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In the new inspection regime (NIR) of port state control (PSC), the criteria for being judged as a standard risk ship (SRS) is too broad. Some ships are classified as SRS even though they have a large number of ship deficiencies. This paper develops a selection system to identify the hidden risk of target ships in the SRS category using PSC inspection records. This system allows the target ship to be used to help reduce cases of flags being greylisted or blacklisted, which can cause huge shipping losses. This study analyzes ship deficiency data in the Tokyo memorandum of understanding (Tokyo MoU) database. It adopts the multiple criteria decision making (MCDM) model as a data processing technique to build a risk assessment scale. It uses fuzzy importance performance analysis (F-IPA) and technology for order preference by similarity to the ideal solution (TOPSIS) for its analysis. Subsequently, the weights of F-IPA and TOPSIS are adopted into the MCDM model. This article also consulted the Tokyo MoU database. It has been verified that the next time PSC inspection, the system hits 83.3% of the hidden risk ships in the SRS category. Thus, this system will help inspectors be more insightful for target ships.

Ship Deficiency Data of Port State Control to Identify Hidden Risk of Target Ship