A methodology to model causal relationships on offshore safety assessment focusing on human and organizational factors

INTRODUCTION: Focusing on people and organizations, this paper aims to contribute to offshore safety assessment by proposing a methodology to model causal relationships. METHOD: The methodology is proposed in a general sense that it will be capable of accommodating modeling of multiple risk factors considered in offshore operations and will have the ability to deal with different types of data that may come from different resources. Reason's "Swiss cheese" model is used to form a generic offshore safety assessment framework, and Bayesian Network (BN) is tailored to fit into the framework to construct a causal relationship model. The proposed framework uses a five-level-structure model to address latent failures within the causal sequence of events. The five levels include Root causes level, Trigger events level, Incidents level, Accidents level, and Consequences level. To analyze and model a specified offshore installation safety, a BN model was established following the guideline of the proposed five-level framework. A range of events was specified, and the related prior and conditional probabilities regarding the BN model were assigned based on the inherent characteristics of each event. RESULTS: This paper shows that Reason's "Swiss cheese" model and BN can be jointly used in offshore safety assessment. On the one hand, the five-level conceptual model is enhanced by BNs that are capable of providing graphical demonstration of inter-relationships as well as calculating numerical values of occurrence likelihood for each failure event. Bayesian inference mechanism also makes it possible to monitor how a safety situation changes when information flow travel forwards and backwards within the networks. On the other hand, BN modeling relies heavily on experts' personal experiences and is therefore highly domain specific. IMPACT ON INDUSTRY: "Swiss cheese" model is such a theoretic framework that it is based on solid behavioral theory and therefore can be used to provide industry with a roadmap for BN modeling and implications. A case study of the collision risk between a Floating Production, Storage and Offloading (FPSO) unit and authorized vessels caused by human and organizational factors (HOFs) during operations is used to illustrate an industrial application of the proposed methodology.     

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。     

高风险系统组织因素分类与绩效评价

在收集以组织绩效评价、人的可靠性和人误分析为目的的两类组织因素分类的基础上,结合问卷调查,并依据建立的概念上的组织因素分类框架,从组织的目标和战略、组织结构、资源、规程、管理功能、培训、交流、组织文化等方面确立组织因素分类指标,基本克服了传统的组织因素分类缺陷。同时,依据组织因素的分类,考虑到组织绩效评价的复杂性和不确定性,采用模糊决策方法对某组织的绩效进行评价,识别出该组织现存的主要缺陷:组织管理方面的问题以及组织的结构设计不太合理等问题。     

组织定向的人因失误因果模型及影响关系研究

为了更好地从源头上预防人因失误,首先,基于系统理论发展一个组织定向人因失误的"结构-行为"因果模型,包括组织子模型、情境状态子模型、个体因素子模型以及人因失误子模型。然后,分析模型中各子模型之间以及其因素类别之间的直接和间接影响关系,如模型中各层级之间的因果关系:组织因素→情境状态因素→直接触发人因失误的个体因素→人的认知行为失误。最后,基于事件报告分析、专家意见和文献资料,并依据建立的4种影响类型(I,C,A,N)识别具体情境环境与人因失误或认知行为之间的影响关系。分析结果表明,情境环境因素对人因失误的影响非常复杂,不同的情境环境因素对同一人因失误可能产生不同类型的影响,同一情境环境因素对不同的人因失误可能产生不同类型的影响。     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

船舶溢油应急反应人的可靠性分析研究

为减小船舶溢油事故应急反应人员失误概率,提升应急处置效果,在对应急人员可靠性主要影响因素识别的基础上,利用模糊贝叶斯网络(BN)建立船舶溢油应急人的可靠性分析(HRA)模型,将应急反应流程抽象为可进行概率推算的BN,实现单个应急任务和全过程人的可靠性的量化评估,并依据该模型对一起船舶溢油事故进行实例研究。结果表明,首先模糊集值专家评估较好地解决应急人员可靠性情境依赖性强,难以量化评估的问题;其次,BN卓越的概率推理性能实现由单个应急任务向全过程人的可靠性的推算;最后得到应急反应人的可靠性主要取决于关键应急任务的完成情况和相关情境因素的影响。     

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%。     

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.     

