Human error data collection as a precursor to the development of a human reliability assessment capability in air traffic management

Quantified risk and safety assessments are now required for safety cases for European air traffic management (ATM) services. Since ATM is highly human-dependent for its safety, this suggests a need for formal human reliability assessment (HRA), as carried out in other industries such as nuclear power. Since the fundamental aspect of HRA is human error data, in the form of human error probabilities (HEPs), it was decided to take a first step towards development of an ATM HRA approach by deriving some HEPs in an ATM context.This paper reports a study, which collected HEPs via analysing the results of a real-time simulation involving air traffic controllers (ATCOs) and pilots, with a focus on communication errors. This study did indeed derive HEPs that were found to be concordant with other known communication human error data. This is a first step, and shows promise for HRA in ATM, since HEPs have been derived which could be used in safety assessments, although these HEPs are for only one (albeit critical) aspect of ATCOs’ tasks (communications). The paper discusses options and potential ways forward for the development of a full HRA capability in ATM.     

飞行机组人为差错风险分析方法研究

提出了一个新的飞行机组人为差错风险评估方法F HECA,识别和分析航空公司的机组人为差错风险。该方法在对机组人为差错类型进行总结和分类的基础上,选取人为差错严重度作为评价指标,将该指标中的3个变量人为差错概率、人为差错后果严重度、人为差错影响概率与灰色综合评价法结合,定量评估机组人为差错的严重度,实现机组人为差错风险评估。通过实例分析验证此方法可用于分析机组人为差错风险,为飞行训练和飞行操作手册内容的改进提供技术支持,是民航人为因素研究中可借鉴的一种方法。     

Human errors versus stress

This paper discusses human errors in a man-machine system with the dependence on different stresses. A method is presented for defining ranges of normal stress values, based on the construction of the membership function from the fuzzy set theory. This method is applied to a stress analysis for a sample of station foremen in the railway traffic system of Slovenia. The results of this analysis are given.     

Reliability of drivers in urban intersections

The concept of human reliability has been widely used in industrial settings by human factors experts to optimise the person-task fit. Reliability is estimated by the probability that a task will successfully be completed by personnel in a given stage of system operation. Human Reliability Analysis (HRA) is a technique used to calculate human error probabilities as the ratio of errors committed to the number of opportunities for that error. To transfer this notion to the measurement of car driver reliability the following components are necessary: a taxonomy of driving tasks, a definition of correct behaviour in each of these tasks, a list of errors as deviations from the correct actions and an adequate observation method to register errors and opportunities for these errors. Use of the SAFE-task analysis procedure recently made it possible to derive driver errors directly from the normative analysis of behavioural requirements. Driver reliability estimates could be used to compare groups of tasks (e.g. different types of intersections with their respective regulations) as well as groups of drivers’ or individual drivers’ aptitudes. This approach was tested in a field study with 62 drivers of different age groups. The subjects drove an instrumented car and had to complete an urban test route, the main features of which were 18 intersections representing six different driving tasks. The subjects were accompanied by two trained observers who recorded driver errors using standardized observation sheets. Results indicate that error indices often vary between both the age group of drivers and the type of driving task. The highest error indices occurred in the non-signalised intersection tasks and the roundabout, which exactly equals the corresponding ratings of task complexity from the SAFE analysis. A comparison of age groups clearly shows the disadvantage of older drivers, whose error indices in nearly all tasks are significantly higher than those of the other groups. The vast majority of these errors could be explained by high task load in the intersections, as they represent difficult tasks. The discussion shows how reliability estimates can be used in a constructive way to propose changes in car design, intersection layout and regulation as well as driver training.     

A non-probabilistic prospective and retrospective human reliability analysis method — application to railway system

The paper describes a method to analyze human reliability. It defines human reliability as a degradation function related to deviations of both human behavioral state and system state due to this behavior. The method is called ACIH, a French acronym for Analysis of Consequences of Human Unreliability. It is a non-probabilistic approach, which aims at identifying both tolerable and intolerable sets of human behavioral degradations, which may affect the system safety. The corresponding scenarios of degradations are characterized by a behavioral model of unreliability including three main factors: acquisition related factors, problem solving related factors, and action related factors. Both prospective and retrospective analyses are taken into account to specify error prevention tools. They are applied to the railway system.     

