Assessment of human reliability based on evaluation of plant experience: requirements and implementation

A major problem in assessment of human failures in probabilistic safety assessment is the lack of empirical data needed for human reliability analysis (HRA). This problem is aggravated by the fact that different HRA methods use different parameters for the assessment and that HRA is currently enforced to provide data and methods for assessment of human reliability in new technical environments such as computerized control rooms, in accident management situations, or in low-power and shut down situations. Plant experience is one source to deal with this problem. In this paper, a method is presented that describes how plant experience about human failures and human performance may be used to support the process of analyzing and assessing human reliability. Based on considerations of requirements of HRA, a method is presented first which is able to describe and analyze human interactions that were observed within events. Implementation of the approach as a database application is outlined. Second, the main results of the application of the method to 165 boiling water reactor events are presented. Observed influencing factors on human performance are discussed; estimates for probabilities are calculated and compared with the data tables of the THERP handbook. An outline is given for using the presented method for the analysis of cognitive errors or organizational aspects.     

基于全决策树的空管人因可靠性研究

随着民用航空运输业的迅猛发展和空中交通流量的不断增长,民用航空器的数量显著增加,对空中交通管制的工作提出了更高的要求和挑战。作为民用航空运输系统中三大安全支柱之一的空中交通管制,长久以来,事故和事件80%以上是由人为表现不佳引起的,人为因素已经成为影响安全和工作效率的最大因素。本文分析了全决策树分析方法(the Entire Decision Tree,EDT)、模型原理和分析步骤,研究了影响空管人因可靠性的相关因素,提出了基于全决策树的空管人因可靠性的方法,对提高空管工作的效率和安全具有参考价值。     

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.     

A method of human reliability analysis and quantification for space missions based on a Bayesian network and the cognitive reliability and error analysis method

Analyses of human reliability during manned spaceflight are crucial because human error can easily arise in the extreme environment of space and may pose a great potential risk to the mission. Although various approaches exist for human reliability analysis (HRA), all these approaches are based on human behavior on the ground. Thus, to appropriately analyze human reliability during spaceflight, this paper proposes a space‐based HRA method of quantifying the human error probability (HEP) for space missions. Instead of ground‐based performance shaping factors (PSFs), this study addresses PSFs specific to the space environment, and a corresponding evaluation system is integrated into the proposed approach to fully consider space mission characteristics. A Bayesian network is constructed based on the cognitive reliability and error analysis method (CREAM) to model these space‐based PSFs and their dependencies. By incorporating the Bayesian network, the proposed approach transforms the HEP estimation procedure into a probabilistic calculation, thereby overcoming the shortcomings of traditional HRA methods in addressing the uncertainty of the complex space environment. More importantly, by acquiring more information, the HEP estimates can be dynamically updated by means of this probabilistic calculation. By studying 2 examples and evaluating the HEPs for an International Space Station ingress procedure, the feasibility and superiority of the developed approach are validated both mathematically and in a practical scenario.     

Human-centered modeling in human reliability analysis: some trends based on case studies

As an informal working group of researchers from France, Germany and The Netherlands created in 1993, the EARTH association is investigating significant subjects in the field of human reliability analysis (HRA). Our initial review of cases from nuclear operating experience showed that decision-based unrequired actions (DUA) contribute to risk significantly on the one hand. On the other hand, our evaluation of current HRA methods showed that these methods do not cover such actions adequately. Especially, practice-oriented guidelines for their predictive identification are lacking. We assumed that a basic cause for such difficulties was that these methods actually use a limited representation of the stimulus-organism-response (SOR) paradigm. We proposed a human-centered model, which better highlights the active role of the operators and the importance of their culture, attitudes and goals. This orientation was encouraged by our review of current HRA research activities. We therefore decided to envisage progress by identifying cognitive tendencies in the context of operating and simulator experience. For this purpose, advanced approaches for retrospective event analysis were discussed. Some orientations for improvements were proposed. By analyzing cases, various cognitive tendencies were identified, together with useful information about their context. Some of them match psychological findings already published in the literature, some of them are not covered adequately by the literature that we reviewed. Finally, this exploratory study shows that contextual and case-illustrated findings about cognitive tendencies provide useful help for the predictive identification of DUA in HRA. More research should be carried out to complement our findings and elaborate more detailed and systematic guidelines for using them in HRA studies.     

Analysis of operators' performance under emergencies using a training simulator of the nuclear power plant

It is well known that there are many factors that affect the reliability of nuclear power plants (NPPs). Among them, human reliability has been considered one of the most important factors. Thus, not only in order to quantify human reliability but also to identify main causes that can degrade human reliability, various kinds of human reliability analysis (HRA) methods have been suggested and utilized in many countries. However, to perform HRA more appropriately, it is necessary to collect plant-specific or domain-specific human performance data: especially for emergencies: because they can be used to generate requisite information for HRA. From this point of view, simulator studies under emergencies may be considered important sources for obtaining human performance data.In this study, the performance data of operating crews in coping with emergencies of the reference NPP have been collected and analyzed to develop human performance database (HPDB). Since the number of collected records is 112, it can be said that extracted/analyzed results included in HPDB are statistically meaningful. Therefore, HPDB can be used not only for HRA input data but also for multiple purposes such as improving emergency operating procedures and developing advanced HRA methods.     

