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Abstract The arrangement design of the ship mainly depends on the previous mothership data or the experience of experts because there are various restrictions of the owner and the classification regulations. Therefore, it is difficult to select the optimal design by examining various alternatives. Accordingly, a method that can review and optimize various arrangement designs before construction is required. Digital twin technology is one of the methods by which alternatives can be considered before production by creating digital replicas of real physical entities. This study propose a method for designing an optimal arrangement that satisfies the requirements of the ship-owner and several design rules and implements the result as a virtual twin. In the arrangement design process, locations of partitions dividing compartments and locations of each equipment are set as design variables. Furthermore, as objective functions, building cost, stability, and the feasibility for expert knowledge are considered. Also, the arrangement designed during the optimization process can be reviewed by the designer in advance as if the arrangement is actually manufactured through virtual twin. The effectiveness of the method proposed in this study is verified by applying it to selecting the optimal arrangement design for an actual ship. In particular, it has a differentiated advantage from the existing arrangement design optimization method in that the designer can visually review the design first.
Publication Date 2022-10-10

Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of PRADS 2022, pp. 21, Dubrovnik, Croatia, 2022.10.09-13


  1. John-Kyu Hwang, Myung-Il Roh, Ju-Hwan Cha, "Design Modification of a Damaged Free-Fall Lifeboat for FPSO through the Free-Fall Test", Proceedings of ISOPE(International Society of Offshore and Polar Engineers) 2014, Busan, Korea, 2014.06.15-20

  2. John-Kyu Hwang, Myung-Il Roh, Ji-Hyun Hwang and Ju-Hwan Cha, Kyu-Yeul Lee, "Overview on Detailed Design and Construction of 2,000,000BBLS FPSO", Proceedings of Design & Construction of FPU(Floating Production Units) 2007, Suntec, Singapore, pp. 1-6, 2007.04.03

  3. John-Kyu Hwang, Geun-Jae Bang, Myung-Il Roh, Kyu-Yeul Lee, "Detailed Design and Construction of the Hull of an FPSO(Floating, Production, Storage, and Off-loading unit)", Proceedings of ISOPE 2009, Osaka, Japan, pp. 151-158, 2009.06.21-26

  4. Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Flooding Analysis of a Ship Using Surrogate Model by Deep Learning", Proceedings of the 31st Asian-Pacific TEAM 2017, Osaka, Japan, pp. 397-400, 2017.09.25-28

  5. Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Analysis Using Surrogate Model by Deep Learning and Application to Ship Flooding Analysis", Proceedings of ISCDE 2017, Ho Chi Minh, Vietnam, pp. 1-2, 2017.12.13-16

  6. No Image 17Dec
    by SyDLab
    in International Conference

    Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13

  7. Jisang Ha, Myung-Il Roh, Jong-Hyeok Lee, Jin-Hyeok Kim, Min-Chul Kong, Seung-Ho Ham, "Integrated Ship Remote Operating System Based on Digital Twin Technology", Proceedings of TEAM 2019, Tainan, Taiwan, pp. 106, 2019.10.14-17

  8. Jisang Ha, Myung-Il Roh, Hye-Won Lee, Jong-Ho Eun, Jong-Jin Park, Hyun-Joe Kim, "A Method of the Collision Avoidance of a Ship Using Real-time AIS Data", Proceedings of ACSMO 2020, Seoul, Korea, pp. 106, 2020.11.23-25

  9. Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, Min-Jae Oh, Sejin Oh, "Estimation Model of Hydrodynamic Performance Using Hull Form Variation and Deep Learning", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp.??, 2022.10.09-13

  10. Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, "Estimation of the Hydrodynamic Performance of the Parameterized Hull Forms Using Deep Learning", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10

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