计及人因可靠性的变电站自动化系统失效风险评估

目前对于变电站自动化系统的可靠性研究鲜有涉及人为因素的定量影响,而许多电网事故是由人为失误引起的,因此提出了一种计及人因可靠性的变电站自动化系统失效风险评估方法。首先根据工作人员所处场景采用层次分析法-成功似然指数法评估人为失效概率以此修正设备故障概率,其次基于IEC-61850的功能分解对自动化系统各种功能的失效风险进行评估,最终融合为系统失效风险,以此描述当前系统可靠性,为调度部门决策提供指导。算例结果表明,人为因素对于系统失效风险有着较大的影响,计及人因可靠性可更为客观地描述系统风险,为调度操作人员提供风险预警。     

Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways     

风、列车作用下斜拉桥索-梁相关振动对拉索疲劳可靠性的影响

以实际大跨度斜拉桥为研究对象,研究了随机风、列车作用下发生的索-梁相关振动对拉索疲劳可靠性的影响。使用编制的动力有限元计算程序,建立了大跨度铁路斜拉桥全桥3维精细有限元模型,计算了斜拉桥全桥在风、列车动力作用下的振动响应,分析了全桥索-梁相关振动的特性。建立了列车交通荷载概率模型,根据桥位处风速统计数据资料建立了桥梁的风荷载概率模型,对拉索的应力谱进行了计算。依据损伤理论,使用Monte-Carlo方法开展了拉索在风、列车动力作用下的疲劳可靠度分析。研究结果表明:在斜拉桥日常运营状态中,风、列车作用下索-梁相关振动不会导致拉索共振,索-梁相关振动是拉索疲劳可靠性下降的主要原因;对于拉索在长期动力荷载下的疲劳失效概率,风场作用占比很小,列车作用占比较大;各个拉索的成桥状态索力影响了列车作用下的拉索应力幅,进一步影响了斜拉桥在长期动力作用下拉索的疲劳可靠性。     

车辆运行状态测试设备间相对误差率分析新方法

车辆运行状态安全测试设备的一致性、准确性是铁路智能运输系统中防止车辆超载引发事故的关键。文中提出了一种新的车辆运行状态测试设备间相对误差率分析方法,克服了现有随机抽样法所引起的数据局限性,获得了蕴含丰富现场工况的数据源,运用最大熵原理导出了相对误差率的分布模型;实现了多系统数据的匹配校验,纠正了系统中的误传数据,同时评定了速度、天气、车种各因素对相对误差率的影响。实验和实际应用的结果表明,该法解决了目前车辆运行状态安全测试设备间相对误差率分析方法的匮乏问题,从理论上验证了设备的一致性、可靠性。     

Human Reliability Analysis of Roof Bolting Operation in Underground Coal Mines

Investigations have shown that human error is the most common cause of roof bolting injuries. Human error probability estimation has become a critical issue for human reliability analysis (HRA) of roof bolting operation. Specialist judgment plays a crucial role in quantifying human error probability in the field because of limited availability of empirical data. However, the aggregation of specialist judgment is typically not carried out in a formal way in HRA. In this paper, an approach to combine Bayesian methodology and the success likelihood index method was to build a computable model using information from specialists for HRA of roof bolting operation. A numerical example was used to illustrate the application of the proposed methodology. Copyright © 2015 John Wiley & Sons, Ltd.     

A new model to optimize the human reliability based on CREAM and group decision making

