A risk perspective suitable for resilience engineering

In recent years, resilience engineering has been given considerable attention among safety researchers and analysts. The area represents a new way of thinking about safety. Whereas conventional risk management approaches are based on hindsight knowledge, failure reporting and risk assessments calculating historical data-based probabilities, resilience engineering looks for ways to enhance the ability of organisations to be resilient in the sense that they recognise, adapt to and absorb variations, changes, disturbances, disruptions and surprises. The implications of this shift in thinking are many. We focus in this paper on the understanding of the risk concept and how risk can be assessed and treated. The traditional ways of looking at risk are not suitable for use in resilience engineering, but other risk perspectives exist. A main purpose of this paper is to draw attention to such perspectives, in particular one category of perspectives where probability is replaced by uncertainty in the definition of risk. We argue that the basic ideas of resilience engineering can be supported by such risk perspectives.     

Understanding and assessing safety culture through the lens of organizational management of uncertainty

The management of uncertainties is discussed as a key challenge for organizations and two approaches to handling uncertainties are introduced, i.e. minimizing uncertainties versus coping with uncertainties. The analysis of rules as for instance laid out in standard operating procedures is suggested as one method for identifying the approach to uncertainty management chosen in a particular organization. Given advantages and disadvantages of both approaches to uncertainty management, loose coupling is discussed as a way of balancing the two approaches and a conceptualization of safety culture as a means for loose coupling is proposed. One of the central controversies underlying discussions on designing organizations for safety, i.e. the relationship between autonomy and safety, is expanded upon in order to deepend the understanding of different design strategies within the framework of uncertainty management. Finally, it is argued that the role and importance of safety culture differs depending on the chosen approach to uncertainty management, requiring that any safety culture assessment is preceeded by an assessment of the fit between the uncertainties an organization is confronted with and the chosen forms of handling these uncertainties. Methods for carrying out these assessments are suggested.     

An approach to estimating the individual risk for toxic-gas releases using the load-resistance model

A new approach to quantify the uncertainty of the individual risk for toxic releases is presented in this paper. The individual risk is defined as the probability of fatality per year. The probability of fatality is calculated by a classical load-resistance model based on reliability (survivability) theory. The load effect is defined as the concentration intensity to which a human is exposed. Furthermore, the resistance is defined as the human tolerance to a certain concentration load in this study. The Monte Carlo method is used to obtain the probability distributions of outputs (the load effect and resistance) propagated from the uncertainties of the input variables. The fatality probability exceeding a limit state can then be obtained by comparing pairs of samples from the load effect and the resistance distributions. The separation of sampling from the load and resistance distributions is also proposed to allow more efficient calculation than that achieved by the classical Monte Carlo method. The analytical risk estimates computed by the load-resistance model are compared to conventional risk estimates that correspond to the upper-end percentile of the load-effect distribution. A case study shows that the conventional risk estimates can be directed to wrong decisions when the load-effect distribution has upper-end tail heaviness.     

建设工程重大危险源界定和辨识标准研究

以重大危险源为研究对象,对当前重大危险源辨识标准进行研讨,指出建设工程重大危险源管理中存在的问题;从风险角度,结合建设工程实际,提出建设工程重大危险源的定义;从事故后果和发生概率两个角度,提出12个辨识因子,建立建设工程重大危险源辨识标准。以实例对某桥梁一处模板工程重大危险源进行辨识,验证了该标准的可行性,为建设工程安全风险管理提供一种新方法。     

Analyzing system safety and risks under uncertainty using a bow-tie diagram: An innovative approach

A bow-tie diagram combines a fault tree and an event tree to represent the risk control parameters on a common platform for mitigating an accident. Quantitative analysis of a bow-tie is still a major challenge since it follows the traditional assumptions of fault and event tree analyses. The assumptions consider the crisp probabilities and “independent” relationships for the input events. The crisp probabilities for the input events are often missing or hard to come by, which introduces data uncertainty. The assumption of “independence” introduces model uncertainty. Elicitation of expert's knowledge for the missing data may provide an alternative; however, such knowledge incorporates uncertainties and may undermine the credibility of risk analysis.This paper attempts to accommodate the expert's knowledge to overcome missing data and incorporate fuzzy set and evidence theory to assess the uncertainties. Further, dependency coefficient-based fuzzy and evidence theory approaches have been developed to address the model uncertainty for bow-tie analysis. In addition, a method of sensitivity analysis is proposed to predict the most contributing input events in the bow-tie analysis. To demonstrate the utility of the approaches in industrial application, a bow-tie diagram of the BP Texas City accident is developed and analyzed.     

