基于HFACS-PE模型的川航3U8633航班成功备降人为因素解析与安全启示
Analysis of Human Factors in the Successful Diversion of Sichuan Airlines Flight 3U8633 and Its Safety Implications Based on the HFACS-PE Model
DOI: 10.12677/jast.2026.142007, PDF,   
作者: 焦 鹏, 刘宇麟, 毛海涛, 赵 勇:中国人民解放军92728部队,上海;李海君:中国人民解放军91115部队,浙江 舟山
关键词: HFACS-PE川航3U8633成功备降人为因素航空安全HFACS-PE Sichuan Airlines Flight 3U8633 Successful Diversion Human Factors Aviation Safety
摘要: 为填补传统Safety-I安全管理理念及HFACS模型聚焦失效、缺乏正向经验系统化分析工具的缺口,本文以川航3U8633航班遭遇极端险情成功备降案例为对象,立足Safety-II理念,采用HFACS-PE模型开展实证研究。结果表明,正向组织支持、安全监督保障、良好行为前提与核心安全行为是成功备降的关键因素,据此从以上四个维度提出针对性优化建议。研究证实,HFACS-PE模型可有效提炼成功经验,推动航空安全管理从“规避失败”向“复制成功”转型,为构建韧性安全体系提供理论与实践支撑。
Abstract: To address the gap that traditional Safety-I safety management philosophy and the HFACS model focus on failures and lack systematic analytical tools for positive experiences, this study takes the successful emergency landing case of Sichuan Airlines Flight 3U8633 which encountered an extreme emergency as the research object. Based on the Safety-II philosophy, empirical research is conducted using the HFACS-PE model. The results show that positive organizational support, safety supervision guarantee, favorable preconditions for safe behaviors, and core safe behaviors are the key factors for the successful emergency landing, and targeted optimization suggestions are proposed accordingly. The study confirms that the HFACS-PE model can effectively extract successful experiences, promote the transformation of aviation safety management from “avoiding failures” to “replicating successes”, and provide theoretical and practical support for establishing a resilient safety system.
文章引用:焦鹏, 刘宇麟, 李海君, 毛海涛, 赵勇. 基于HFACS-PE模型的川航3U8633航班成功备降人为因素解析与安全启示[J]. 国际航空航天科学, 2026, 14(2): 54-62. https://doi.org/10.12677/jast.2026.142007

参考文献

[1] 中国民用航空局. 航空器严重征候调查报告(SWCAAC-SIR-2018-1): 风挡玻璃空中爆裂脱落四川航空3U8633航班A319-133/B-6419号机重庆至拉萨巡航阶段[R]. 成都: 中国民用航空局, 2020: 16-17.
https://safety.caac.gov.cn/indexnewsdetail/init.act?args=B6B551E0DF6672F4E0531FDE010A7861, 2020-06-01.
[2] 赵赶超, 向小军. 基于多模型的国航4·15飞行事故人误分析[J]. 中国民航飞行学院学报, 2017, 28(4): 41-43.
[3] Materna, M., Maternová, A., Kamenická, D. and Chodelka, F. (2023) The Influence of Human Factor on Aviation Accidents in Slovakia through HFACS Framework: A Comprehensive Study. Transportation Research Procedia, 75, 173-182. [Google Scholar] [CrossRef
[4] 武晨. 基于HFACS-BN的智能船舶碰撞事故人为因素研究[D]: [硕士学位论文]. 大连: 大连海事大学, 2024.
[5] 宋雪青. 基于HFACS的重症医学科医院感染人为因素风险评估指标体系的构建研究[D]: [硕士学位论文]. 济南: 山东大学, 2024.
[6] Lenné, M.G., Salmon, P.M., Liu, C.C. and Trotter, M. (2012) A Systems Approach to Accident Causation in Mining: An Application of the HFACS Method. Accident Analysis & Prevention, 48, 111-117. [Google Scholar] [CrossRef] [PubMed]
[7] Liu, R., Cheng, W., Yu, Y., Xu, Q., Jiang, A. and Lv, T. (2019) An Impacting Factors Analysis of Miners’ Unsafe Acts Based on HFACS-CM and Sem. Process Safety and Environmental Protection, 122, 221-231. [Google Scholar] [CrossRef
[8] Hollnagel, E. (2013) A Tale of Two Safeties. Nuclear Safety and Simulation, 4, 1-2.
[9] Hollnagel, E. (2014) Safety-I and Safety-Ⅱ: The Past and Future of Safety Management. Ashgate.
[10] Zavila, O. (2025) Human Factors Analysis and Classification System-Positive Experience (HFACS-PE): New Approaches to Aviation Accident and Incident Investigation. Journal of Loss Prevention in the Process Industries, 94, Article 105578. [Google Scholar] [CrossRef
[11] 航空生理学编写组. 航空生理学[M]. 北京: 国防工业出版社, 2018.
[12] Lauber, J.K. (2010) Crew Resource Management. Second Edition, Academic Press, 7-9. [Google Scholar] [CrossRef
[13] Airbus (2017) A320 Aircraft Flight Manual (AFM). Airbus S.A.S.