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- Title
Preventive Maintenance Topic Models for LNG Containment Systems of LNG Marine Carriers Using Dock Specifications.
- Authors
Youn, Ik-Hyun; Kim, Sung-Cheol
- Abstract
Featured Application: The proposed mathematical maintenance models may be directly applied by the maintenance managers of liquefied natural gas carrier (LNGC) fleets to establish a more reliable and safer LNGC cargo containment maintenance strategy. The proposed framework could also lead to the discovery of higher quality critical system maintenance topic models in various fields such as the construction and manufacturing industries. The high demand for liquefied natural gas (LNG) requires more LNG carriers (LNGCs) to be in operation. During transportation, there is a high risk due to the required extremely low temperatures and the explosive nature of LNG cargo. Moreover, when there is a lack of experience in operating old LNGCs, there is a serious concern regarding operational accidents. A systematic maintenance strategy, especially for LNG cargo containment systems, is crucial for maintaining safe LNG transportation at sea. The purpose of this study is to develop preventive LNG cargo containment system maintenance models by using LNGC dock specifications from LNGCs of various ages. The dock specifications from a conventional LNGC repairing dock were analyzed using natural language processing techniques in order to develop preventive maintenance models of the LNG cargo containment system. From these results, and by considering the ship's age, it was found that for young LNGCs, the priority for repair should focus on checking routine consumable spare parts by tank inspections, whereas for older LNGCs, the focus should be on tank condition maintenance rather than on other facilities. These results are expected to be useful in the development of a maintenance strategy of preventive LNG cargo containment systems in maritime LNG transportation.
- Subjects
MARITIME shipping; MAINTENANCE equipment; LIQUEFIED natural gas; TECHNICAL specifications; NATURAL language processing; DOCKS
- Publication
Applied Sciences (2076-3417), 2019, Vol 9, Issue 6, p1202
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app9061202