核电厂操纵员人因失误影响因素分析

为研究核电厂操纵员的行为影响因素(PIFs)以及它们间的关联关系,通过文献分析,从组织视角建立比较全面具体的PIFs分类体系。统计分析核电厂大量人因事件,识别影响操纵员人因失误的重要因素。基于人因事件样本数据,对PIFs进行相关性分析,研究PIFs之间的相互影响关系。研究表明:影响核电厂操纵员的主要因素为个体因素中的心理状态、素质和能力,情境环境因素中的规程、培训和组织管理等因素;个体因素受各种情境环境因素的影响,但不同的个体因素与各种情境环境因素的影响关系不同,如心理状态主要受人的素质和能力、技术系统等影响,而人的生理状态主要受工作环境、班组因素和组织结构等影响。     

基于DEMATEL-ISM-BN的施工人员不安全行为致因研究*

为明确施工过程中人的不安全行为致因及产生路径，基于理论与案例分析构建以个体、设备、管理、环境为核心的评估指标体系；结合DEMATEL和ISM并借助专家知识构建层次网络模型，将其映射到BN中，依据节点的先验概率和条件概率实现因素之间耦合关系强度的量化；利用正向因果推理方法预测不同情况下不安全行为发生概率，反向诊断推理识别不安全行为产生的最大致因链。结果表明:施工过程不安全行为发生概率为26.5%，最大致因路径为政府监管力度不足→现场监管工作存在漏洞→不良行为习惯→安全认知失误→不安全行为，可为现场施工人员安全行为管控提供参考。     

人因失误机理及原因因素研究

在复杂社会技术系统中,人因失误已成为引发事故的最主要原因之一.给出了国内外学者对人因失误的定义.从个体和组织层次上分析了人因失误的机理,并基于此失误机理分析了人误原因因素,给出了个体和组织层次下的原因因素图.     

电梯检验过程人因失误及其影响因素的实证研究

以248家电梯企业(包括外企和国企)的中高层管理人员和基层技术人员为调查对象,对人因失误的主要影响因素进行实证研究。研究结果表明,员工的能力素质、组织沟通与组织文化因素与人因失误的频繁程度显著负相关。此外,电梯检验过程人因失误与个体年龄、工龄、婚姻状况也存在相关性。研究结果为电梯行业改善组织管理,降低人因失误提供了充分的依据。     

高处坠落事故的人因失误与干预策略研究

为系统分析导致高处坠落人因事故的产生机理,通过统计152起建筑工程高处坠落事故的调查与分析报告,从组织影响、安全监管、不安全行为前提条件和不安全行为等4个层次,辨识影响高处坠落事故的人为失误因素,修订人为因素分析与分类系统框架（HFACS）。设计高处坠落人因失误调查问卷,开展一线高处作业人员问卷调查,建立高处坠落人因失误结构方程模型,对导致高处坠落事故的人为失误因素进行路径分析。结果表明:各潜在因素间均呈正相关,且高处坠落人因失误事故的关键路径为资源管理不到位→安全监督培训不充分→班组管理不良→操作违规。综合各因素间相关性,提出了针对性的预防高处坠落事故的人因干预策略。     

高铁列车调度员人因失误概率量化方法研究

为评估高铁列车调度员操作可靠性及其对列车调度系统风险的影响,建立改进的高铁列车调度人因失误概率量化方法。首先根据高铁列车调度指挥认知行为模型划分列车调度任务类型,对各任务类型下的人因失误分别构造贝叶斯网络(BN)模型。然后,基于证据理论(D-S)合成专家多源信息,以确定节点变量状态先验概率和条件概率。最后,通过贝叶斯推理计算成功似然指数(SLI),并依据成功似然指数法(SLIM)将其转化为人因失误概率。以列车临时限速为例进行应用分析。研究结果表明,在给定边界概率的基础上,用该方法能获得列车调度员不同任务类型和不同行为影响因子下的人因失误概率。列车调度员发布限速调度命令时总的人因失误概率为0.002 24。     

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。     

一种基于认知过程分析的人因失误辨识方法——应用于高速铁路列车调度系统

通过总结既有的人因失误分类方法,对主要分类方法的优缺点和适用性进行了评述。既有的人因失误分类方法主要侧重于人因事故分析,在对人的认知过程四阶段尤其是计划决策阶段的失误模式进行主动辨识具有较大的困难。通过综合认知行为四阶段模型和技能型-规则型-知识型行为理论(SRK理论),建立了高铁列车调度指挥认知行为SRK模型。以认知行为SRK模型为基础,提出一种新的人因失误分类方法用以人因失误辨识。以高铁列车调度指挥临时限速为任务背景,进行实际的人因失误辨识工作,并给出了详细的辨识结果。通过对列车调度员的访谈,辨识结果全面覆盖了临时限速时可能出现的人因失误类型,验证了方法的实用性。     