On the critique of Beck’s view on risk and risk analysis

Ulrich Beck’s stand on risk and risk analysis has been challenged by many researchers. In this paper we look closer into some of the arguments used, with a main focus on the fundamental analysis carried out by Campbell and Currie. These two authors argue that Beck’s criticisms of the theory and practice of risk analysis are groundless: Beck’s understanding of what risk is, is badly flawed, and he misunderstands and distorts the use of probability in risk analysis. However, the analysis of Campbell and Currie is based on a set of premises, for example that risk is a function of probability and harm, and that risk really exists and one can be wrong about risk. Although such ideas are common, they can be challenged, and in the literature a number of alternative perspectives have been suggested. The purpose of the present paper is to study Beck’s stand on risk analysis and the related critique of Campbell and Currie and others, in view of some of these alternative perspectives on risk. To what extent is the critique then justified? The paper concludes that the case raised against Beck’s view is still strong and relevant, but has to be nuanced with respect to some important issues, for example concerning the distinction between belief and truth when it comes to risk. Allowing for spacious interpretations of some of Beck’s theses, the paper provides strengthened support for Beck’s view on these points.     

Careers as repositories of knowledge: A new perspective on boundaryless careers

This paper argues for a reconceptualization of careers as repositories of knowledge. Careers are visualized as accumulation of information and knowledge rather than simply progressions of work experiences. This definition is considered in light of theories which characterize organizations as knowledge creators. The paper then applies this perspective to the emerging phenomenon of boundaryless careers and concludes that a knowledge perspective provides significant insight into the implications of such careers for individuals and organizations.     

基于三角模糊理论的尾矿库风险评价研究

根据尾矿库的特点和我国现行的尾矿库安全生产监督管理法律法规及标准规范的要求,构建了尾矿库风险评价指标体系。综合考虑评价指标对风险发生可能性及后果严重程度的不同影响来确定指标权重,同时考虑到权重确定和指标赋值中的模糊性和不确定性等问题,选用三角模糊理论建立了尾矿库风险评价模型,并以本溪某尾矿库为例进行说明。理论分析和实例计算表明,该方法对尾矿库风险评价有很好的适用性。     

危险源相关事故致因理论及概念分析

与危险源相关的事故致因理论,包括能量单元、二类危险源理论和三类危险源理论,均可用于指导事故预防工作,在安全工作实践中发挥良好的作用。二类危险源理论和三类危险源理论的思路是一致的,用于事故预防工作时的应用方式清晰、明确,但这两个事故理论中使隐患的概念变得模糊,危险源的概念也需要加以界定。基于此,本文分析了危险源、隐患和风险的定义、特性及关系,讨论了与危险源相关各事故致因理论的应用方式和存在问题的解决方案,建议将各类危险源视作风险的不同分类,或者在应用过程中对各类危险源做出界定性说明,以理清相关概念在应用时产生的困惑,使这两种事故致因理论在事故预防工作中发挥更好的作用。     

Handling and updating uncertain information in bow-tie analysis

Bow-tie analysis is a fairly new concept in risk assessment that can describe the relationships among different risk control parameters, such as causes, hazards and consequences to mitigate the likelihood of occurrence of unwanted events in an industrial system. It also facilitates the performance of quantitative risk analysis for an unwanted event providing a detailed investigation starting from basic causes to final consequences. The credibility of quantitative evaluation of the bow-tie is still a major concern since uncertainty, due to limited or missing data, often restricts the performance of analysis. The utilization of expert knowledge often provides an alternative for such a situation. However, it comes at the cost of possible uncertainties related to incompleteness (partial ignorance), imprecision (subjectivity), and lack of consensus (if multiple expert judgments are used). Further, if the bow-tie analysis is not flexible enough to incorporate new knowledge or evidence, it may undermine the purpose of risk assessment.Fuzzy set and evidence theory are capable of characterizing the uncertainty associated with expert knowledge. To minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence are equally important in addition to addressing the uncertainties in the knowledge. This paper proposes a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis. A case study comprising a bow-tie for a typical offshore process facility has also been developed to describe the utility of this methodology in an industrial environment.     

