航空人为差错事故/事件分析(ECAR)模型研究

为深入研究航空人为差错事故/事件的影响因素,以人为差错相关理论为基础,对比分析几种典型的人为差错分析模型;通过借鉴ECCAIRS分析框架,并在基元事件分析(EEAM)逻辑和CCAR396部的分类方法基础上,构建航空人为差错事故/事件分析(ECAR)模型,它从事件层、描述层、原因层和组织因素与改进建议层,分析航空事故和不安全事件的人为差错。此外,还将组织因素概念引入该模型。     

基于HFACS的空中相撞事故分析及建议

空中相撞事故往往是由诸多人为差错相互叠加、耦合和作用而导致的,要找出事故的真正诱因,防止类似事故再次发生,难度非常大。为了有效地分析和定位人为差错,以更好地服务于防相撞的管理与决策,提出一种基于人为因素分析分类系统（HFACS）的空中相撞事故分析方法,它按照从显性差错到隐性差错的思路来分析事故的诱因,最终找出组织因素对事故的影响。并利用HFACS对巴西卡欣布上空发生的一起空中相撞事故进行了系统分析。案例分析结果表明,该方法不仅能够找出导致空中相撞事故的人为差错,解释事故发生的原因和过程,而且能够据此提供防止相撞事故发生的安全建议。     

航空维修人为差错的行为特点分析及对策

主要从行为科学的基本理论出发，通过对航空维修人为差错的统计分析，寻求人为差错的行为类型、特点及预防人为差错的基本对策     

基于SHEL模型的航空维修差错风险指标体系

航空维修差错是导致航空事故的重要诱因,预防维修差错对于保障航空安全具有重要现实意义。为有效识别与缓解维修差错风险,根据民航维修差错咨询通告(AC-121-007),采用层次分析法(AHP),结合SHEL模型从人、硬件、软件和环境四方面确定航空维修差错风险指标体系及权重排序。结果表明,沟通与协调、心理/生理素质、安全文化、知识与技能等是维修差错的关键风险指标。鉴于以上差错指标风险程度,有针对性提出维修差错防控措施,从而降低维修差错风险。     

基于BP神经网络的海军飞行员人为差错安全影响评估

为了更客观合理地对海军飞行员人为差错安全影响进行评估,提出了一套基于BP神经网络的海军飞行员人为差错安全影响评估方法。首先,根据"人为错误因素"模型并结合海军航空兵飞行员人为因素事故案例建立海军飞行员人为差错安全影响评估指标体系;然后,依据该指标体系构建了基于BP神经网络的人为差错飞行安全影响评估模型;最后,以海军航空兵历年人为因素事故统计数据为训练样本对BP神经网络安全影响模型进行训练,并利用该模型对部分数据进行飞行安全影响评估测试。结果表明,评估结果符合实际情况,该方法可对海军航空兵飞行员人为差错安全影响进行评估。     

一种基于贝叶斯网络的机务维修差错调查模型算法

提出一种基于贝叶斯网络的机务维修差错调查模型算法,根据已经建立的机务人为诱因导致事故/事故征候模型,利用贝叶斯原理编程实现了该算法。利用该算法对中国民航飞行学院2001-2011年的机务人为有引导的事故/事故征候依次进行分析并验证,得到了相应的事故诱因概率排序。该算法克服了样本空间不足,在事故发生以后能够在引入其他证据的情况下根据以前的经验概率得到新的事故诱因概率排序,为民航机务维修差错调查提供了可靠的技术支持。     

人为差错成因分析方法研究

控制甚至消除人为差错成因能从本质上降低人为差错的发生概率,从而提高系统安全性。因此,辨识和分析人为差错成因是一件非常必要而又十分重要的工作。针对该问题,在总结和分析现有的人为差错成因分析方法的基础上,提出了一种新的人为差错成因分析框架。在该框架中,将差错成因分为"操作者-系统-任务-环境-组织因素"5个方面进行分析,并提出了"从大类到小类"的层次化分析原则。为了尽量降低不同差错成因之间的关联,提出了以任务为中心,将差错成因分为任务相关和任务无关两大类因子的分类方式。最终共分析得出了34种不同的差错成因。该差错成因分类框架的提出,为人为差错概率量化以及差错规避措施的设计提供了依据。     

航空维修差错分析及其管理

航空维修差错是诱发或直接导致飞行事故最重要的原因之一 ,对维修差错进行分类和分析有助于航空安全。笔者在分析航空维修环境变化的基础上 ,基于Reason模型构建了维修差错分类与诱因分析的框架 ,并结合机务维修的实际情况 ,对框架所包括的不安全行为、不安全行为的先兆、不安全的管理及组织因素进行了初步编码。文章还简要论述了维修差错的管理技术 ,指出借助框架编制详细的差错分类与分析编码系统是发展的方向。     

