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.     

人的可靠性分析:历史、需求和进展

人的可靠性分析 (HRA)是人机工程、安全科学极为关注的问题。近年来 ,该领域的理论研究和应用技术发展很快 ,尤其将认知科学与人的失误的研究相结合 ,从失误模型到计算方法都更加与现实情景相吻合。笔者介绍了HRA的发展历史和相关的第一代HRA计算方法及其特点 ,并且就HRA在我国核电领域中的应用状况和前景进行了探讨 ,重点介绍了国际原子能机构赞助的中国核电厂操纵员可靠性研究项目 ,其成果对于进一步完善安全管理和提高我国核电厂人员可靠性提供了科学的依据和借鉴经验。     

基于人因失误率预测法改进的事故后人因可靠性分析技术

人因可靠性分析是概率风险分析的重要组成部分,事故后人因事件分析是人因可靠性分析的核心内容.工程应用中的人因可靠性分析技术应在满足分析准确性需求的基础上尽可能简单与规范.本文分析了人因失误率预测法(THERP)的主要不足及事故序列评估程序人因可靠性分析技术(ASEP HRA)所做出的重要改进,描述了事故后ASEP HRA在工程应用中的基本程序,给出了一个应用实例.     

On the operator action analysis to reduce operational risk in research reactors

Human errors during operation and the resulting increase in operational risk are major concerns for nuclear reactors, just as they are for all industries. Additionally, human reliability analysis together with probabilistic risk analysis is a key element in reducing operational risk. The purpose of this paper is to analyze human reliability using appropriate methods for the probabilistic representation and calculation of human error to be used alongside probabilistic risk analysis in order to reduce the operational risk of the reactor operation. We present a technique for human error rate prediction and standardized plant analysis risk. Human reliability methods have been utilized to quantify different categories of human errors, which have been applied extensively to nuclear power plants. The Tehran research reactor is selected here as a case study, and after consultation with reactor operators and engineers human errors have been identified and adequate performance shaping factors assigned in order to calculate accurate probabilities of human failure.     

复杂工业系统中班组人因失误分析

在复杂工业系统中 ,人因可靠性分析 (HRA)是预防和减少人因失误的有效方法。人在复杂工业系统中的生产活动 ,往往是由组织中班组成员集体完成的 ,完整的HRA必须充分考虑班组人误的产生。班组人误的产生有其自身的规律 ,如何合理地定义人员行为形成因子 (PSFs)是班组人因失误分析的难点 ,也是班组人因失误分析的重要手段 ,被广泛应用在核电厂 ,航空和造船工业领域的事故分析中。笔者详细分析和探讨了班组人因失误的定义、产生过程及相关的人的行为形成因子 ,以期能使大规模工业系统中的人因失误分析更加合理和完善。     

民航安全中人的因素研究方法综述

分析民航业中人的因素研究方法,指出其存在的不足。在此基础上,对核工业中成功应用的人的可靠性分析技术进行系统的研究。结合其优势,提出在民航安全工作中进行人的可靠性研究的观点。并将民航业与核工业中的多项内容进行对比,论证研究其可行性。为民航安全中人的因素研究提供新的理论指导和可靠的数据支持,最终使人因分析结果全面、深入和准确。     

Application of CREAM human reliability model to cargo loading process of LPG tankers

The storage and handling processes of liquefied petroleum gas (LPG) constitutes a complex operational environment in the maritime mode of transportation. The LPG cargo is carried by specially designed ships called LPG tankers. The LPG cargo loading and discharging operations have always potential hazards. Thus, the crew on-board LPG tankers should be fully aware of operational risks during the cargo handling process, which includes various critical tasks such as drying, inerting, gassing-up, cooling, and reliquefaction. During these stages, human reliability (operation without failure) plays a crucial role in sustainable transportation of cargo. Human reliability analysis (HRA), related to various parameters such as the human factor, technology, and ergonomics, is always a critical consideration as regards maritime safety and environment. The main focus of the research is to systematically predict human error potentials for designated tasks and to determine the required safety control levels on-board LPG ships. The paper adopted CREAM (Cognitive reliability and error analysis method) basic and extended versions in order to assess human reliability along with the cargo loading process on-board LPG tanker ships. Specifically, the model is demonstrated with an operational case study. Consequently, the research provides should contribute to maritime safety at sea and prevention of human injury and loss of life on-board LPG ship.     

