在中国使用混合HFACS-CN模型识别建筑事故的关键原因
Xiaolong Wang1, Xiang Yang Hu1, Lulu Wang1
1School of Emergency Management and Safety Engineering, China University of Mining and Technology - Beijing, Beijing, China.
International journal of occupational safety and ergonomics : JOSE
|January 20, 2024
概括
本研究使用混合方法,将人类因素分析和分类系统 (HFACS) 与复杂网络 (CN) 理论相结合,确定了关键建筑事故的原因. 提取了六个关键的因果因素,改善了建筑安全管理.
科学领域:
- 职业安全与健康问题 职业安全与健康问题
- 工程 工程师 工程师 工程师
- 数据科学数据科学数据科学
背景情况:
- 建筑事故对财产和人类生命构成重大风险.
- 有效地确定事故原因对于加强安全管理至关重要.
- 现有的方法可能无法完全捕捉因果因素的复杂相互依赖.
研究的目的:
- 引入和验证一种混合方法来识别建筑事故的关键原因.
- 将人类因素分析和分类系统 (HFACS) 与复杂网络 (CN) 理论结合起来.
- 为改善建筑行业安全协议做出贡献.
主要方法:
- 开发了一种融合HFACS和CN理论的混合方法.
- 收集和分析了863起建筑事故的数据.
- 构建了一个事故因果网络,以提取关键的因果因素.
主要成果:
- 从事故案例中总共确定了46个因果因素.
- 使用混合方法成功提取了六个关键因果因素.
- 与传统方法相比,混合方法在识别关键因果因素方面表现优越.
结论:
- 混合HFACS和CN方法有效地识别了建筑事故中的关键因果因素.
- 这项研究提高了对HFACS和CN理论应用的理解.
- 这些发现为推进建筑行业的安全管理策略提供了宝贵的见解.
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