基于BN-CREAM的深水井控压井作业风险诱因研究

深水井控压井作业是有效控制溢流演化为井喷事故的二级井控工艺屏障。为提高深水井控压井作业可靠性,采用 BN-CREAM方法对其风险诱因进行研究。结合深水井控压井作业特点,考虑共因失效等因素,采用贝叶斯网络方法建立深 水井控压井作业风险演化模型。应用人因可靠性分析CREAM法计算深水压井人因失误先验概率,参考海洋可靠性数据手 册OREDA确定深水井控设备失效先验概率。依托贝叶斯网络的逆向推理能力辨识压井作业的主要风险节点,从而实现对 深水井控压井作业风险诱因的有效预测和评估。研究表明:深水井控压井作业共包含6个关键风险根节点,且压井作业人 因可靠性要低于设备可靠性;3级子节点“压井方法选择不合理”对深水压井作业的成功起到至关重要的作用,需进一 步开展风险分析研究。     

人的失误理论研究进展

人的失误理论研究已进入结合认知心理学并以人的失误动态过程为研究热点的阶段。笔者回顾了人的失误理论研究的进展,讨论了相关的人的认知行为类型、认知失误的基本概念和人的失误模型。例如适用于不同情景和应用条件的几种模型:刺激-调制-响应(S-O-R)模型;失误的决策阶梯(Step-ladder)模型;通用GEMS模型以及Worledge认知模型。由于人的行为的复杂性和难以预测性造成了人的可靠性分析(HRA)的困难,因此,对人的行为的深入了解必须从人的行为特性及其规律性入手,将人的可靠性分析与行为科学理论结合起来,揭示人的失误发生的内在规律。与此同时,重点分析了概率安全评价技术(PSA)中如何对人的失误事件进行定量估计;如何考虑人的心理因素影响的几种重要的人的失误理论模型,并对今后这该领域中的研究方向进行了讨论。     

A human factors and reliability approach to clinical risk management: Evidence from Italian cases

Similarly to the industrial sector in the late 1980s, nowadays leading organizations in the healthcare sector acknowledge the fact that human errors, adverse events and system failures must be managed and controlled. Whilst Human Reliability Analysis (HRA) has been well-accepted and integrated into safety management processes in other industries, the application of such error techniques to the problem of managing the associated risks in healthcare is rare. The main purpose of this research is to analyse clinical risk management (CRM) and patient safety improvement in Italian healthcare organizations, through human factors and human reliability theories. In particular, the specific objectives are to explore the Italian state-of-the-art in CRM, with regard to organizational and managerial issues; to identify and verify the factors influencing the growth and sharing of the safety culture and to understand and describe the possibility of transferring human reliability methodologies and theories to the domain of healthcare.Six case studies belonging to the Italian scenario have been performed, in order to describe the Italian healthcare system and to identify the key influencing factors of CRM policies.Results obtained from within and cross-case analysis give an empirical contribution to the recent introduction of CRM in the Italian context and a theoretical contribution referring to the framework used to analyse CRM in healthcare organizations, and to the indications which emerged on the key factors influencing CRM.     

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.     

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.     

基于STPA和模糊BN的装配式建筑吊装施工安全风险分析

为有效评估装配式建筑吊装施工中的安全风险状态,识别关键风险因素,运用系统理论过程分析方法(STPA)构建吊装施工过程中的控制反馈结构,识别导致危险的不安全控制行为,确定不安全控制行为的致因因素;基于风险因素间的关联关系构建贝叶斯网络(BN)模型,推理计算装配式建筑吊装施工安全风险状态概率,并结合反向诊断推理分析影响安全事故的风险因素;通过敏感性分析,识别装配式建筑吊装施工安全中的关键风险因素。结果表明：装配式建筑吊装施工安全风险处于低风险状态;起重机械超负荷运行、现场安全管理不到位和吊索吊具存在缺陷等因素是影响装配式建筑吊装施工安全风险的关键风险因素。     

