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Abstract Design regulations are constantly being revised to ensure the safety and robust design of ships. Advancements in technology and the growing scale of ships have made design regulations increasingly specialized and detailed. As a result, workers such as designers and inspectors face growing challenges in efficiently finding necessary information within the large volume of design regulation documents. In particular, a significant investment of time and effort is required to thoroughly review each regulation and comprehend the specialized terminology and complex details in order to obtain the desired information. Therefore, this study proposed a method to address these challenges by implementing a generative AI-based Q&A system. The proposed method employed a RAG (Retrieval-Augmented Generation) architecture, which integrates information search modules with generative AI capabilities, to construct a Q&A system that is both accurate and reliable. First, data were extracted from PDF-format design regulations and transformed into a format suitable for the RAG architecture, and used to build the corresponding database. The concept of domain adaptation was then applied to a pre-trained general-purpose language model, resulting in a specialized Q&A system dedicated to design regulations. The proposed Q&A system quickly identifies relevant regulations within the database based on the designer’s queries. It then provides detailed and accurate answers that align with the intent of the query, leveraging generative AI. Applying this system to the regulations of the Korean Register (KR-Rules) demonstrated its ability to deliver fast and precise information to the designer’s queries. By enabling better comprehension of complex ship design regulations and delivering context-relevant answers beyond simple document searches, this study is expected to improve the work efficiency of workers in the field significantly.
Publication Date 2025-10-20

In-Su Han, Myung-Il Roh, Min-Chul Kong, "A Generative AI-based Q&A System for Design Regulations", Proceedings of PRADS(International Symposium on Practical Design of Ships and Other Floating Structures) 2025, Ann Arbor, USA, 2025.10.19-23


List of Articles
번호 분류 제목 Publication Date
553 Domestic Conference 안도혁, 노명일, 여인창, 이혜원, "다양한 작업 조건을 고려한 해상 크레인의 심층 강화 학습 기반 제어 방법", 2025년도 대한조선학회 춘계학술발표회, 부산, p. 362, 2025.05.08-05.10 file 2025-05-09
552 Domestic Conference 김진혁, 노명일, 여인창, "불확실성을 고려한 선형 성능 예측 근사 모델의 자동 개선 방법", 2025년도 한국CDE학회 동계학술발표회, 용평, 2024.02.19-02.22 file 2025-02-20
551 International Conference In-Chang Yeo, Myung-Il Roh, Jin-Hyeok Kim, In-Su Han, Dong-Woo Kim,"A Method for Optimizing Pump Tower Design in LNG Tanks Considering Structural Safety", Proceedings of PRADS 2025, Ann Arbor, USA, 2025.10.19-23 file 2025-10-23
» International Conference In-Su Han, Myung-Il Roh, Min-Chul Kong, "A Generative AI-based Q&A System for Design Regulations", Proceedings of PRADS 2025, Ann Arbor, USA, 2025.10.19-23 file 2025-10-20
549 Domestic Conference 김하연, 안도혁, 공민철, 여인창, "자율 운항 선박의 성능 검증을 위한 통합시험 환경", 2025년도 한국CDE학회 동계학술발표회, 용평, 2024.02.19-02.22 file 2025-02-20
548 Domestic Conference 최성원, 노명일, 여인창, "속도 제어를 고려한 심층 강화 학습 기반 자율 운항 선박의 충돌 회피 방법", 2025년도 한국CDE학회 동계학술발표회, 용평, 2025.02.19-02.22 file 2025-02-20
547 Domestic Conference 김윤식, 노명일, 안도혁, 김하연, 여인창, 손남선, "해상 장애물 추적을 위한 개선된 위치 예측 방법", 2025년도 한국CDE학회 동계학술발표회, 용평, 2025.02.19-02.22 file 2025-02-20
546 International Conference Seong-Won Choi, Myung-Il Roh, In-Chang Yeo, "A Method for Collision Avoidance of an Autonomous Ship in Dynamic Environments", Proceedings of ISOPE 2025, Goyang, Korea, 2025.06.01-06 file 2025-06-05
545 Domestic Conference 안도혁, 노명일, 여인창, 이혜원, 전도현, "다양한 해상 상태를 고려한 해상 크레인의 심층 강화 학습 기반 제어 방법", 2025년도 한국CDE학회 동계학술발표회, 용평, 2024.02.19-02.22 file 2025-02-20
544 Domestic Conference 한인수, 노명일, 공민철, "선박 규정 검색을 위한 생성형 AI 기반 질의 응답 시스템 구축", 2025년도 한국CDE학회 동계학술발표회, 용평, 2024.02.19-02.22 file 2025-02-20
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