Safety and human factors considerations in control rooms of oil and gas pipeline systems: conceptual issues and practical observations.

All oil and gas pipeline systems are run by human operators (called controllers) who use computer-based workstations in control rooms to "control" pipelines. Several human factor elements could contribute to the lack of controller success in preventing or mitigating pipeline accidents/incidents. These elements exist in both the work environment and also in the computer system design/operation (such as data presentation and alarm configuration). Some work environment examples include shift hours, shift length, circadian rhythms, shift change-over processes, fatigue countermeasures, ergonomics factors, workplace distractions, and physical interaction with control system computers. The major objective of this paper is to demonstrate the critical effects of human and organizational factors and also to highlight the role of their interactions with automation (and automated devices) in the safe operation of complex, large-scale pipeline systems. A case study to demonstrate the critical role of human organizational factors in the control room of an oil and gas pipeline system is also presented.     

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.     

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。     

复杂人——机系统中的人因失误

随着人——机系统变得越来越多，装置的可靠性越来越高，人因失误已成为重要的潜在事故源。本文描述了复杂人——机系统的特征，探讨了该系统中人因失误的定义、分类、数据采集和事故模型。这些研究有助于对人因失误的预测、预防和减少。     

Human reliability analysis: A critique and review for managers

In running our increasingly complex business systems, formal risk analyses and risk management techniques are becoming more important part to managers: all managers, not just those charged with risk management. It is also becoming apparent that human behaviour is often a root or significant contributing cause of system failure. This latter observation is not novel; for more than 30 years it has been recognised that the role of human operations in safety critical systems is so important that they should be explicitly modelled as part of the risk assessment of plant operations. This has led to the development of a range of methods under the general heading of human reliability analysis (HRA) to account for the effects of human error in risk and reliability analysis. The modelling approaches used in HRA, however, tend to be focussed on easily describable sequential, generally low-level tasks, which are not the main source of systemic errors. Moreover, they focus on errors rather than the effects of all forms of human behaviour. In this paper we review and discuss HRA methodologies, arguing that there is a need for considerable further research and development before they meet the needs of modern risk and reliability analyses and are able to provide managers with the guidance they need to manage complex systems safely. We provide some suggestions for how work in this area should develop. But above all we seek to make the management community fully aware of assumptions implicit in human reliability analysis and its limitations.     

Overcoming the blame game to learn from major accidents: A systemic analysis of an Anhydrous Ammonia leakage accident

This article aims to demonstrate the need for changing the methods with which accidents are analyzed, if we truly wish to use what we uncover from them to learn and enrich our knowledge base of organizational management. The goal is to relinquish the broadly adopted and rather simplistic paradigm that accepts the search for human error and unsafe acts performed by workers, and produces “guilt diagnostics”. Instead, we use a systemic accident analysis methodology, based on the sociotechnical principle of understanding the real operating conditions in which accidents take place. In order to demonstrate the benefits of the theoretical framework, we compare the analyses of an Anhydrous Ammonia gas leakage accident in a fish processing plant using the traditional accident analysis model based on unsafe acts and the proposed systemic approach. The results favor the latter since it tends to be more reliable and offering useful recommendations to safety management processes, thus helping to prevent accidents, especially in complex systems.     

Incorporating organizational factors into probabilistic risk assessment of complex socio-technical systems: Principles and theoretical foundations

The current generation of Probabilistic Risk Analysis (PRA), particularly those for technical systems, does not include an explicit representation of the possible impacts of organization and management on the safety performance of equipment and personnel. There are a number of technical challenges in developing a predictive model of organizational safety performance. There is a need for a widely accepted and theoretically sound set of principles on which models of organizational influences could be developed and validated. As a result of a multidisciplinary effort, this paper explores the feasibility of developing such principles and proposes a set of principles for organizational safety risk analysis. Then, as a realization of the proposed modeling principles, a safety risk framework, named Socio-Technical Risk Analysis (SoTeRiA), is developed. SoTeRiA formally integrates the technical system risk models with the social (safety culture and safety climate) and structural (safety practices) aspects of safety prediction models, and provides a theoretical basis for the integration. A systematic view of safety culture and safety climate leaves an important gap in modeling complex system safety risk, and SoTeRiA, describing the relationship between these two concepts, bridges this gap. The framework explicitly recognizes the relationship among constructs at multiple levels of analysis, and extends the PRA framework to include the effects of organizational factors in a more comprehensive and defensible way.     

