Maritime transport is the backbone of the international trade, more than 80% of global freight transport is carried by ships on the seas. However, in a complex and high-risk environment at sea, substandard ships in maritime transport causes serious accidents and hence bring out many threats to the maritime industry. As a result, with the aim of detection and elimination the substandard ships, port state controls (PSC) have been developed to inspect the ships respect to their Ship Risk Profile (SRP). SRP helps to determine the ship's priority for PSC inspections through categorizing the ships in high risk, standard risk or low risk using various generic and historic parameters. In this study a new model is proposed to predict SRP by using fuzzy clustering analysis (FCA) and fuzzy rule-based classification system (FRBS) different from the standard calculation of the SRP in the PSC regimes. The proposed model is structured on five different parameters which are ship type, ship flag, ship age, deficiency number and detention. In the proposed model, to predict the SRP, 53788 ship inspection data belonging to the parameters has been analyzed gathered from the Paris MoU online database between the years of 2017 and 2020. The results obtained with the proposed approach help to identify the risk profile for the ship targeted at almost certain risk level. As a result of the study, it is aimed to provide decision supports for port state control (PSC) officers to detect the most appropriate/risky ship for the inspection.
In recent years, despite the technological advances, and increasing security measures in the maritime industry, it is observed that the effect of the human factor in the marine accidents has not changed. Most of the accidents occur in narrow canals, straits, rivers and entering port areas, resulting in environmental pollution, economical casualties and injury/loss of life. Pilotage is set compulsory in order to maintain safe passage at such confined waters. The purpose of this study is to investigate the effect of critical human factors on the potential ship accidents under pilotage operations. To explore the identified human factors, depth interviews and a questionnaire study were conducted with masters and pilots. The obtained data was analysed using DEMATEL (Decision Making Trial and Evaluation Laboratory) method to identify the most important and influential factors. The DEMATEL method is used to investigate interaction among human factors and to visualize them with help of causal-effect relation diagram. The results show that master experience, pilot experience and crew training are significant factors compared to other human risk factors. As a result of the findings of this research, it is also thought that improving the collaboration and communication between the master and the pilot will be effective in preventing the accidents.Moreover, understanding casual relations among human factors is important to prevent marine accidents. Furthermore, sensitivity analysis was performed for testing reliability of the experts' evaluation and being clear certainty of the main results/findings in the DEMATEL method. It is found that expert considerations to the casual relationship between human factors are objective and sufficient. The findings of this article provide a critical overview of the research literature on the development of preventive measures for policy makers, shipping companies and port authorities.
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