人误模式与原因因素分析

将人误模式分为显现型和潜在型两类.显现型人误模式主要体现在时间、行为、目标、顺序四维时空特性上,而潜在的人误模式是基于认知过程与组织的,需要从微观与宏观两方面对其进行分类.影响人为失误的原因归结为个人、技术、组织、环境四类因素.将人误作为一个事件来进行分析,构建了概念上的人误原因层次诊断模型,它包括原因主因素、子因素和子子因素层等.以人误模式为切入点,对这些因素的诊断采用了人误原因的回溯性分析方法,具体过程为:一般行为条件描述-确定可能的人误模式-确定可能的人误原因因素-匹配判断.     

复杂人-机系统中人因失误因素辨识

章讨论了复杂人一机系统的特征和其人因失误因素辨识(HEFI)的意义；对HEFI技术的现状进行了简单的评述；提出一种结构化的HEFI方法人因失识因素辨识多视图，给出了其框架结构。     

地铁行车调度员人误模式结构化分析

为了预防地铁行车调度系统人因事故,本文基于层次分析法(HTA)和多资源理论,提出了一种地铁行车调度人误模式的结构化分析方法。首先定义了基本任务模块,将传统层次分析拆解为基本任务模块分析和任务分析两个阶段,以构建人因事件场景;然后完成了对行车调度员感知、认知及操作的人误行为分析,并构建基于视觉、听觉、认知与心理运动(Visual,Auditory,Cognitive,Psychomotor)模型的地铁行车调度员人误行为分类框架,以行为难度等级作为人误行为发生可能性的评价依据;最后,将分析过程进一步规范总结为包含任务分析层、人误行为分析层、人误模式诊断层的结构化的人误模式分析模型。对接触轨断电突发事件案例研究表明,此模型可以通过对地铁行车调度员工作任务的详细分解,寻找到可能的人误行为,并诊断出人误模式及发生的可能性。     

组织人因失误分析

工业生产中，人因失误已成为最主要的事故源之一。人因失误研究越来越受到重视，研究方向已从个体失误向组织人误发展。文章论述了组织人因失误产生的过程，辨识出组织人因失误行为形成因子(PSFs)并归纳成为组织人因失误的4大类12组原因因素，提出了预防组织人因失误的基本对策。     

复杂人机系统人误分析技术研究

构建了反映复杂人机系统动态与潜在失误的人误分析基本框架,从组织、操纵员、设备与机器三个部分出发分析人误的形成及其相互关系.提出包含原因分析和因素分析两大模块的人误分析模型,在原因分析中着重分析组织失误的基本分类,通过对复杂系统中可能导致风险的潜在内部与外部人员行为形成因子研究,给出了动态条件下的人误风险指数计算方法,综合反映在特定条件下不同重要度的行为形成因子对系统风险的影响.     

紧急情况下人的误判断与误操作数学模型

分析人在紧急情况下的行为特征，讨论人产生误操作和误判断的根源与影响因素。通过在紧急情况下人的误操作与误判断实验，得到紧急情况下成年人的特征数据，建立了紧急情况下人的误判断与误操作数学模型。     

利用IHCP对淬火测试探头表面冷却特性辨识的研究

通过对淬火测试探头进行导热反问题辨识，得到了探头表面的淬火冷却特性曲线。中简单要阐述了反问题辨识的基本原理和方法；给出了数学模模拟及典型的实验结果；对辨识结果的精度进行了实测验证；并分析了影响精度的主要原因。研究表明，反问题方法能得到准确可靠的辨识结果。     

复杂社会-技术系统中人误演变过程

从微观个体和宏观组织两方面研究人误的产生、发展演变过程。微观方面基于人机系统揭示单个人误的产生发展过程;宏观方面侧通过人误事件的分析,揭示人误事件的发展演变过程。最后,整合上述两方面建立了人误演变模型,且探讨了人误的三种演变模式：纵向、横向及混合演变模式。     

民用航空中的人误分类与分析

根据民航实际情况分析人误概念，强调在实践中应将人误看作事件而不是事故的原因，重视人误事件的原因分析。在简要介绍五种主要的人误研究取向基础上，提出人误事件分类和分析的触发器--不安全事件--结果框架(Triggers-Events-Result,TER)。     

人误模式、影响与严重度分析方法

人因失误已成为复杂系统最主要的事故源之一，而人误分析技术存在着缺乏一致性和使用困难等问题。本文将故障模式，影响与严重度分析方法进行人因特征化改造，提出人误模式，影响与严重度分析方法，规范化地分析人因失误的故障模式与影响，根本原因及严重度和相应的人因失误防范策略。     

Combining task analysis and fault tree analysis for accident and incident analysis: A case study from Bulgaria

Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident – the flooding of the plant's basement – was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.     

