Human error risk analysis in offshore emergencies

Human factors play an important role in the completion of emergency procedures. Human factors analysis is rooted in the concept that humans make errors, and the frequency and consequences of these errors are related to work environment, work culture, and procedures. This can be accounted for in the design of equipment, structures, processes, and procedures. As stress increases, the likelihood of human error also increases. Offshore installations are among the harshest and most stressful work environments in the world. The consequences of human error in an offshore emergency can be severe.A method has been developed to evaluate the risk of human error during offshore emergency musters. Obtaining empirical data was a difficult process, and often little information could be drawn from it. This was especially an issue in determining the consequences of failure to complete muster steps. Based on consequences from past incidents in the offshore industry and probabilities of human error, the level of risk and its tolerability are determined. Using the ARAMIS (accidental risk assessment methodology for industries) approach to safety barrier analysis, a protocol for choosing and evaluating safety measures to reduce and re-assess the risk was developed. The method is assessed using a case study, the Ocean Odyssey incident, to determine its effectiveness. The results of the methodology agree with the analysis of survivor experiences of the Ocean Odyssey incident.     

人为差错成因分析方法研究

控制甚至消除人为差错成因能从本质上降低人为差错的发生概率,从而提高系统安全性。因此,辨识和分析人为差错成因是一件非常必要而又十分重要的工作。针对该问题,在总结和分析现有的人为差错成因分析方法的基础上,提出了一种新的人为差错成因分析框架。在该框架中,将差错成因分为"操作者-系统-任务-环境-组织因素"5个方面进行分析,并提出了"从大类到小类"的层次化分析原则。为了尽量降低不同差错成因之间的关联,提出了以任务为中心,将差错成因分为任务相关和任务无关两大类因子的分类方式。最终共分析得出了34种不同的差错成因。该差错成因分类框架的提出,为人为差错概率量化以及差错规避措施的设计提供了依据。     

New considerations for SIL verification of functional safety fieldbus communication

Safety integrity level (SIL) verification of functional safety fieldbus communication is an essential part of SIL verification of safety instrumented system (SIS), and it requires quantifying residual error probability (RP) and residual error rate of function safety communication. The present quantification method of residual error rate uses RP of cyclic redundancy check (CRC) to approximately replace the total RP of functional safety communication. Since CRC only detects data integrity-related errors and CRC has intrinsically undetected error, some other residual errors are not being considered. This research found some residual errors of the present quantification method. Then, this research presents an extended new approach, which takes the found residual errors into account to determine more comprehensive and reasonable RP and residual error rate. From perspective of the composition of safety message, this research studies RPs of those controlling segments (sequence number, time expectation, etc.) to cover the found residual errors beyond CRC detection coverage, and the influences of insertion/masquerade errors and time window on RP are investigated. The results turn out these residual errors, especially insertion/masquerade errors, may have a great influence on quantification of residual error rate and SIL verification of functional safety communication, and they should be treated seriously.     

Method for identifying errors in chemical process development and design base on accidents knowledge

It has been claimed that the high accident rate in the chemical process industry is due to poor dissemination of accident knowledge that affects directly the level of learning from accidents. In response to this situation, this paper utilized past accident knowledge as a basis to develop a safety oriented design tool whereby the accident information were directly disseminated into plant design. The method was developed based on our previous accident analysis of design error in which the common design errors were ranked in accordance to their frequency and its origins during normal plant design project. Based on the design error ranking and its origin at a specific design phases, a method for design error detection is proposed. The method is expected to be able to identify the possible design error and its causes throughout chemical process development and design. The main objective is to trigger safe design thinking at the specific design phases so that appropriate action for risk reduction could be timely implemented. The Bhopal and BP Texas tragedies are used as case studies to test and verify the method. The proposed method can detect up to 74% of design errors.     