Reliability analysis and operator modelling

The paper considers the state of operator modelling in reliability analysis. Operator models are needed in reliability analysis because operators are needed in process control systems. HRA methods must therefore be able to account both for human performance variability and for the dynamics of the interaction. A selected set of first generation HRA approaches is briefly described in terms of the operator model they use, their classification principle, and the actual method they propose. In addition, two examples of second generation methods are also considered. It is concluded that first generation HRA methods generally have very simplistic operator models, either referring to the time-reliability relationship or to elementary information processing concepts. It is argued that second generation HRA methods must recognise that cognition is embedded in a context, and be able to account for that in the way human reliability is analysed and assessed.     

Human reliability analysis—why not turn to the human factors community?

In response to the Dougherty thesis that contemporary human reliability analysis (HRA) methods are inadequate, this paper proposes that credible assessments of these HRA methods adequacy can be obtained only by means of their full exploitation by human factors specialists as part of the probabilistic risk assessment (PRA) process. The paper traces the history of human factors in PRA. It concludes that regarding PRA, only peripheral attention has been given to human factors; further that there has been almost a total absence of human factors specialists involved in the PRA process. The paper introduces and discusses a recent US Nuclear Regulatory Commission research initiative on a task analysis-linked evaluation technique (TALENT) concept for integrating human factors expertise into the PRA process, and fully exploiting state-of-knowledge HRA methods and data. The paper concludes that by means of TALENT implementation: (1) more credible assessments of HRA methods adequacy can be made, and (2) more realistic estimates of the overall impact of human error on complex high reliability systems' reliability and risk can be achieved.     

The systematic integration of human factors into safety analyses: An integrated engineering approach

The performance of the human reliability analysis (HRA) and integration of its outcomes into quantitative risk assessment schemes remains quite a difficult and complex task to perform. Even worse is the assessment of organisational reliability assessment. The reasons of this difficulty mainly lay on the absence of a generically accepted paradigm that enables engineers to include systematically human and organisational factors (H&OF) into the analysis. Broadly speaking, engineering approaches very often account for error of omission forgetting the errors of commission (EOC), and, on top of that, they do not make any macro distinction between pre- and post-initiating human failures. This paper offers a paradigm on how to integrate H&OF into safety analysis by means of the recursive operability analysis (ROA), which has been adapted to accommodate H&OF, and renamed integrated recursive operability analysis (IROA). By means of a practical example, the method will illustrate how to account for H&OF in a systematic and consistent manner using an engineering approach. The paper will even provide a paradigm for the construction of integrated fault trees consistent with the IROA framework.     

Another view of the state of human reliability analysis (HRA)

This note discusses the author's view of the guest editorial by E. M. Dougherty, Jr. This author considers that HRA exhibits the normal progression of science in which breakthroughs are infrequent. Progress has been made in the field of HRA and has been due to the efforts of persons such as Swain, Rasmussen, Wreathall and others.This note tries to clarify the underlying concepts of the human cognitive reliability (HCR) correlation and answer some of the misconceptions about HCR given in the guest editorial. Additionally, the note touches on the usefulness of simulator results for calculation and estimation for HRA purposes. The note draws attention to the fact that the methods advanced in EPRI NP-6560 are not the same as those in NUREG/CR-4550. Finally, the note calls for the organization of a meeting for the various specialists to discuss their HRA approaches in front of their peers.     

Advances in human reliability analysis methodology. Part II: PC-based HRA software

This paper, in two parts, summarizes some of the advancements made in the area of human reliability analysis (HRA) in the past decade. The paper focuses on the HRA program sponsored by the Electric Power Research Institute (EPRI) since 1982 as part of an effort to better understand the role of operators in safe operation of nuclear power plants (NPPs) and advance the state-of-the-art in HRA. Many technical reports have been published and numerous papers have been presented in national and international conferences on the various EPRI HRA projects. This paper is an attempt to summarize a decade of research in this area with an emphasis on recent advancements made towards development of a simulator-based HRA methodology using data from NPP simulators. HRA frameworks, models, data and computer codes are discussed, and areas for further research are pointed out. Part I herein covers the frameworks, models and data. Part II of the paper (see this issue, pp. 57–66) discusses the PC-based software developed to facilitate the process of simulator data collection and analysis as well as the assessment of human reliability.     

Thermal fatigue and corrosion fatigue in heat recovery area wall side tubes

In this paper, findings of visual inspections, chemical analysis on deposits, metallurgical examinations and creep analysis on the failed SA210-A1 heat recovery area (HRA) wall side tubes of a boiler unit are presented. The investigations were carried out following two boiler tube failures at heat recovery areas involving the left hand side (LHS) and right hand side (RHS) side wall tubes. Findings from the microscopic examinations are used to support the investigation in determining the failure mechanisms. The first failure at LHS HRA side wall tube is identified due to thermal fatigue while the second failure is as a result of combination of the corrosion fatigue, thermal fatigue and creep damage. Recommendations are made to reduce unavailability of the boiler unit due to the HRA side wall tube failures.     

