Identifying ship deficiency patterns in port state control: an association rule mining-based analysis framework

Port state control (PSC) inspections are essential for identifying substandard ships, enhancing safety, protecting the marine environment, and safeguarding crew welfare. Yet, correlations between ship features and deficiencies remain underexplored. This study develops a deficiency analysis framework using the Apriori algorithm to mine association rules between ship particulars and deficiencies, as well as among deficiencies. Using Paris MoU data, the results reveal overlooked deficiency clusters and ship type–deficiency patterns. The framework supports more targeted high-risk ship selection, improves PSC efficiency, and contributes to predictive models, maritime digitalization, and smart port development.