The paradoxes of almost totally safe transportation systems

Safety remains driven by a simple principle: complete elimination of technical breakdowns and human errors. This article tries to put this common sense approach back into perspective in the case of ultra-safe systems, where the safety record reaches the mythical barrier of one disastrous accident per 10 million events (10⁻⁷). Three messages are delivered: (1) the solutions aimed at improving safety depend on the global safety level of the system. When safety improves, the solutions used to improve the safety record should not be further optimised; they must continue to be implemented at present level (to maintain the safety health obtained), and supplemented further by new solutions (addition rather than optimisation rationale); (2) the maintenance and linear optimisation of solutions having dwindling effectiveness can result in a series of paradoxes eventually replacing the system at risk and jeopardising the safety record obtained in the first place; and (3) after quickly reviewing ambiguities in the definition of human error and the development of research in this area, this article shows, through recent industrial examples and surveys, that errors play an essential role in the acquisition and effectiveness of safety, at individual as well as collective levels. A truly ecological theory of human error is developed. Theories of error highlight the negative effects of an over-extensive linear extrapolation of protection measures. Similarly, it is argued that accepting the limitation of technical systems performance through the presence of a minimum breakdown and incident ‘noise’ could enhance safety by limiting the risks accepted. New research opportunities are outlined at the end of this paper, notably in the framework of systems now safe or ultra-safe.     

Allocation of performance shaping factors in the risk assessment of an offshore installation

Offshore oil production is one of the most important human productive activities. There are many risks associated with the process of constructing a subsea well, pumping oil to the platform, and transporting it to refineries via underwater pipes or oil tankers. All actions performed by workers in those operations are influenced by specific working conditions, involving the use of complex systems. Contextual factors such as high noise, low and high temperatures and hazardous chemicals are considered to be contributors to unsafe human actions in accident analysis and also give a basis for assessing human factors in safety analysis. Some failure modes are particularly dangerous and can result in severe accidents and damage to humans, the environment and material assets. Fires and explosions on oil rigs are some of the most devastating types of offshore accidents and can result in long-term consequences. The most typical root causes related to accidents include equipment failure, human error, environmental factors, work organization, training and, communication, among others. The principal objective of this study is to propose a methodological framework to identify the factors that affect the performance of operators of an offshore unit for oil processing and treatment. In this phase, an ergonomics approach based on operators' work analysis is used as a supporting tool. After identification of factors that affect the performance of operators, a decision-making model based on AHP (analytic hierarchy process) is applied to rank and weight the principal performance shaping factors (PSFs) that influence safe operations. The next step involves the use of the SHELLO model to group the main PSFs in elements named software, hardware, environment, liveware and organization. In the last phase, a relevant accident that occurred aboard a floating production storage and offloading (FPSO) vessel is analyzed. The allocation process of the factors that affect the operator's performance in risk assessment was developed through fuzzy logic and the ISO 17776 standard.     

基于HERA-JANUS模型的空管人误认知分析

空管人误分类分析是空管人误研究的基础。为了对管制员人误进行系统的分类研究,结合空管业务知识和认知心理学理论,对欧洲航空安全局和美国联邦航空局合作开发的HERA-JANUS模型的工作原理和流程进行较详细地分析。运用该方法模型,对我国一起空管不安全事件案例进行分析后得到3个由管制员所产生的人误差错,并对这3个人误差错分别从人误类型、人误认知、相关因素3方面进行详尽的分析研究,最后得出该不安全事件的21项人误结果。结果表明,HERA-JANUS模型能较全面地从深层次分析管制员的人误,其分类形式也便于开展空管人误统计。     

CREAM-based communication error analysis method (CEAM) for nuclear power plant operators’ communication

Communication error has been considered a primary cause of many incidents and accidents in the nuclear industry. In order to prevent these accidents, a method for the analysis of such communication errors is proposed here. This paper presents a qualitative and a quantitative method to analyze communication errors. The qualitative method focuses on finding a root cause of the communication error and predicting the type of communication error which could happen in nuclear power plants. We develop context conditions and antecedent-consequent links of influential factors related to communication errors. The quantitative analysis method focuses on estimating the probability of communication errors. To accomplish the quantification of communication errors, the Cognitive Speaking Process (CSP) is defined and a method to estimate the weighting factors and the probability is suggested. Finally, case studies conducted to validate the applicability of the proposed methods are detailed. From the results, we can foresee the effects of given plant conditions on communication errors and reduce the error occurrences.     