Looking for errors of omission and commission or The Hunting of the Snark revisited

Since the early 1990s, considerable effort has been spent to understand what is meant by an “error of commission” (EOC), to complement the traditional notion of an “error of omission” (EOO). This paper argues that the EOO–EOC dyad, as an artefact of the PSA event tree, is insufficient for human reliability analysis (HRA) for several reasons: (1) EOO–EOC fail to distinguish between manifestation and cause; (2) EOO–EOC refer to classes of incorrect actions rather than to specific instances; (3) there is no unique way of classifying an event using EOO–EOC; (4) the set of error modes that cannot reasonably be classified as EOO is too diverse to fit into any single category of its own. Since the use of EOO–EOC leads to serious problems for HRA, an alternative is required. This can be found in the concept of error modes, which has a long history in risk analysis. A specific system for error mode prediction was tested in a simulator experiment. The analysis of the results showed that error modes could be qualitatively predicted with sufficient accuracy (68% correct) to propose this method as a way to determine how operator actions can fail in PSA-cum-HRA. Although this still leaves the thorny issue of quantification, a consistent prediction of error modes provides a better starting point for determining probabilities than the EOO–EOC dyad. It also opens a possibility for quantification methods where the influence of the common performance conditions is prior to and more important than individual failure rates.     

Human reliability analysis—Taxonomy and praxes of human entropy boundary conditions for marine and offshore applications

This is the first stage towards the development of a human reliability model called human entropy (HENT). The paper presents qualitative and quantitative taxonomies and praxes of performance shaping factors (PSF) for Marine and Offshore operations. Three structured and guided expert elicitation methods were used in this study. The experts interrogated accident reports and databases from which the generic root causes of failures/accidents in operations are determined. The elicitations led to the development of 9 qualitative and quantitative human influencing factors, which are called Human Entropy Boundary Conditions (HEBC). Further explications of the 9 HEBC gave birth to 137 quantifiable explanatory variables, which are called hypothetical constructs (HyC). The HyCs are used to identify potential risks due to shrinkages in safety standards. Human entropy is a detour from traditional human error and was used as a result of tripartite human failure modes; error, local rationality and extraneous acts, all of which signify disorderliness and are seemingly inevitable in maritime operations. The praxes and scaling of HEBC was developed as guidance towards a practical oriented HRA and provide inputs for measuring human disorderliness in maritime operations.     

基于ACT-R模型的汽车冷媒加注工序人因防错研究

为了对汽车装配中冷媒加注工序进行有效的人因防错设计,应用ACT-R认知模型分析操作行为的人因失误。对汽车冷媒加注操作进行ACT-R认知行为建模,并运用CogTool软件仿真,得出空调类型与车型不匹配的错误和管路辨识错误是冷媒加注工序中的主要人因失误,验证了ACT-R认知模型应用到冷媒加注操作人因失误分析的有效性。并结合防错设计的消除、检测、替代、简化、减少等思路,对冷媒加注生产工序进行了人因防错设计。企业的反馈评价说明了本防错设计的可行性和有效性。     

基于FTA的老年人APP交互设计

目的提升老年人对APP的满意度,帮助老年人更好地接受和使用APP。方法提出基于故障树分析(FTA)的老年人APP交互设计方法。首先通过焦点小组确定导致错误发生的原因并建立故障树,对错误发生的原因进行合理分类;随后对故障树进行定性定量分析,计算故障树的最小切集和错误发生的概率,找到导致头号事件发生的核心因素;接着进行重要度分析,计算构造重要度,根据构造重要度值对引起错误发生的基本事件进行排序,为设计改良提供理论上的优先顺序;最后以老年人医疗APP为研究案例进行设计改良,并对改良后的结果进行错误率验证。结论该方法可以有效地发现老年人操作APP时出现障碍的原因,不仅可以帮助设计师找到较为合理的改良方案,而且还可以使老年人获得良好的交互体验。     