基于人误系统复合状态(MSHES)的人误防范理论研究

评析国内外以第一代人因可靠性分析(静态)、第二代人因可靠性分析(动态)为主体形成的人误防范理论和方法;针对目前不能量化人的生理、认知、心理等相关非结构性和非确定性参数和数据的"瓶颈",建立基于人-机-环系统业务流程的人误系统复合状态(Multiplex State ofHumanErrors System,MSHES)结构模型;探求运用粗糙集数据挖掘,对资深专业人员的经验规则信息、人因事故或事件分析的信息,挖掘人因层次结构中的根因与人误层次结构中的差错之间的关联关系,构建基于规则的人误防范专家系统结构模型;探究人的风险性评估和人误防范理论。     

核电厂HRA定性分析

人因可靠性分析(HRA)是核电厂概率安全评价(PSA)的重要组成部分,定性评价对核电厂庞大的数据进行筛选和分析,是HRA的基础和出发点.本文介绍了核电厂HRA定性分析的目的、原则、方法和程序,并以压水堆核电厂蒸汽发生器传热管破裂(SGTR)为具体实例进行说明.     

核电站事故前人因可靠性分析方法

人因可靠性分析 (HRA)已成为概率安全分析 (PSA)必不可少的内容 ,事故前人因事件可靠性分析对有效预防维修、调校工作中的人因失误有着重要作用 ,是人因可靠性分析的重要组成部分 ,对PSA最终计算结果有重要影响。笔者结合核电站人因可靠性分析的实际需求 ,运用了以THERP为主的人因失误概率评价方法 ,创建了事故前人因事件分析的基本程序、方法及分析文档模式 ,表述了程序化的事故前人因事件分析模式 ,为我国核电站事故前人因可靠性分析提供了完整和有效的分析方法 ,并有效用于秦山核电站的PSA。     

A taxonomy of performance influencing factors for human reliability analysis of emergency tasks

This paper introduces the process for, and the result of, the selection of performance influencing factors (PIFs) for the use in human reliability analysis (HRA) of emergency tasks in nuclear power plants. The approach taken in this study largely consists of three steps. First, a full-set PIF system is constructed from the collection and review of existing PIF taxonomies. Secondly, PIF candidates are selected from the full-set PIF system, considering the major characteristics of emergency situations and the basic criteria of PIF for use in HRA. Finally, a set of PIFs is established by structuring representative PIFs and their detailed subitems from the candidates. As a result, a set of PIFs comprised of the 11 representative PIFs and 39 subitems was developed.     

Fuzzy logic-based approach for identifying the risk importance of human error

In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by “human error”. There are uncertainties in the traditional human error risk assessment (e.g. HECA) due to the uncertainties and imprecisions in Human Error Probability (HEP), Error-Effect Probability (EEP) and Error Consequence Severity (ECS). While fuzzy logic can deal with uncertainty and imprecision. It is an efficient tool for solving problems where knowledge uncertainty may occur. The purpose of this paper is to develop a new Fuzzy Human Error Risk Assessment Methodology (FHERAM) for determining Human Error Risk Importance (HERI) as a function of HEP, EEP and ECS. The modeling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs (i.e. HEP, EEP, and ECS) and outputs (i.e. HERI) of a risk assessment system in the form of IF–THEN rules. It is implemented on fuzzy logic toolbox of MATLAB using Mamdani techniques. A case example is presented to demonstrate the proposed approach. Results show that the method is more realistic than the traditional ones, and it is practicable and valuable.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

Issues of the Human Reliability Analysis in the Context of Probabilistic Safety Studies

This article addresses methodological issues of the human reliability analysis (HRA) in the context of probabilistic safety studies. Several conventional HRA techniques, more often used for the evaluation of the human error probabilities (HEPs), have been classified. A taxonomy of human actions, failure events, and related factors is outlined in order to distinguish action phases, human behavior types and incorrect outputs (errors of omission or commission), error types (slips, lapses, and mistakes), and performance-shaping factors (PSFs) influencing the human performance. A tree is proposed to facilitate the selection of a specific method for the evaluation of human reliability with regard to attributes of the situation analyzed. A software system based on the expert system technology to facilitate and document PSA and HRA is outlined. At the end of the article some research challenges in the domain are discussed.     

HRA in China: Model and data

Human reliability analysis (HRA) is generally viewed as quite an important part in probabilistic safety assessment (PSA). In this paper, a THERP + HCR HRA model is presented to model the operators’ post-accident behavior in Chinese nuclear power plants. The paper shows how the model is structured and how to consider and acquire the corresponding data, including HCR data modification and HRA event tree data. A case study is presented to make an illustration.     