基于认知可靠性的飞行差错影响因素体系的构建

提高飞行员认知可靠性可以有效降低飞行差错发生概率。合理确定飞行差错影响因素有利于客观、快速地评估飞行差错,提高飞行中的安全性。基于人的认知可靠性建立P-D-A-F飞行认知可靠性模型分析飞行差错发生机理;并结合对人的认知可靠性影响因素分析结果,构建以心理、生理、外部为主要影响因素的飞行差错影响因素体系;运用Delphi法确定体系包含40个影响因子,并提出影响因子以独立或者联合影响的方式影响飞行差错。该影响因素体系可以应用于飞行差错分析与评估。     

施工中人因差错调查

人因差错是造成建筑工程施工事故的主要原因之一。目前国内建筑行业由于实际施工操作人员大多是农民工,对他们的技术培训常常是不够的,再加上部分施工企业管理水平较低,造成在施工中人因差错屡屡发生。要研究施工中人因差错发生的规律及其影响,首先必须对施工中的人因差错进行有效的调查。在重点介绍直接调查法和问卷调查法的含义、操作要点、优缺点与相应措施的基础上,笔者通过案例分析,探讨了在实际调查工作中如何有效地运用这些调查方法,获得人因差错真实准确的数据资料,为研究施工中人因差错发生的规律及其影响打好基础。最后以调查得到的混凝土施工中人因差错发生与影响的一些规律为依据,笔者提出了有关人因差错建模的建议。     

海洋钻井平台事故致因分析与评价指标研究

该文在广泛调研国内外已发生的海洋平台事故基础上,从人因失误、工艺设备、物料危险、管理缺陷和危险环境五个方面系统分析事故致因因素,提出海洋钻井平台事故致因评价框架,提出5个一级评价指标和24个二级评价指标,根据层次分析法,计算确定各指标的标准权重值.最后针对某在役海洋钻井平台,开展实例研究.为实际评价海洋钻井平台事故风险提供一种新方法,具有一定的实际应用价值.     

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.     

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.     

Revised fire consequence models for offshore quantitative risk assessment

Offshore oil and gas platforms are well known for their compact geometry, high degree of congestion, limited ventilation and difficult escape routes. A small mishap under such conditions can quickly escalate into a catastrophe. Among all the accidental process-related events occurring offshore, fire is the most frequently reported. It is, therefore, necessary to study the behavior of fires and quantity the hazards posed by them in order to complete a detailed quantitative risk assessment. While there are many consequence models available to predict fire hazards-varying from point source models to highly complex computational fluid dynamic models—only a few have been validated for the unique conditions found offshore.

In this paper, we have considered fire consequence modeling as a suite of sub-models such as individual fire models, radiation model, overpressure model, smoke and toxicity models and human impact models. This comprehensive suite of models was then revised by making the following modifications: (i) fire models: existing fire models have been reviewed and the ones most suitable for offshore conditions were selected; (ii) overpressure impact model: a model has been developed to quantify the overpressure effects from fires to investigate the possible damage from the hot combustion gases released in highly confined compartments; (iii) radiation model: instead of a point/area model, a multipoint grid-based model has been adopted for better modeling and analysis of radiation heat flux consequences. A comparison of the performance of the revised models with the ones used in a commercial software package for offshore risk assessment was also carried out and is discussed in the paper.     

