The increasing number of international maritime regulations has significantly impacted the workload of ship surveyors. As compliance requirements grow, surveyors face higher levels of stress, which can lead to human errors and missed deficiencies during inspections. This study explores the potential quality improvement in the survey process by evaluating alternatives for the survey checklist. Using he CREAM (HRA) method, human error classifications and influencing factors were analyzed to identify critical points in the inspection process. Quantifying the human errors in the survey process is done by the use of a python simulation. Besides, four error reduction techniques are implemented to find the potential quality improvement in ship surveys.