The Cognitive Reliability and Error Analysis Method (CREAM) represents one of the second-generation approaches to human reliability assessment, taking into account the influence of environmental conditions on human error probability (HEP). In the context of CREAM, the Common Performance Conditions (CPCs) influence error probabilities. Since not all CPCs have equal impacts, this study employs the Bayesian Best Worst Method (BWM), a novel approach in group decision-making, to assign weights to these factors. Subsequently, two techniques based on basic CREAM are proposed. The current control mode is determined in the first technique according to the experts' opinions. Then the probability of human error is calculated based on the amount of control. It is possible to provide solutions for improving control mode, based on obtained results. Therefore, in this study, the second method has been used to make suggestions to enhance human reliability. For this purpose, in the second technique, an optimization problem is formulated to select the best applicable programs for managers to enhance human reliability. The proposed bi-objective model tries to increase the reliability of human resources by reducing human error and costs. The proposed bi-objective model seeks to bolster the reliability of human resources by concurrently minimizing HEP and associated costs. The efficiency of the presented methods is verified through a case study in the control room of the cement factory. The results of the first technique reveal an opportunistic control mode with a corresponding HEP of 0.0198. On the other hand, the outcomes of our proposed model underscore the greater impact of improving CPC levels in reducing the probability of human error. Ultimately, the practical programs derived from our mathematical model provide decision-makers with valuable insights to reduce the probability of human error to a mere 0.000172 through the transition from opportunistic to strategic control.     

Reliability of a Multi‐State Computer Network Through k Minimal Paths Within Tolerable Error Rate and Time Threshold

A computer system is usually modeled as a network topology where each branch denotes a transmission medium and each vertex represents a station of servers. Each branch has multiple capacities/states due to failure, partial failure, and maintenance. Such a network is named a multi‐state computer network (MSCN). From the viewpoint of quality management, transmission error rate and transmission time are both critical performance indicators to assess Internet quality for system managers and customers. Within both tolerable error rate and time threshold, the addressed problem is concentrated on an MSCN for computing the probability that d units of data can be sent through multiple minimal paths simultaneously. Such a probability is named system reliability. A solution procedure including an efficient algorithm based on MPs is proposed to derive the lower boundary vectors (LBVs) meeting the requirements. Then system reliability, which is represented as the probability of union of subsets, can be subsequently evaluated by the LBVs. Copyright © 2015 John Wiley & Sons, Ltd.     

A digital filter-based approach to the remote condition monitoring of railway turnouts

Railway operations in Europe have changed dramatically since the early 1990s, partly as a result of new European Union Directives. Performance targets have become more and more exacting, due to reductions in state support for railways and the need to increasing traffic. More intensive operations also place greater demands on the hardware of the railway. This is true for both rolling stock and infrastructure subsystems and components, particularly so in the case of the latter where the time available for maintenance is being reduced. The authors of this paper focus on the railway infrastructure, and more specifically on points. These are critical elements whose reliability is key to the operation of the whole system. Using intelligent monitoring systems, it is possible to predict problems and enable quick recovery before component failures disrupt operations. The authors have studied the application of remote condition monitoring to point mechanisms and their operation, and have identified algorithms which may be used to identify incipient failures. In this paper, the authors propose a Kalman filter for the linear discrete data filtering problem encountered when using current sensor data in a point condition monitoring system. The reason for applying Kalman filtering in this study was to increase the reliability of the model presented to the rule-based decision mechanism.     

Human communication, mutual awareness and system dependability. Lessons learnt from air-traffic control field studies

The dependability of many complex and critical systems strongly relies on human operators, both through human reliability and human ability to handle adequately the unexpected events. This paper focuses on ergonomics field studies of air traffic control activities, and more specifically on the analyses of communication within teams of controllers. We show how operators use spontaneously the natural redundancy and diversity of human communication (multimodality, addressing features,…), so as to successfully maintain mutual awareness. This is the key for reliable cooperation, for the sake of global system dependability that rests on mechanisms such as error detection, recovery, and prevention (by anticipation and regulation). This study helps in providing specifications for the design of systems efficiently supporting both human cooperation and human ability to contribute to dependability.     

A Hybrid Probabilistic Model for Evaluating and Simulating Human Error in Industrial Emergency Conditions (HEIE)

Over the years, many techniques have been developed for human reliability analysis (HRA). The main weakness of traditional HRA approaches is the use of a simple classification scheme without a link to a model of cognition in terms of mental processes. The present work is an attempt in this direction through a particular hybrid probabilistic model. The human error in industrial emergency model aims to develop an integrated methodological approach useful in critical infrastructures during an emergency condition. The proposed method, starting from the integration of existing techniques, develops a very flexible tool, able to take into account the main external and internal factors responsible of human error in emergency conditions. The model is able to estimate the evolution of human behavior and error following the evolution of the emergency scenario. The final result is a simulation model that calculates the contextualized human error probability, through which it is possible to estimate a realistic and detailed scenario of the conditions during the emergency management.     