Risk perception by offshore workers on UK oil and gas platforms

This paper reports the first investigation of risk perception by workers on offshore oil and gas installations on the UK Continental Shelf, following changes in offshore safety legislation in the wake of the Piper Alpha disaster in 1988. The Offshore Safety Case regulations (Health and Safety Executive, 1992, A Guide to the Offshore Installations (Safety Case) Regulations) put the onus on the operator to identify the major hazards and to reduce the risks to As Low As is Reasonably Practicable (ALARP). The regulations specifically state that Quantitative Risk Assessments (QRA) must be used when preparing the Safety Case. However, people do not use QRA when making everyday judgements about risk; they make subjective judgements known as risk perceptions, which are influenced by a number of different factors. This study was designed to complement the extensive QRA calculations that have already been carried out in the development of Safety Cases. The aim was to measure subjective risk perception in offshore personnel and examine how this relates to the more objective risk data available, namely accident records and QRA calculations. This paper describes the Offshore Risk Perception Questionnaire developed to collect the data and reports on UK offshore workers' perceptions of the risks associated with major and minor hazards, work tasks and other activities aboard production platforms.     

Determination of human error probabilities for offshore platform musters

The focus of this work is on prediction of human error probabilities during the process of emergency musters on offshore oil and gas production platforms. Due to a lack of human error databases, and in particular human error data for offshore platform musters, an expert judgment technique, the Success Likelihood Index Methodology (SLIM), was adopted as a vehicle to predict human error probabilities. Three muster scenarios of varying severity (man overboard, gas release, and fire and explosion) were studied in detail. A panel of 24 judges active in the offshore oil and gas industry provided data for both the weighting and rating of six performance shaping factors. These data were subsequently processed by means of SLIM to calculate the probability of success for 18 muster actions ranging from point of muster initiator to the final actions in the temporary safe refuge (TSR). The six performance shaping factors considered in this work were stress, complexity, training, experience, event factors and atmospheric factors.     

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。     

基于差错分类框架辨识人为差错

为解决人因可靠性分析中的人为差错辨识问题,提出新的工作流程。在该流程中,由人为差错引导词引导,以自问自答方式开展差错辨识工作。针对动作和决策2种差错类型,分别设计差错基本分类框架。其中,动作差错基本分类框架包括5个差错大类,10个差错小类;决策差错基本分类框架包括2个差错大类,10个差错小类。这些差错小类可作为差错辨识过程中的引导词。通过2个实例,演示这2个框架在差错辨识过程中的作用。演示结果表明,在人为差错引导词引导下开展差错辨识工作,更容易保证差错辨识结果的全面性和一致性。     

基于事故/事件的民机人因防错设计关键因素研究

针对民机人因防错设计对飞行安全的影响,从世界民航安全事故/事件数据库中筛选出92起典型的人为因素事故案例,采用基元事件分析法进行深度分析,提炼出民机人因防错设计需要考虑的重要设计因素,并建立重要设计因素集。基于系统工程学的“人机环”模型,结合国内外飞机设计相关标准,建立民机人因防错设计重要因素指标体系。运用模糊层次分析法对因素指标进行权重计算,确立影响飞行安全的14项人因防错设计关键因素,并针对这些关键因素提出民机人因防错设计通用要求,以期为民机人因防错设计满足初始适航要求提供参考。     

Confidence-based quantitative risk analysis for offshore accidental hydrocarbon release events

Quantitative risk analysis (QRA) has been widely used to conduct the assessment of offshore accidental risks. However, the accuracy and validity of QRA is significantly affected by uncertainties when subjective judgments are involved. Therefore, it is unrealistic to determine the probability of a hazardous event by using one single explicit value when safety experts have a relatively low confidence level in their judgments. This paper proposes a new methodology for incorporating uncertainties into conventional QRA using the concept of confidence level. Offshore hydrocarbon release hazards are focused on and a barrier and operational risk analysis (BORA-Release) method is selected as the basic model to illustrate the proposed methodology. A left–right (L–R) bell-shaped fuzzy number is employed and its membership curve is able to control its shape to represent different confidence levels. As to the complex geometry of the bell-shaped fuzzy number, an α-cut operation is introduced to conduct the arithmetic operations of the fuzzy number, and a defuzzification method with total integral value is chosen to match the α-cut operations and acquire complete information for the fuzzy numbers. In the meantime, an optimism index is used to describe the attitude of the decision-maker. One case study is provided in this paper to demonstrate the implementation of this method.