This study aims to establish a data-driven framework for identifying fishing vessel risk factors based on the Korean Maritime Accident Verdicts. As fishing vessels accounted for 64.66% of maritime accidents and 77.45% of fatalities in Korea (2020 – 2024), they represent a key target for maritime safety management. The narrative structure of verdicts — covering background, cause, and consequence — was transformed into 4M (Man, Machine, Method, Media)-based causal data, and the contribution ratios of each factor were calculated by an accident type. To complement documentary analysis, a HAZID (Hazard Identification) workshop was conducted to verify findings through field assessment. The proposed analytical framework converts narrative verdict records into numerical contribution values and reproducible causal sequences, enabling quantitative comparison of accident mechanisms across accident categories. This allows the identification of which causal factors and combinations should be prioritized for prevention efforts in fishing vessels, providing an objective basis for determining safety-check items and risk-control priorities. By integrating quantitative data analysis with field-based validation, this study establishes a practical and data-driven foundation for risk assessment in fishing-vessel design and safety management.

서 론
재료 및 방법
    재결서의 구조적 특징 및 데이터 수집
    전처리 및 데이터 프레임 정의
    사고전개단계 구조화
    4M 체계 기반 원인 분류
    시나리오별 위험도 산정
    정규화 및 4M 기여율 도출
    HAZID 워크숍 기반 현장검증 수행
    워크숍 구성 및 절차
결과 및 고찰
    재결서 데이터의 구조화 및 위험도 평가 결과
    사고유형별 인과 시나리오 단위 분석 결과
    HAZID Workshop 수행 결과
결 론
사 사
References

• 백소연(한국해양교통안전공단 어선안전연구TF 연구원) | So-Yeon BAEK (Researcher, Fishing Vessel Safety Research TF, Korea Maritime Transportation Safety Authority, Sejong 30100, Korea)
• 권수연(한국해양교통안전공단 어선안전연구TF 팀장) | Soo-Yeon KWON (Team Leader, Fishing Vessel Safety Research TF, Korea Maritime Transportation Safety Authority, Sejong 30100, Korea) Corresponding author