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Abstract The shipping company or the operator determines the mode of operation of a ship. In the case of container ships, there may be various operating patterns employed to arrive at the destination within the stipulated time. In addition, depending on the influence of the ocean’s environmental conditions, the speed and the route can be changed. As the ship’s fuel oil consumption is closely related to its operational pattern, it is possible to identify the most economical operations by analyzing the operational patterns of the ships. The operational records of each shipping company are not usually disclosed, so it is necessary to estimate the operational characteristics from publicly available data such as the automatic identification system (AIS) data and ocean environment data. In this study, we developed a visualization program to analyze the AIS data and ocean environmental conditions together and propose two categories of applications for the operational analysis of container ships using maritime big data. The first category applications are the past operation analysis by tracking previous trajectories, and the second category applications are the speed pattern analysis by shipping companies and shipyards under harsh environmental conditions. Thus, the operational characteristics of container ships were evaluated using maritime big data.
Publication Date 2021-04-18
Role Corresponding Author
Category SCIE

Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Myeong-Jo Son, Jeong-Youl Lee, “Operational Analysis of Container Ships by Using Maritime Big Data”, Journal of Marine Science and Engineering, Vol. 9, No. 4, pp. 438: 1-21, 2021.04.18

https://doi.org/10.3390/jmse9040438


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    Nam-Kug Ku, Ju-Hwan Cha, Myung-Il Roh, Kyu-Yeul Lee, "A Tagline Proportional-Derivative Control Method for the Anti-Swing Motion of a Heavy Load Suspended by a Floating Crane in Waves", Journal of Engineering for the Maritime Environment, Vol. 227, No. 4, pp. 357-366, 2013.11.01

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    Myung-Il Roh, Kyu-Yeul Lee, "Generation of the Production Material Information of a Building Block and Simulation of the Block Erection for Computer-Aided Process Planning and Scheduling in Shipbuilding", International Journal of Production Research, Vol. 45, No. 20, pp. 4653-4683, 2007.10.01

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    Myung-Il Roh, Kyu-Yeul Lee, "Development of a 3D CAD System for Modeling Hull Structure at the Initial Ship Design Stage", Ships and Offshore Structures, Vol. 1, No. 2, pp. 135-151, 2006.04.01

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    Myung-Il Roh, Kyu-Yeul Lee, "An Initial Hull Structural Modeling System for Computer-Aided Process Planning in Shipbuilding", Advances In Engineering Software, Vol. 37, No. 7, pp. 457-476, 2006.07.01

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    Myung-Il Roh, Ju-Hwan Cha, "A Block Transportation Scheduling System Considering a Minimization of Travel Distance without Loading of and Interference between Multiple Transporters", International Journal of Production Research, Vol. 49, No. 11, pp. 3231-3250, 2011.06.01

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    Myung-Il Roh, "Determination of an Economical Shipping Route Considering the Effects of Sea State for Lower Fuel Consumption", International Journal of Naval Architecture and Ocean Engineering, Vol. 5, No. 2, pp. 246-262, 2013.06.01

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    Myung-Il Roh, "Block Layout Method in the Block Stockyard Based on the Genetic Algorithm", Ocean Systems Engineering, Vol. 2, No. 4, pp. 271-287, 2012.12.01

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    Min-Jae Oh, Taw-Wan Kim, Myung-Il Roh, "G1 Bezier Surface Interpolation with T-junctions at a 3-Valent Singular Vertex", Computer Aided Geometric Design, Vol. 67, pp. 79-95, 2018.12.01

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    Min-Jae Oh, Myung-Il Roh, Tae-Wan Kim, "Local T-spline Surface Skinning with Shape Preservation", Computer-Aided Design, Vol. 104, pp. 15-26, 2018.11.01

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    Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Se-Hyun Myung, "Big Data-based Piping Material Analysis Framework in Offshore Structure for Contract Design", Ocean Systems Engineering, Vol. 9, No. 1, pp. 79-95, 2019.01.01

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    Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Myeong-Jo Son, Jeong-Youl Lee, “Operational Analysis of Container Ships by Using Maritime Big Data”, Journal of Marine Science and Engineering, Vol. 9, No. 4, pp. 438: 1-21, 2021.04.18

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