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Abstract Piping systems are fundamental to a ship's operational infrastructure, supporting key functions such as fuel transfer, cooling, and waste management. Designing these systems requires navigating spatial constraints, ensuring compatibility with equipment connections, adhering to stringent regulations, and minimizing costs. Traditional manual approaches, reliant on Piping and Instrumentation Diagrams (P&IDs) and expert knowledge, are time-consuming and iterative. This study introduces an automated methodology for ship piping design that integrates historical data and quantified expert knowledge. Historical P&IDs and 3D piping models are analyzed to identify design patterns, offering practical guidance for new designs. Simultaneously, expert knowledge is transformed into a comprehensive evaluative framework, allowing for design optimization based on cost, construction feasibility, and operational efficiency. The proposed approach automates the generation of "go zones" and "grouping zones," enabling the application of routing algorithms to streamline the design process. The results are evaluated and visualized using Unity, ensuring effective verification and high-quality outcomes. This methodology significantly improves the efficiency and reliability of ship piping design by bridging traditional expertise with computational techniques. The integration of historical patterns and expert evaluations provides a robust, practical solution to the challenges of modern shipbuilding.
Publication Date 2025-06-25

Min-Chul Kong, Myung-Il Roh, In-Su Han, Seong-Won Choi, Mijin Kim, Jeoungyoun Kim, Inseok Lee, "A Method for Ship Piping Design Using Past Data and Expert Knowledge", Proceedings of OMAE(International Conference on Ocean, Offshore and Arctic Engineering) 2025, Vancouver, Canada, 2025.06.22-27


List of Articles
번호 분류 제목 Publication Date
584 International Conference Do-Hyeok Ahn, Myung-Il Roh, In-Chang Yeo, Hye-Won Lee, Seung-Ho Ham, "A Control Method Based on Safe Reinforcement Learning for Cranes in Shipyards", Proceedings of OMAE 2026, Tokyo, Japan, 2026.06.07-12 2026-06-07
583 International Conference Yun-Sik Kim, Myung-Il Roh, Ha-Yun Kim, In-Chang Yeo, Nam-Sun Son, "An Improved Method for Detection and Tracking of Maritime Obstacles Using Multiple-Sensor Fusion", Proceedings of OMAE 2026, Tokyo, Japan, 2026.06.07-12 2026-06-07
582 International Conference Seong-Won Choi, Myung-Il Roh, In-Chang Yeo, "A Method for Ship Collision Avoidance Based on Deep Reinforcement Learning Considering Uncertainty", Proceedings of OMAE 2026, Tokyo, Japan, 2026.06.07-12 2026-06-07
581 International Conference Ha-Yun Kim, Myung-Il Roh, Do-Hyeok Ahn, Min-Chul Kong, In-Chang Yeo, Seong-Won Choi, "A Method for Ship Modeling in a Virtual Environment for SILS-Based Collision Avoidance Simulation", Proceedings of 11th PAAMES and AMEC, Singapore, 2025.12.10-12 file 2025-12-11
580 Domestic Conference 한인수, 노명일, 공민철, 최성원, 장화섭, 조연화, 이갑헌, "도면 검토를 위한 지적 사항 검색 방법", 2025년도 대한조선학회 추계학술발표회, 창원, p. 437, 2025.11.13-11.14 file 2025-11-14
579 Domestic Conference 김윤식, 노명일, 김하연, 여인창, 손남선, "개선된 학습 기반의 해상 장애물 추적 방법", 2025년도 대한조선학회 추계학술발표회, 창원, pp. 405-406, 2025.11.13-11.14 file 2025-11-14
578 Domestic Conference 여인창, 노명일, 최성원, 김윤식, "카메라를 활용한 USV의 접안 지점 및 접근 방향 결정 방법", 2025년도 대한조선학회 추계학술발표회, 창원, p. 402, 2025.11.13-11.14 file 2025-11-14
577 Domestic Conference 김진혁, 노명일, 여인창, "다층 퍼셉트론 구조와 자동 갱신형 근사 모델 기반의 선형 최적화 방법", 2025년도 대한조선학회 추계학술발표회, 창원, pp. 131, 2025.11.13-11.14 file 2025-11-14
576 Domestic Conference 공민철, 노명일, 한인수, 최성원, 김미진, 김정연, 이현승, 이인석, "실적 데이터, 배관 설계 특성 및 전문가 지식을 고려한 선박의 자동 배관 배치 방법", 2025년도 대한조선학회 추계학술발표회, 창원, pp. 442-443, 2025.11.13-11.14 file 2025-11-14
575 Domestic Conference 안도혁, 노명일, 여인창, 이혜원, "블록 탑재를 위한 안전 강화 학습 기반의 대형 크레인 제어 방법", 2025년도 대한조선학회 추계학술발표회, 창원, p. 63, 2025.11.13-11.14 file 2025-11-13
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