基于DEMATEL的铁路行车人因事故关键因素实证分析

针对铁路行车人因事故受多因素交互影响的问题,提出了一种基于信息熵和DEMATEL法耦合的铁路行车人因事故关键因素实证分析方法。首先依据铁路行车人因事故认知行为模型,从感知、决策、计划和执行4个过程分析铁路行车人因事故的影响因素;然后综合运用信息熵和DEMATEL法构建关键因素量化识别模型,利用中心度和原因度两个参数分析铁路行车人因事故的关键影响因素;最后,结合2008—2013年铁路行车人因事故数据进行实证分析。结果表明,机车操作人员相关情形记忆失误、情景诊断失误、未严格执行操作规则和采取错误行动是铁路行车人因事故的关键影响因素。     

掘进工作面复杂环境因素与人因伤亡事故的关联度分析

为探究煤矿掘进工作面的温度、湿度、噪声、照度、粉尘等环境因素对人因伤亡事故发生的影响,进一步明确不同类型的人因伤亡事故与各环境因素之间的关系,针对人因伤亡事故的发生与各环境因素之间不具有确定的线性关系,而是具有灰色系统的特点,运用灰色关联分析方法建立了不同类型人因伤亡事故与环境因素之间的灰色关系模型,分析了掘进工作面不同类型的人因伤亡事故与各环境因素之间关联程度的大小。结果表明,在煤矿掘进工作面的温度、湿度、噪声、照度、粉尘5个环境因素中,温度是影响掘进工作面人因伤亡事故的最主要因素,其次是光照,再次是温度。     

考虑组织因素的液化天然气泄漏安全评价方法

为考虑组织因素对于人因失误发生的根本性影响,提出一种以贝叶斯网络(BN)为工具的人因风险分析方法,并用于液化天然气泄漏的安全评价。先将认知可靠性与失误分析方法(CREAM)的共同绩效条件(CPC)分成3层,即组织层、技术系统层和个人层。以BN为工具,利用其因果推理和诊断推理的功能,进行人因失误预测和追溯的双向分析。将考虑组织因素的人员操作失误概率引入浮式液化天然气船(FLNGV)装卸过程LNG泄漏的BN中,进行LNG泄漏的安全评价以及事故原因的重要度分析。结果表明,"执行"失误是LNG泄漏最主要的事故原因,而个人层的CPC会对执行失误产生较大的影响。     

An integrated framework to the predictive error analysis in emergency situation

This paper introduces an analysis framework and procedure to predictively analyze human errors in performing emergency tasks, which are mostly composed of cognitive activities, in nuclear power plants. The framework focuses on the cognitive errors and provides a new perspective in the utilization of context factors into cognitive error prediction. The basic viewpoint on the occurrence of cognitive error taken in this paper is that the cognitive function failures occur from the mismatch between operator's cognitive capability and the requirements of a given task and situational condition. In accordance with this viewpoint, performance influencing factors that influence the occurrence of human errors are classified into three groups, i.e. Performance Assisting Factors (PAF), Task Characteristic Factors (TCF), and Situational Factors (SF). This classification helps analysts view the overall task context in an integrative way by considering the level of PAF with the requirements of TCF and SF to predict the possibility of cognitive function failures. Further, it enables analysts to draw specific error reduction strategies. The framework suggested was applied to the analysis of cognitive error potential for the bleed and feed operation of emergency tasks in nuclear power plants.     

A fuzzy Bayesian network approach to improve the quantification of organizational influences in HRA frameworks

Organizational factors are the major root causes of human errors, while there have been no formal causal model of human behavior to model the effects of organizational factors on human reliability. The purpose of this paper is to develop a fuzzy Bayesian network (BN) approach to improve the quantification of organizational influences in HRA (human reliability analysis) frameworks. Firstly, a conceptual causal framework is built to analyze the causal relationships between organizational factors and human reliability or human error. Then, the probability inference model for HRA is built by combining the conceptual causal framework with BN to implement causal and diagnostic inference. Finally, a case example is presented to demonstrate the specific application of the proposed methodology. The results show that the proposed methodology of combining the conceptual causal model with BN approach can not only qualitatively model the causal relationships between organizational factors and human reliability but also can quantitatively measure human operational reliability, and identify the most likely root causes or the prioritization of root causes causing human error.     

