[논문]베이지안 네트워크를 이용한 아차사고 평가 모델 개발 및 주요 원인 도출

하선영; 이미정; 백종배

doi:10.14346/jkosos.2023.38.4.54

베이지안 네트워크를 이용한 아차사고 평가 모델 개발 및 주요 원인 도출
Development of Near miss Assessment Model Using Bayesian Network and Derivation of Major Causes 원문보기

한국안전학회지 = Journal of the Korean Society of Safety, v.38 no.4, 2023년, pp.54 - 59

하선영 (한국교통대학교 안전공학과) , 이미정 (한국교통대학교 안전공학과) , 백종배 (한국교통대학교 안전공학과)

Abstract ▼ AI-Helper

The relationship between near misses and major accidents can be confirmed using the ratios proposed by Heinrich and Bird. Systematic reviews of previous national and international studies did not reveal the assessment process used in near-miss management systems. In this study, a model was developed for assessing near misses and major factors were derived through case application. By reviewing national and international literature, 14 factors were selected for each dimension of the P2T (people, procedure, technology) model. To identify the causal relationship between accidents and these factors, a near-miss assessment model was developed using a Bayesian network. In addition, a sensitivity analysis was conducted to derive the major factors. To verify the validity of the model, near-miss data obtained from the ethylene production process were applied. As a result, "PE2 (education)," "PR1 (procedure)," and "TE1 (equipment and facility not installed)" were derived as the major factors causing near misses in this process. If actual workplace data are applied to the near-miss assessment model developed in this study, results that are unique to the workplace can be confirmed. In addition, scientific safety management is possible only when priority is given through sensitivity analysis.

주제어

표/그림 (9)

표 Table 1. Comparison of domestic and international near-miss related research
표 Table 2. Examples of the structure formula
그림 Fig. 1. Near miss assessment model.
표 Table 3. Specific definition of people(PE)
표 Table 4. Specific definition of procedure(PR)
표 Table 5. Specific definition of Technology(TE)
그림 Fig. 2. Near miss assessment model of ethylene manufacturing process.
그림 Fig. 3. Results of sensitivity analysis of ethylene manufacturing process.
표 Table 6. Probability value by factor for target near miss

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