The role of situation awareness in accidents of large-scale technological systems

In the last two decades, several serious accidents at large-scale technological systems that have had grave consequences, such as that at Bhopal, have primarily been attributed to human error. However, further investigations have revealed that humans are not the primary cause of these accidents, but have inherited the problems and difficulties of working with complex systems created by engineers. The operators have to comprehend malfunctions in real time, respond quickly, and make rapid decisions to return operational units to normal conditions, but under these circumstances, the mental workload of operators rises sharply, and a mental workload that is too high increases the rate of error. Therefore, cognivitive human features such as situation awareness (SA)—one of the most important prerequisite for decision-making—should be considered and analyzed appropriately. This paper applys the SA Error Taxonomy methodology to analyze the role of SA in three different accidents: (1) A runaway chemical reaction at Institute, West Virginia killing two employees, injuring eight people, and requiring the evacuation of more than 40,000 residents adjacent to the facility, (2) The ignition of a vapor cloud at Bellwood, Illinois that killed one person, injured two employees, and caused significant business interruption, and (3) An explosion at Ontario, California injuring four workers and caused extensive damage to the facility. In addition, the paper presents certain requirements for cognitive operator support system development and operator training under abnormal situations to promote operators’ SA in the process industry.     

人为失误及其辨识技术的研究

随着机器设备的可靠性不断提高，人的可靠性分析研究日益得到重视。大部分事故是由于人为失误造成的。分析了人为失误与事故发生的关系，讨论了管理失误对系统安全的影响；讨论了人为失误辨识的作用，对人为失误率预测技术、通过失误建模系统、人为失误率评价和优化系统等几种的人为失误辨识技术进行了评述。指出了人为失误及其辨识技术的发展趋势和方向。     

From job-based to competency-based organizations

The efficacy of designing organizations around job structures is challenged. Although this approach has dominated the fields of organizational behavior and human resource management for decades, a number of forces have converged to suggest that a competency-based approach often is more appropriate. In the global competitive environment which large, complex organizations face, the competency-based approach and the capabilities that individuals need to acquire and develop should be the major focus. Reward systems, career tracks, selection systems, and the structure of organizations need to change to focus on competencies. The challenges and opportunities for research, theory, and practice development that a change to a competency-based approach raises are many and diverse. For example, new pay systems are needed, new selection systems are needed, indeed whole new concepts about what constitutes selection validity and career development are needed.     

决策树方法在高风险复杂技术系统组织因素量化中的应用

主要探讨运用决策树方法对高风险复杂技术系统组织因素量化的问题.对影响人误发生的组织文化、组织结构、规程、培训、组织沟通以及监督检查、组织决策7个因素按照好、一般、差3种表现形式分别进行了解释,画出了组织因素决策树例图.介绍了决策树量化的方法,给出了量化的公式和实例.     

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.     

Usage of human reliability quantification methods.

Human reliability quantification (HRQ) methods are becoming increasingly important in risk and accident assessment in systems these terms are usually related to (hi-tech industrial systems, including nuclear and chemical plants). These methods began to intensively develop after numerous accidents caused by human error or inadequate activity of people who controlled and managed complex technological processes. For already existing systems, but also for new ones, it is important to assess the possibility of an accident. Determination of possible preventive activities, which include the influence of human error on the safety of a system, is also required. These are the main goals of the HRQ method. Using Absolute Probability Judgment (APJ) and Success Likelihood Index Methods (SLIM) HRQ techniques in control and management centers in electro-power systems in Belgrade and railway traffic in Nis (both in Serbia and Montenegro) are shown in this paper.     