Analysis of train derailments and collisions to identify leading causes of loss incidents in rail transport of dangerous goods in Canada

The Canadian railway industry has improved safety performance in the last decade as measured by freight loss incidents per billion gross ton-miles. Further improvements in safety performance require a deeper analysis of the leading causes to identify weaknesses in implementing safety systems. In this paper, we classify the causes of railway loss incidents using a Safety Management System (SMS) framework to identify system weaknesses. The role of human factors is further analyzed through the Human Factors Analysis and Classification System (HFACS) approach. For this, we utilized data from 42 main track derailments and collisions involving the transport of dangerous goods in Canada between 2007 and 2018, which have been investigated by the Transportation Safety Board of Canada in detail. Associations between adjacent sub-categories of the HFACS framework are analyzed to identify any interdependency that exists between active and latent errors using a Chi-square test and Kruskal's lambda analysis. Furthermore, we implement the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method and the Analytical Network Process (ANP) to identify causal relationships between different sub-categories of the HFACS framework and calculate the weighted influence of each sub-category on main track derailments and collisions. Finally, a comparison is made between this work and others', which have analyzed human factors in the railway industry. There is good agreement between the results of these studies that highlight the importance of supervisory and organizational factors in the prevention of railway loss incidents. Based on these findings, we make recommendations to reduce railway loss incidents.     

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。     

Organizational influence on working people's occupational noise protection in Hong Kong

INTRODUCTION: While there is some evidence of the influences of personal knowledge and organizational factors on workers' hearing protection, a causal model examining relationships between these variables is lacking. METHOD: To create and test such a model, this study collected data from 1,701 workers in Hong Kong through a random sample telephone survey. RESULTS: Fitting the model to the data revealed that organizational regulation of occupational noise protection was a root cause of workers' protective behavior, whereas workers knowledge about the protection exhibited only a minimal effect. CONCLUSIONS: These findings cast doubt on the significance of personal knowledge as a unique factor contributing to noise protection. The study also finds that organizational regulation was predictable by a number of organizational and industrial factors. IMPACT ON INDUSTRY: To prevent occupational deafness, organizational regulation accompanied by regular inspection and a norm of noise protection is important.     

Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment

To address human error in system reliability, Human Reliability Analysis (HRA) is an essential issue. Human Error Assessment and Reduction Technique (HEART) as a rather straightforward technique for HRA has successfully been used in many areas to predict human error probability (HEP). However, knowledge acquisition of experts during assessed proportion of affect (APOA) calculation is subjected to vagueness and ambiguity. To overcome this challenge, in this paper Intuitionistic Fuzzy (IF) set due to their advantage to represent more fuzzy information than a classical fuzzy set adopted through APOA calculation. To demonstrate this hybrid approach short for, IF-HEART, the furnace start-up operation is handled, since analysis shows that most of explosions and losses occur during furnace start-ups operation. Further, a sensitivity analysis is carried out to approve the proposed integrated approach. In addition to its academic contribution, the results of the paper enable to improve the overall safety level of a furnace by taking into account potential human error.     

海洋石油轮班作业风险定量分析方法研究

长期以来,海洋石油领域风险研究主要集中在对设施的潜在失效概率和后果研究方面,而对于人员可靠性及风险管理方面的研究较弱。然而,据统计资料显示,海上设施在其生命周期内的设计、建造和生产作业等各个阶段中发生的事故大多与人为错误和组织错误（HOE）有关联。在海洋工程领域,开展人员可靠性分析（HRA）的研究工作具有重要意义。根据海上作业的特殊性及轮班制度的特点,推导出轮班风险的定量分析公式,据此计算出每个工作日轮班风险的相对大小,然后结合我国海上作业的实际情况,对影响轮班风险的可变因素进行了敏感性分析,为风险控制与管理提供参考。