用层次分析法分析核电站中影响人误的组织因素

应用层次分析法的基本原理,构建核电站中影响人误的组织因素AHP(层次分析法)模型,确定影响人误的组织因素的指标体系,将成对比较矩阵的特征向量作为组织因素的权重,确定了相关因子的影响力排序。研究结果显示:培训与交流反馈是影响人误的主要组织因素;强化质量监督与控制以及加强交流协作与技能培训,是减少核电站人误发生的重要举措。     

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的化工企业火灾爆炸事故人因分析*

为研究化工企业火灾爆炸事故的主要人为因素，以63起火灾爆炸事故案例为样本，构建人为因素分析与分类系统（HFACS）模型，进行火灾爆炸事故人为因素分类统计与分析，并利用卡方检验和比值比分析HFACS模型上下层级间的因果关系。结果表明:HFACS模型中上下层级人为因素间存在显著的因果关系，层级1中的“不良的组织氛围”及“组织过程漏洞”和层级2中“监督不充分”在HFACS模型中可以显著增大事故发生的可能性，且“资源管理漏洞”、“不良的组织氛围”、“组织过程漏洞”→“监督不充分”→“人员因素”→“违规”是引发事故的关键路径，并根据HFACS模型中引发事故的关键路径及其人为因素的主要表现形式，提出针对性的化工企业火灾爆炸事故预防措施。     

Human error taxonomies applied to driving: A generic driver error taxonomy and its implications for intelligent transport systems

Recent research indicates that driver error contributes to up to 75% of all roadway crashes. Despite this, only relatively little is currently known about the types of errors that drivers make and of the causal factors that contribute to these errors being made. This article presents an overview of the literature on human error in road transport. In particular, the work of three pioneers of human error research, Norman, Reason and Rasmussen, is scrutinised. An overview of the research on driver error follows, to consider the different types of errors that drivers make. It was found that all but one of these does not use a human error taxonomy. A generic driver error taxonomy is therefore proposed based upon the dominant psychological mechanisms thought to be involved. These mechanisms are: perception, attention, situation assessment, planning, and intention, memory and recall, and action execution. In addition, a taxonomy of road transport error causing factors, derived from the review of the driver error literature, is also presented. In conclusion to this article, a range of potential technological solutions that could be used to either prevent, or mitigate, the consequences of the driver errors identified are specified.     

Why bad things happen to good people

Accidents in the process industries are extensively investigated to determine root causes, for lessons learned, and many times in search of the “guilty”. Accidents are seldom simple and most accidents have human elements that led to or facilitated the accident. Many times the people involved in these accidents, when considered individually on their merit, would be considered “good” people yet “bad things” (accidents) still occur.Human errors can be classified as individual, group, and organizational. Individual human errors have been addressed in a number of studies and papers. Many of these classify human errors and treat them probabilistically or cognitively. Less has been said regarding the individual psychological/sociological response/interaction mechanisms that might contribute to an industrial accident. These elements also contribute to a lack of situational awareness which often plays a large part in human error. Group and organizational interactions/dynamics can also contribute negatively to situational awareness and to the chain of events of an accident. Organization errors, which are typically latent, can also facilitate an accident and are many times people enabled for personal and business vested interests.This paper will discuss the effect of human error at the practical plant level in contributing to accidents in the process industries from individual, group, and organizational perspective. The discussion will include psychological/sociological response/interaction mechanisms that can contribute to situational awareness and human error. It will also discuss how complexity, veracity, and quantity of available information can affect the human decision-making process leading to mistakes.Accidents are seldom simple and most accidents have a number of elements that led to or facilitated the accident. When looking at individual elements probabilistically, multiplying probabilities together, it is hard to see how an accident could have occurred. A common refrain “That’s double jeopardy and we don’t have to consider that” is essentially a qualitative probabilistic analysis. Yet we have cases of triple, quadruple, n-jeopardy occurring to cause accidents. The paper will discuss the superimposition of causes and a similar concept of functional resonance in causing accidents.     

基于HERA-JANUS模型的空管人误认知分析

空管人误分类分析是空管人误研究的基础。为了对管制员人误进行系统的分类研究,结合空管业务知识和认知心理学理论,对欧洲航空安全局和美国联邦航空局合作开发的HERA-JANUS模型的工作原理和流程进行较详细地分析。运用该方法模型,对我国一起空管不安全事件案例进行分析后得到3个由管制员所产生的人误差错,并对这3个人误差错分别从人误类型、人误认知、相关因素3方面进行详尽的分析研究,最后得出该不安全事件的21项人误结果。结果表明,HERA-JANUS模型能较全面地从深层次分析管制员的人误,其分类形式也便于开展空管人误统计。