航空维修差错模式及差错成因的灰色关联分析

提出一种基于HFACS-ME框架和灰色关联分析法的航空维修差错模式和差错成因之间关系的分析方法。利用该方法分别从"模式—成因"和"成因—模式"2个方向,以"技能差错"和"身体状态差"为例,对差错模式和差错成因之间的关系进行分析,得到影响"技能差错"的主要差错成因依次为空间狭窄、培训不足、工具损坏、身体状态差、精神状态差、空间阻碍,以及"身体状态差"主要影响的差错模式为记忆差错、决策差错、技能差错。结果表明,灰色关联分析法对航空维修差错模式和差错成因之间关系的分析是有效的、可行的。     

基于灰色关联分析的LNG接收终端人因事故辨识方法

陆岸LNG接收终端是LNG海上进口系统中的重要设施。针对我国LNG接收终端人因事故不断增多的现状，基于航空事故调查分析中的HFACS事故致因分析模型，将人因事故的影响因素归纳为个人因素、人际因素、环境因素、监督因素和组织因素五大类，结合灰色理论中的灰色关联分析，得到了LNG接收终端人因事故辨识方法。最后，运用该方法对某LNG接收终端人因事故进行辨识，通过灰关联度的计算，找出其最主要的不安全事件来自“个人因素”中的个人“安全意识不强”。此方法克服了小样本事故数据带来的弊端，对保障LNG接收终端的安全运行具有一定的指导意义。     

层次分析法及其在航空工业企业风险评价中的应用研究

结合历史事故统计及调查问卷分析,确定评价分析指标;应用层次分析法确定评估因素;建立较为完备的航空工业企业评价体系模型;对指标的权重进行综合的定量分析和计算,确定了航空工业企业评估指标的权重。应用实例表明:应用层次分析法确定评价指标权重,可以综合考虑影响事故各种影响因素,能较为客观、真实地反映被评价指标因素概况,易于实现计算机程序化,直观易懂,可操作性强,可在航空工业企业中推广应用。     

基于灰色系统理论的煤矿人因事故关键因素分析

通过对煤矿人因失误事故致因因素进行分析,统计出相关的关键影响因素,运用灰色系统关联理论,根据国家安监局近十年煤矿事故统计数据,对煤矿人因失误事故影响类型进行了分析。以煤矿事故发生起数和事故死亡人数作为参考指标,计算和分析行为失误致因、个人违章、组织管理失误等十项主要与煤矿人因事故相关的灰色关联度,进而推算出这些因素的灰色关联序,确定出导致煤矿人因失误事故的关键因素,最终得到煤矿人因事故与关键影响因素之间的定量化分析结果。采用灰色关联理论对煤矿人因失误影响因素进行分析,能够很好地说明人因失误与各关键影响因素之间的权重关系,对煤矿人因事故主致因机理有更加深刻的理解,为煤矿事故的预防和控制提供重要的参考依据。     

基于事故/事件的民机人因防错设计关键因素研究

针对民机人因防错设计对飞行安全的影响,从世界民航安全事故/事件数据库中筛选出92起典型的人为因素事故案例,采用基元事件分析法进行深度分析,提炼出民机人因防错设计需要考虑的重要设计因素,并建立重要设计因素集。基于系统工程学的“人机环”模型,结合国内外飞机设计相关标准,建立民机人因防错设计重要因素指标体系。运用模糊层次分析法对因素指标进行权重计算,确立影响飞行安全的14项人因防错设计关键因素,并针对这些关键因素提出民机人因防错设计通用要求,以期为民机人因防错设计满足初始适航要求提供参考。     

Arabian,Asian, western: a cross-cultural comparison of aircraft accidents from human factor perspectives

Introduction. Rates of aviation accident differ in different regions; and national culture has been implicated as a factor. This invites a discussion about the role of national culture in aviation accidents. This study makes a cross-cultural comparison between Oman, Taiwan and the USA. Method. A cross-cultural comparison was acquired using data from three studies, including this study, by applying the Human Factors Analysis and Classification System (HFACS) framework. The Taiwan study presented 523 mishaps with 1762 occurrences of human error obtained from the Republic of China Air Force. The study from the USA carried out for commercial aviation had 119 accidents with 245 instances of human error. This study carried out in Oman had a total of 40 aircraft accidents with 129 incidences. Results. Variations were found between Oman, Taiwan and the USA at the levels of organisational influence and unsafe supervision. Seven HFACS categories showed significant differences between the three countries (p?<?0.05). Conclusion. Although not given much consideration, national culture can have an impact on aviation safety. This study revealed that national culture plays a role in aircraft accidents related to human factors that cannot be disregarded.     

