Big data analysis of port state control ship detention database

Tsou, Ming-Cheng

doi:10.1080/20464177.2018.1505029

Cited by 57 publications

(33 citation statements)

References 7 publications

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“…Another important indicator of the maritime company performance refers to the number of detentions by the Port State Control (PSC) and to the deficiencies detected by the PSC surveys [8], [9]. Table 6 presents the data on the detected errors/ deficiencies during the PSC inspections.…”

Section: Discussion / Raspravamentioning

confidence: 99%

Accident Statistics and Key Performance Indicators in Marine Offshore Industry

2019

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Maritime transport is the backbone of the world trade. One of its segments refers to maritime offshore industry. These companies perform specific activities and tasks related to the exploitation of natural gas and oil from the sea subsoil, in addition to the wind power plants installed in marine environment. This study focuses on oil and gas offshore companies. Over the past decades this industry has been faced with responsible management requirements, which in practice implies the implementation of measures aiming at prevention of ecological damage to the marine and coastal environment and subsoil. The International Marine Contractors Association (IMCA) produces combined reports on offshore accidents and sets the excellence criteria based on statistical data. The companies comply with the responsible management principles which results in positive image within the industry and on the international market. This study has been based on accident reports for 264 offshore companies. Comparison of the average results in the observed group with the results of one selected offshore company has provided insights into deviations from the group average indicators. This has enabled an analysis of the causes of deviations at the selected company. In addition, the results have been studied from the standpoint of the sustainable growth and development of the company. Sažetak Pomorski promet okosnica je svjetske trgovine. Jedan dio odnosi se na odobalne pomorske kompanije. Ove kompanije obavljaju specijalizirane zadaće i aktivnosti povezane s eksploatacijom podmorja zemnim plinom i naftom ili vjetroelektrana koje se instaliraju u morskom okruženju. U ovom radu ciljana skupina upravo su odobalne pomorske kompanije za naftu i zemni plin. Posljednjih desetljeća ova je industrija izložena zahtjevima odgovornog poslovanja, što u praksi podrazumijeva implementaciju zaštitnih mjera za sprječavanje ekološke štete morskog te priobalnog okoliša i podmorja. Međunarodna pomorska udruga poduzetnika (engl. The International Marine Contractors Association-IMCA) izrađuje skupna izvješća o nezgodama za odobalne kompanije i na temelju statističkih podataka postavlja kriterije izvrsnosti. Kompanije prihvaćaju odgovorno poslovanje, a rezultat je pozitivan imidž u branši i na međunarodnom tržištu. U ovom radu istraživanje se temelji na podatcima o pomorskim nezgodama za 264 pomorske odobalne kompanije. Usporedbom prosječnih rezultata za promatranu skupinu kompanija s rezultatima (jedne) izabrane odobalne kompanije, došlo se do uvida o odstupanjima u odnosu na grupne pokazatelje. Shodno nalazu, istraženi su uzroci odstupanja kod promatrane odobalne pomorske kompanije. Isto je promatrano i sa stajališta održivog rasta i razvoja ove kompanije.

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Section: Discussion / Raspravamentioning

confidence: 99%

Accident Statistics and Key Performance Indicators in Marine Offshore Industry

2019

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“…Stimulated by those results, we conducted a correlation analysis on mining the historical PSC inspection data. The Apriori relevant models have been employed to identify the crucial ship deficiencies from different ship detention cases, indicating favorable ship deficiency recognition results [20,21]. In that manner, the Apriori model is considered as an efficient model to tackle the challenge of exploiting intrinsic ship deficiency categories from the historical PSC dataset.…”

Section: Model Developmentmentioning

confidence: 99%

Mining ship deficiency correlations from historical port state control (PSC) inspection data

Chen

et al. 2020

PLoS ONE

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Early warning on the ship deficiency is crucial for enhancing maritime safety, improving maritime traffic efficiency, reducing ship fuel consumption, etc. Previous studies focused on the ship deficiency exploration by mining the relationships between the ship physical deficiencies and the port state control (PSC) inspection results with statistical models. Less attention was paid to discovering the correlation rules among various parent ship deficiencies and subcategories. To address the issue, we proposed an improved Apriori model to explore the intrinsic mutual correlations among the ship deficiencies from the PSC inspection dataset. Four typical ship property indicators (i.e., ship type, age, deadweight and gross tonnage) were introduced to analyze the correlations for the ship parent deficiency categories and subcategories. The findings of our research can provide basic guidelines for PSC inspections to improve the ship inspection efficiency and maritime safety.

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“…In this work, the Apriori algorithm is used to identify the relationship between the deficiencies to provide the inspector with useful information in order to enhance the PSC inspection. A conceptually identical work, which utilised a similar method, was proposed by (Tsou 2019) where the author examined the relationships between the detention deficiencies with other factors. This valuable knowledge is important for enhancing the inspection performance by providing the inspector with a particular targeted ship.…”

Section: Literature Reviewmentioning

confidence: 99%

Association rule mining for identification of port state control patterns in Malaysian ports

Osman

Chen

Tian

et al. 2020

Maritime Policy & Management

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Port State Control (PSC) inspection data is used for determining the inspection pattern of PSC in Malaysia and identifying the relationship between the inspection place, flag state, number of deficiency, detention result, and ship risk profile. Based on 8,089 inspection reports from 2015 to 2019, the mining association rule is proposed as a learning approach due to its determination pattern in the information bank. The learning of association rules of PSC inspections is performed primarily on the Apriori Algorithm, in order to produce alluring rules. Inspection patterns of Malaysian ports revealed that flag state, ship risk profile, and inspection place generally lead to no detention result, as well as zero deficiency recorded on-board. The reported quantity of detention was significantly related to the high number of deficiencies raised for ships registered under blacklisted countries. Furthermore, the analysis of deficiency discovered the pattern of inspection at Malaysian ports is frequently related to zero and a low number of deficiencies raised by inspectors. Lastly, five major ports were selected for providing a useful rule to help PSC officers in organising an effective inspection plan. A similar approach can also be used for other ports beyond Malaysia for comparative analysis.

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Big data analysis of port state control ship detention database

Cited by 57 publications

References 7 publications

Accident Statistics and Key Performance Indicators in Marine Offshore Industry

Accident Statistics and Key Performance Indicators in Marine Offshore Industry

Mining ship deficiency correlations from historical port state control (PSC) inspection data

Association rule mining for identification of port state control patterns in Malaysian ports

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