ZG230-450铸钢的重构疲劳可靠性S-N曲线

给定若干概率水平的常规疲劳可靠性曲线只能做相应概率水平的疲劳设计与寿命预测,要实现任意可靠性水平的疲劳设计、寿命预测和可靠性评定,需要重构全概率疲劳可靠性S-N曲线。首先应用Monte Carlo模拟技术在可接受的误差范围重构了铁道车辆ZG230-450车轮铸钢的疲劳极限和成组法S-N数据。然后应用广义极大似然法测定了其中短寿命范围的可靠性S-N曲线。最后应用概率疲劳极限外推法获得了该材料中短和长寿命范围的合理疲劳概率S-N曲线。并进一步发展了适于车辆结构用万公里单位表征的可靠性曲线。应用该曲线可实现任意可靠性水平的疲劳可靠性设计、寿命预测和可靠性评价。     

The task demands‐resources method: A new approach to human reliability analysis from a psychological perspective

This study proposes a new approach to human reliability analysis (HRA) by introducing the occupational stress model in human resources management. Most existing HRA methods are restricted to a given set of risk factors in the task context, which are often called performance shaping factors (PSFs), and they are built on the causal relationship between PSFs and human performance, with little concern for the psychological factors that drive human behavior. We argue that a well‐developed occupational stress model that incorporates comprehensive working conditions and focuses on psychological factors offers us a new perspective to evaluate human reliability. The proposed approach, namely, the task demands‐resources (TD‐R) method, considers that the PSFs, in the task context, can be categorized into two different groups: task demands and task resources. These two PSF groups can both motivate and stress the operators during the task, thereby influencing their performances. Based on the theoretical framework of the TD‐R method, we also designed a probabilistic model linking motivational intensity to human error probability (HEP) under different stress levels. A human reliability experiment has been conducted to validate the effectiveness and flexibility of the TD‐R method. The experiment results showed that the TD‐R method could produce a meaningful explanation for the operators' performances and provide a quantification result for HEP.     

基于车桥耦合随机振动分析的钢桥疲劳可靠度评估

发展了一种基于车桥耦合系统随机振动分析的铁路钢桥疲劳可靠度评估方法,建立车桥耦合系统模型,选取车速和轨道不平顺作为基本随机变量进行随机振动分析,以此确定桥梁构件等效疲劳应力幅及其循环次数的概率模型。在此基础上,建立基于S-N曲线法的疲劳极限状态函数并进行疲劳可靠度分析。以一座铁路下承式钢桁梁桥为例进行了疲劳可靠度评估,并讨论了车速及轨道平顺性对构件疲劳可靠性的影响。结果表明:该文方法可有效用于铁路钢桥疲劳可靠度评估;受车速及轨道不平顺随机性的影响,列车引起的桥梁构件等效疲劳应力幅及其循环次数均具有一定的不确定性,应视为随机变量,二者可采用对数正态分布表示;车速和轨道不平顺可显著影响桥梁构件的疲劳可靠性,疲劳关键构件的可靠度指标随着轨道平顺性增强而提高。     

Fatigue strength analysis of welded joints in closed steel sections in rail vehicles

A great need exists for practicability and reliability analyses of the various dimensioning concepts in railway vehicle production, as currently parts are commonly sized according to the nominal stress concept. Although Finite Element Analysis is used for the dimensioning of parts according to the nominal stress concept, no use is made of the locally resolved information from these calculation methods. Concepts based on local stress are highly applicable, as the Finite Element Analysis allows detailed modelling of critical areas of parts.     

车辆行驶对高层建筑微振动影响的试验研究

由于交通车辆引起的建筑物振动对强度和安全的影响通常可以忽略不计 ,这类振动没有受到足够的重视。然而 ,对交通干线附近建筑内的精密仪器 ,车辆引起的楼板微振动却是一个不可忽略的因素。本文实际测量分析了某三面紧邻交通干线的高层建筑振动状态 ,研究了轻轨列车行驶对高层建筑振动的影响 ,发现轻轨列车和重型汽车通过时 ,大楼的振动明显增大 ,可能导致部分仪器的测量误差增大。