A modified accident analysis and investigation model for the general aviation industry: Emphasizing on human and organizational factors

IntroductionCurrently, there is a lack of specific analytical tools for general aviation accidents (GAAs). This has led to loopholes in the prevention of GAAs.MethodsA Swiss Cheese model for general aviation (SCM-GA) is proposed to identify the human and organizational factors involved in GAAs. In the proposed SCM-GA, 5 categories, 45 subcategories, a general aviation safety management system (GA-SMS) and safety culture were developed based on the classic accident causation models combined with the laws and regulations and safety management practices in the general aviation industry.ResultsOne GAA was analyzed using SCM-GA. The human and organizational causes revealed by SCM-GA were more complete than the causes revealed through the accident report. The identification results of the deficiencies in the subcategories of GA-SMS and the safety culture were more consistent with the requirements in the general aviation laws and regulations than the organizational factors in the accident report. Based on the subcategories of SCM-GA, 41 GAAs that occurred between 1996 and 2010 in China were statistically analyzed and χ² test analyses were performed to estimate the statistical strength of the association between two adjacent subcategories of SCM-GA. The results showed that two adjacent subcategories of SCM-GA were significantly associated. They helped to determine the hidden problems in the accident report based on the path of accident.ConclusionsSCM-GA is an accident analysis tool that can comprehensively analyze the human and organizational deficiencies involved in GAAs. The accident causes revealed by SCM-GA were more consistent with the general aviation safety management practices.Practical applicationsGeneral aviation companies should establish their own GA-SMS and safety culture based on the subcategories developed herein. Using SCM-GA for routine safety inspection and accident investigation will help the management and the staff make effective safety decisions to effectively prevent GAAs.     

基于CREAM和贝叶斯网络的航空维修人为差错概率预测

航空维修差错不仅严重威胁着飞行安全,同时也会增加航空公司的维修成本。针对航空维修人员发生差错成因的复杂性以及历史事故数据缺乏的情况下,将人因可靠性与失误分析方法（CREAM）和贝叶斯网络（BN）相结合,提出一种改进的维修差错分析模型。根据维修任务构建相应的贝叶斯网络模型,为各子节点设置条件概率表（CPT）;基于维修基地的实际维修环境,对行为形成因子（PSFs）进行评估,得到共同绩效条件（CPCs）的水平;利用各CPC因子下各个行为功能失效模式的权重因子,对各认知活动进行失效概率的修正;将修正概率作为贝叶斯网络根节点的输入,利用推理机制,得到差错发生概率。通过案例分析和计算,验证了所述方法的可行性和有效性。     

航空事故调查中人的因素安全建议框架研究

对航空事故中人的不安全行为进行了系统分析,将失误划分为感知失误、记忆失误、决策失误、技能失误4个类别,将违章划分为习惯性违章和偶然性违章。将人的因素干预维度确定为组织管理、人/团队、技术、任务和环境。针对不安全行为制定相应的初步改进措施后,还需从措施的可行性、可接受性、经济性和有效性4个方面进行综合评估和取舍。实证研究表明,人的因素干预矩阵是制定安全建议的有效工具,该框架具备良好的适用性。     

Allocation of performance shaping factors in the risk assessment of an offshore installation

Offshore oil production is one of the most important human productive activities. There are many risks associated with the process of constructing a subsea well, pumping oil to the platform, and transporting it to refineries via underwater pipes or oil tankers. All actions performed by workers in those operations are influenced by specific working conditions, involving the use of complex systems. Contextual factors such as high noise, low and high temperatures and hazardous chemicals are considered to be contributors to unsafe human actions in accident analysis and also give a basis for assessing human factors in safety analysis. Some failure modes are particularly dangerous and can result in severe accidents and damage to humans, the environment and material assets. Fires and explosions on oil rigs are some of the most devastating types of offshore accidents and can result in long-term consequences. The most typical root causes related to accidents include equipment failure, human error, environmental factors, work organization, training and, communication, among others. The principal objective of this study is to propose a methodological framework to identify the factors that affect the performance of operators of an offshore unit for oil processing and treatment. In this phase, an ergonomics approach based on operators' work analysis is used as a supporting tool. After identification of factors that affect the performance of operators, a decision-making model based on AHP (analytic hierarchy process) is applied to rank and weight the principal performance shaping factors (PSFs) that influence safe operations. The next step involves the use of the SHELLO model to group the main PSFs in elements named software, hardware, environment, liveware and organization. In the last phase, a relevant accident that occurred aboard a floating production storage and offloading (FPSO) vessel is analyzed. The allocation process of the factors that affect the operator's performance in risk assessment was developed through fuzzy logic and the ISO 17776 standard.