A framework for human error risk analysis of coal mine emergency evacuation in China

Evacuation from underground coal mine in emergency as soon as possible makes the difference between life and death. Human factors have an important impact on a successful evacuation, but literature review shows that there is a lack of consideration of human error risk during coal mine emergency evacuation in China. To address the above problems, in this paper, we established a framework for human error risk analysis of coal mine emergency evacuation, consisting of scenario and task analysis, risk assessment and risk reduction. A general evacuation procedure which is applicable for different causes is detailed through the scenario and task analysis. A new method based on expert judgment, named OGI-Model, is proposed to evaluate the reliability of human safety barrier. In this new approach, human safety barrier is divided into three sub-barriers, i.e., organization safety sub-barrier (OSSB), group safety sub-barrier (GSSB), and individual safety sub-barrier (ISSB). Each sub-barrier consists of a series of concrete measures against specific evacuation actions. An example is provided in this paper to demonstrate the use of this framework and its effectiveness.     

基于RBF的起重作业岗位人因可靠性预测

为提高起重作业可靠性,防止人因失误酿成事故,针对人因失误的随机性、模糊性和不确定性特点,提出运用具有非线性映射能力和容错能力的径向基函数(RBF)神经网络,分析人因失误非线性动力学过程。以起重机操作岗位作为人因可靠性分析(HRA)实例,首先,建立基于"作业人员、交流界面、作业环境、作业特性、作业组织"的人因可靠性预测指标体系,并对指标进行量化;其次,根据人因可靠性原理,统计出人因失误次数,给出人因失误率;最后,通过对"人的疲劳和情绪、交流通道、作业复杂程度和时间裕度、照明环境和风力影响、工作强度和安全监管"等因素的分析,构建基于RBF的起重机操作岗位人因可靠性预测分析神经网络模型。分析结果表明,RBF预测分析同时包含人的操作可靠性与认知可靠性,预测结果同现场实际观测结果的符合度达到92.0%。     

Determination of human error probabilities in maintenance procedures of a pump

The “human factor” constitutes an important role in the prediction of safe operation of a facility. Hence, information about human capacities and behaviours should be applied methodically to increase the safety of a systematic process. This paper provides an analysis of human factors in pre- and post-maintenance operations. For possible failure scenarios, this paper considers the procedures for removing process equipment from service (pre-maintenance) and returning the component to service (post-maintenance). In this study, a pump is used as the test example. For each scenario, the human error probability (HEP) is calculated for each activity, using the Human Error Assessment and Reduction Technique (HEART) which is commonly implemented technique in industry, can also be applied in the analyses of safety cases. HEART is a reliable technique for comparing HEP and its approach is based on the degree of error recovery. Consequences are also assessed for each activity in this methodology. The final value of risk for each activity is assigned by combining error likelihood and related consequences. When the calculated risk is beyond acceptable levels, risk management strategies are provided to increase the safety of the maintenance procedures. The most probable human errors for a considered case study are related to the activities of “draining lines” and “open valves”. These two activities have high HEPs, which are 9.57E−01 and 9.62E−01, respectively.     

Layer of Protection Analysis – Quantifying human performance in initiating events and independent protection layers

Layer of Protection Analysis (LOPA) is widely used within the process industries as a simplified method to address risks and determine the sufficiency of protection layers. LOPA brings a consistent approach with added objectivity and a greater degree of understanding of the scenarios and risks as compared to purely qualitative studies such as Process Hazard Analyses. LOPA can be used to address a wide range of risk issues and serves as a highly effective aid to decision making.Incorporation of human performance within LOPA is recognized as an important, though often challenging, aspect of the analysis. The human role in potential initiating events or within human independent protection layers is important throughout the process industries, and becomes even more critical for batch processing facilities and in non-routine operations. The human role is key to process safety and the control of risks, necessitating the inclusion and quantification of human actions in independent protection layers for most companies. Human activities as potential initiating events and human performance within independent protection layers are reviewed and methods for quantification outlined. An extension into Human Reliability Analysis (HRA) is provided, including methods to develop Human Error Probabilities specific to the process safety culture and operations at a given plant site.     

PSA中人因失误模型化研究

主要研究PSA模型如何考虑人因失误的影响,系统地提出如何在电厂系统模型中建立相对应的人因失误分析模型。利用事件树把系统故障和人因失误相结合的方法,探讨如何最大可能地真实描述事故后的操纵员行为,确定重要人因事件发展序列以及根据系统响应确定合理可分析的人因题头,建立完整的人因失误模型化的体系,并以实例说明具体分析过程。此项研究能够较好地描述硬件可靠性和人因可靠性之间的关联关系,降低HRA出力并满足PSA对于事故后人员行为的概率分析需求。