires. A descriptive analytical approach was adopted, in which firefighting procedures were decomposed into main and sub-tasks using Hierarchical Task Analysis (HTA), followed by evaluating the Common Performance Conditions (CPCs) affecting crew performance during firefighting operations. Both the Basic and Extended CREAM models were applied to identify cognitive control modes and estimate Human Error Probability (HEP) for different operational tasks during fire response procedures. The findings revealed significant variation in human error probability across the different stages of emergency response. Higher error probabilities were associated with tasks related to isolating the fire area, shutting down ventilation systems, crew coordination, and performing firefighting operations under time pressure and complex operational conditions. The results also demonstrated that communication quality, training level, and the availability of resources and equipment directly influence human performance efficiency during emergencies. Furthermore, the study confirmed that the CREAM model provides an effective framework for analyzing the relationship between human performance and operational context within high-risk maritime environments. It also assists in identifying the most error-prone tasks, thereby supporting the improvement of training programs and enhancing maritime safety and emergency response procedures onboard ships.