Estimating and ranking the impact of human error roots on power grid maintenance group based on a combination of mathematical expectation,Shannon entropy,and TOPSIS

Due to the importance of electrical grid reliability, analysis and evaluation of human error in the maintenance of electrical networks should be also considered seriously. The root causes of these errors must be identified and prioritized to plan for human error reduction. One of the objectives of the present study is to identify and predict these roots for power transmission maintenance groups from organizational, job position, communication, individual, and supervision aspects along with the relationships between these factors. In particular, this paper demonstrates that supervisor behavior as an external factor has a significant effect on maintenance personnel error. For this reason, special attention has been paid to identifying and controlling human factors from a supervisory point of view in this study. This paper also provides a method for detecting the extent of the expected influence of these roots on each personnel, since human error has a random nature. This is done based on the law of mathematical expectation. Finally, a method is suggested to rank roots based on greater effectiveness and evaluate personnel with higher error expectations. The proposed method is a combination of intermediate methods, Shannon entropy, and technique for order of preference by similarity to ideal solution (TOPSIS). The origins of the four human errors between 2014 and 2018 related to the two experts of Fars Electricity Maintenance Contractor Company are compared by the proposed method.     

Management and Control of Aircraft Maintenance Error Based on the Coordination of the Human-machine-environment System

All of the forming of aircraft maintenance error is not because of human error,but the results of the interaction of multiple factors. So the new concept of the aircraft maintenance error is advanced in this paper in order to change the traditional conceptions of people. In the view of the human-machine-environment system,causes of the aircraft maintenance error have been analyzed in depth. And the error mode which is the most lively and prominent is laid special stress in analyzing. In the end the,methods and measures of preventing various modes of the aircraft maintenance error are given in the view of the human-machine-environment system.     

Application of three­dimensional numerical simulation to analysis of development of deformation zone at beginning of aluminium extrusion process

Abstract

Understanding the thermomechanical phenomena that occur during aluminium extrusion with respect to the variations of temperature, flow stress, strain, and strain rate is of importance for process optimisation. Conventional analytical methods are restricted to the steady state stage of the process and thus cannot provide an insight into the dynamic changes taking place during the initial stage. In the present work, three­dimensional simulations using the finite element method were carried out to analyse the development of the deformation zone at the die front and the temperature evolution, before the process attains the steady state. The analysis revealed that a change in friction factor at the billet/container interface from 0.3 to 0.9 enlarges the dead metal zone. However, its size appears unaffected by a change of die orifice shape from round to square at the same reduction ratio. The increase in friction results in an increase of initial extrusion load of about 6%.     

Quality risk analysis in a cGMP environment: multiple models for comprehensive failure mode identification during the computer system lifecycle

Pharmaceutical quality systems use various inputs to ensure product quality and prevent failures that might have patient consequences. These inputs are generally data from failures that have already occurred, for example process deviations or customer complaints. Risk analysis techniques are well-established in certain other industries and have become of interest to pharmaceutical manufacturers because they allow potential quality failures to be predicted and mitigating action taken in advance of their occurring. Failure mode and effects analysis (FMEA) is one such technique, and in this study it was applied to implement a computerized manufacturing execution system in a pharmaceutical manufacturing environment. After introduction, the system was monitored to detect failures that did occur and these were analyzed to determine why the risk analysis method failed to predict them. Application of FMEA in other industries has identified weaknesses in predicting certain error types, specifically its dependence on other techniques to model risk situations and its poor analysis of non-hardware risks, such as human error, and this was confirmed in this study. Hierarchical holographic modeling (HHM), a technique for identifying risk scenarios in wide-scope analyses, was applied subsequently and identified additional potential failure modes. The technique for human error rate prediction (THERP) has previously been used for the quantitative analysis of human error risk and the event tree from this technique was adapted and identified further human error scenarios. These were input to the FMEA for prioritization and mitigation, thereby strengthening the risk analysis in terms of failure modes considered.