人员可靠性分析及人员可靠性数据管理系统研究

人员可靠性在系统可靠性计算中占的比重越来越大 ,人因失误事件的分析及其管理也成为安全管理的重要组成部分。为更加有效、准确地进行人员可靠性分析和人因失误事件的管理 ,提高系统的安全性 ,建立一个人员可靠性分析及人员可靠性数据管理系统是非常必要的 :首先为人员可靠性分析和人因事件管理提供一个有用的计算机辅助工具 ;再者通过建立具有一定规模的人员可靠性数据库 ,以便为今后进一步的研究提供良好的数据支持。笔者简述了该系统的一些基本原理和实现的主要功能。     

An integrated method for safety pre-warning of complex system

In large-scale and complex industrial systems, unplanned outages and hazardous accidents cause huge economic losses, environmental contamination, and human injuries, due to component degradation, exogenous changes, and operational mistakes. In order to ensure safety and increase operational performance and reliability of complex system, this study proposes an integrated method for safety pre-warning to analyze the current safety state of each component and the whole system indicating hidden hazards and potential consequence, and furthermore predict future degradation trends in the long term.The work presented here describes the rationale and implementation of the integrated method incorporating HAZOP study, degradation process modeling, dynamic Bayesian network construction, condition monitoring, safety assessment and prognosis steps, taking advantage of the priori knowledge of the interactions and dependencies among components and the environment, the relationships between hazard causes and effects, and the use of historical failure data and online real-time data from condition monitoring.The application of the integrated safety pre-warning approach described here to the specific example of the gas turbine compressor system demonstrates how each phase of the presented method contributes to completion of the safety pre-warning system development in a systematic way.     

航空人为差错事故/事件分析(ECAR)模型研究

为深入研究航空人为差错事故/事件的影响因素,以人为差错相关理论为基础,对比分析几种典型的人为差错分析模型;通过借鉴ECCAIRS分析框架,并在基元事件分析(EEAM)逻辑和CCAR396部的分类方法基础上,构建航空人为差错事故/事件分析(ECAR)模型,它从事件层、描述层、原因层和组织因素与改进建议层,分析航空事故和不安全事件的人为差错。此外,还将组织因素概念引入该模型。     

核电厂人因事故预防的定量化决策

人因事故的分析与预防是核电厂安全运行和管理的重要内容。笔者提出的系统安全性层次分析法主要从两种角度考虑系统的安全性:专家能力权值和安全性矩阵的建立。采用专家判断矩阵确定事故原因对系统安全性的重要度排序。举例某核电厂事故定量分析进行说明,在对事故进行原因分析基础上,构建事故影响因素层次模型,利用层次分析法分析得出事故原因重要度排序由高到低依次为组织管理、操作人员、人机界面、培训与设备状态,并据此提出了相应的预防与改进措施,为安全性要求较高的复杂工业系统提供事故预防的定量化决策依据。     

高处坠落事故的人因失误与干预策略研究

为系统分析导致高处坠落人因事故的产生机理,通过统计152起建筑工程高处坠落事故的调查与分析报告,从组织影响、安全监管、不安全行为前提条件和不安全行为等4个层次,辨识影响高处坠落事故的人为失误因素,修订人为因素分析与分类系统框架（HFACS）。设计高处坠落人因失误调查问卷,开展一线高处作业人员问卷调查,建立高处坠落人因失误结构方程模型,对导致高处坠落事故的人为失误因素进行路径分析。结果表明:各潜在因素间均呈正相关,且高处坠落人因失误事故的关键路径为资源管理不到位→安全监督培训不充分→班组管理不良→操作违规。综合各因素间相关性,提出了针对性的预防高处坠落事故的人因干预策略。     

Synergism of Ergonomics,Safety, and Quality—A Behavioral Cybernetic Analysis

Abstract

This report extends a control systems or cybernetic model of behavior to the behavior of groups of many individuals—organizations and institutions—operating together with technology as complex sociotechnical (ST) systems. The premise is that the level of quality in performance of a complex ST system is predicated upon the degree to which its organizational design incorporates elements of a closed-loop behavioral control system: control goals and objectives, sensory receptors, sensory feedback, learning and memory, effectors, and sensory feedback control. From a control systems perspective, ergonomics is essential to effective organizational self-regulation. If working conditions are poorly designed, work performance and safety and quality outcomes cannot be closely controlled. Conversely, as shown by field evidence, good design promotes synergism between ergonomics, safety, and quality as a closed-loop consequence of effective employee and organizational self-control of system performance, safety, and quality.     

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。