基于改进的HFACS机坪保障车辆不安全事件的灰色关联分析

Gray Correlation Analysis on the Unsafe Events of Service Vehicles in Apron Based on Modified HFACS

为了减少机坪保障车辆的不安全事件,本文在分析某机场近7年机坪保障车辆的不安全事件的基础上,对影响保障车辆不安全事件的人为因素进行了系统研究,并运用HFACS理论,构建了一种改进的适合分析机坪保障车辆不安全事件的HFACS差错模型成因分类框架;同时,鉴于保障车辆不安全事件统计数据较少、原因划分模糊等特点,选择灰色关联分析法,以驾驶差错为例,对驾驶差错与差错成因之间的关系进行了分析,计算了机坪保障车辆不安全事件成因的关联度,确定了机坪保障车辆事故各成因的重要程度,并得出影响驾驶差错的主要成因排序为:问题未纠正彻底、监督违规、培训不足、排班不合理、机坪噪音大、车辆服务的顺序发生变化等;最后提出了有针对性的控制措施,对加强机场的安全管理工作具有重要的意义。

For the purpose of reducing the unsafe events of service vehicles in apron, this paper analyzes the unsafe events of service vehicles in an airport in recent seven years, especially on the impact of human factors by systems analysis method. The paper builds a modified HFACS model which is suitable for analyzing vehicle unsafe events in apron. Due to the lack of statistical data and the fuzzy characteristics of the causes of unsafe events, the paper ap- plies grey correlation analysis method to analyzing the relationship between the driving error and the causes. The sequence of the first few causes are：incomplete correction, lack of training, illegal supervision, unreasonable schedule, apron noise, and the sequence of service vehicles. At the end, the study puts forward specific control measures to strengthen the safety management of airports.