An extended CREAM model based on analytic network process under the type-2 fuzzy environment for human reliability analysis in the high-speed train operation

Human error is one of the largest contributing factors to unsafe operation and accidents in high-speed train operation. As a well-known second-generation human reliability analysis (HRA) technique, the cognitive reliability and error analysis method (CREAM) has been introduced to address HRA problems in various fields. Nevertheless, current CREAM models are insufficient to deal with the HRA problem that need to consider the interdependencies between the Common Performance Conditions (CPCs) and determine the weights of these CPCs, simultaneously. Hence, the purpose of this paper is to develop a hybrid HRA model by integrating CREAM, the interval type-2 fuzzy sets, and analytic network process (ANP) to overcome this drawback. Firstly, the interval type-2 fuzzy sets are utilized to express the highly uncertain information of CPCs. Secondly, the ANP is incorporated into the CREAM to depict the interdependencies between the CPCs and determine their weights. Furthermore, human error probability (HEP) can be calculated based on the obtained weights. Finally, an illustrative example of the HRA problem in high-speed train operation is proposed to demonstrate the application and validity of the proposed HRA model. The results indicate that experts prefer to express their preferences by fuzzy sets rather than crisp values, and the interdependences between the CPCs can be better depicted in the proposed model.     

应激情景下数字化系统操纵员认知行为失误分析

人在应激情景下的认知行为特点是第二代人因可靠性分析方法(HRA)的重点研究领域.应激因子是许多人因可靠性分析模型重点考虑的行为形成因子(PSFs)之一.本文提出基于认知资源理论的应激因子作用模型作为统一的分析框架,初步探讨了应激因子对人的认知行为失误的作用机制.运用该模型从认知资源的角度分析了数字化主控室的新特征可能导致的人因失误.     

Review of advances in human reliability analysis of errors of commission, Part 1: EOC identification

In close connection with examples relevant to contemporary probabilistic safety assessment (PSA), a review of advances in human reliability analysis (HRA) of post-initiator errors of commission (EOCs), i.e. inappropriate actions under abnormal operating conditions, has been carried out. The review comprises both EOC identification (part 1) and quantification (part 2); part 1 is presented in this article. Emerging HRA methods addressing the problem of EOC identification are: A Technique for Human Event Analysis (ATHEANA), the EOC HRA method developed by Gesellschaft für Anlagen- und Reaktorsicherheit (GRS), the Misdiagnosis Tree Analysis (MDTA) method, and the Commission Errors Search and Assessment (CESA) method. Most of the EOCs referred to in predictive studies comprise the stop of running or the inhibition of anticipated functions; a few comprise the start of a function. The CESA search scheme—which proceeds from possible operator actions to the affected systems to scenarios and uses procedures and importance measures as key sources of input information—provides a formalized way for identifying relatively important scenarios with EOC opportunities. In the implementation however, attention should be paid regarding EOCs associated with familiar but non-procedural actions and EOCs leading to failures of manually initiated safety functions.     

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.     

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.     

人的可靠性综合分析模式及应用

提高系统可靠性的关键步骤是提高系统中人的可靠性,这需要对人的可靠性进行分析。当前分析人的可靠性主要依靠运用各类HRA模型,这些模型各有优缺点。为了研究航空人为差错,选取了具有代表性的3个HRA模型,对人的可靠性分析模型THERP（technique for human error rate prediction)、CREAM（cognitive reliability and error analysis method)、IDAC(information decision and action)进行了分析。将3种模型进行比较,找出它们的优劣之处,结合3种模型的优点,建立了以THERP模型、CREAM模型以及IDAC模型为主体的人的可靠性综合分析模式,并将该分析模式在航空人为差错分析上进行了应用,并给出实例说明该分析模式的应用。     

A Review of Cognitive Models in Human Reliability Analysis

Human error behavior is determined by both environmental and human factors. In particular, psychological and spiritual factors have a decisive impact on human errors. The human cognitive model not only makes a sound exposition of the generation process and mechanism of human erroneous actions but also improves the accuracy and credibility of human reliability analysis (HRA). Therefore, it helps effectively avoid and prevent human errors in industrial fields. This paper highlights the significant role that the cognitive model has played in HRA. Then, based on an analysis of the nature of human behavior and the classifications of common human errors, several typical cognitive models are summarized in the areas of ergonomics, behavioral science, and cognitive engineering, including a cognitive model related to process, an information‐processing model, a decision‐making and problem‐solving process model, and a cognitive simulation model based on computer technology. Then, cognitive models and the corresponding HRA methods that are applied in the fields of reliability engineering, safety engineering, and risk assessment are reviewed. Finally, some directions and challenges are proposed for the future research of cognitive models applied in HRA methods based on the discussion of current cognitive models used in HRA methods. Copyright © 2016 John Wiley & Sons, Ltd.