Handling data uncertainties in event tree analysis

Event tree analysis (ETA) is an established risk analysis technique to assess likelihood (in a probabilistic context) of an accident. The objective data available to estimate the likelihood is often missing (or sparse), and even if available, is subject to incompleteness (partial ignorance) and imprecision (vagueness). Without addressing incompleteness and imprecision in the available data, ETA and subsequent risk analysis give a false impression of precision and correctness that undermines the overall credibility of the process. This paper explores two approaches to address data uncertainties, namely, fuzzy sets and evidence theory, and compares the results with Monte Carlo simulations. A fuzzy-based approach is used for handling imprecision and subjectivity, whereas evidence theory is used for handling inconsistent, incomplete and conflicting data. Application of these approaches in ETA is demonstrated using the example of an LPG release near a processing facility.     

A method for ranking components importance in presence of epistemic uncertainties

Importance Measures (IMs) are used to rank the contributions of components or basic events to the system performance, e.g. its reliability or risk. Most times, IMs are calculated without due account of the uncertainties in the model of the behavior of the system. The objective of this work is to investigate how uncertainties can influence IMs and to develop a method for giving them due account in the corresponding ranking of the components or basic events. The uncertainties considered in this work affect the model parameters values and are assumed to be described by probability density functions. The method for ranking the contributors to the system performance measure is applied to the auxiliary feedwater system of a nuclear pressurized water reactor.     

Uncertainty aspects in process safety analysis

Uncertainties of input data as well as of simulation models used in process safety analysis (PSA) are key issues in the application of risk analysis results. Mostly, it is connected with an incomplete and uncertain identification of representative accident scenario (RAS) and other vague and ambiguous information required for the assessment of particular elements of risk, especially for determination of frequency as well as severity of the consequences of RAS. The authors discuss and present the sources and types of uncertainties encountered in PSA and also methods to deal with them. There are different approaches to improve such analysis including sensitivity analysis, expert method, statistics and fuzzy logic. Statistical approach uses probability distribution of the input data and fuzzy logic approach uses fuzzy sets. This paper undertakes the fuzzy approach and presents a proposal for fuzzy risk assessment. It consists of a combination of traditional part, where methods within the process hazard analysis (PHA) are used, and “fuzzy part”, applied quantitatively, where fuzzy logic system (FLS) is involved. It concerns frequency, severity of the consequences of RAS and risk evaluation. In addition, a new element called risk correction index (RCI) is introduced to take into account uncertainty concerned with the identification of RAS. The preliminary tests confirmed that the final results on risk index are more precisely and realistically determined.     

Risk assessment of rare events

Rare events often result in large impacts and are hard to predict. Risk analysis of such events is a challenging task because there are few directly relevant data to form a basis for probabilistic risk assessment. Due to the scarcity of data, the probability estimation of a rare event often uses precursor data. Precursor-based methods have been widely used in probability estimation of rare events. However, few attempts have been made to estimate consequences of rare events using their precursors. This paper proposes a holistic precursor-based risk assessment framework for rare events. The Hierarchical Bayesian Approach (HBA) using hyper-priors to represent prior parameters is applied to probability estimation in the proposed framework. Accident precursor data are utilized from an information theory perspective to seek the most informative precursor upon which the consequence of a rare event is estimated. Combining the estimated probability and consequence gives a reasonable assessment of risk. The assessed risk is updated as new information becomes available to produce a dynamic risk profile. The applicability of the methodology is tested through a case study of an offshore blowout accident. The proposed framework provides a rational way to develop the dynamic risk profile of a rare event for its prevention and control.     

基于模糊数学的石油化工装置HAZOP风险分析技术研究

对传统的HAZOP分析中偏差原因发生可能性进行量化。对于有统计数据的,根据行业数据、公司经验及企业事故建立HAZOP风险分析统计数据库;对于没有统计数据的HAZOP分析偏差原因发生概率,通过专家主观评判,用模糊数理论将专家自然语言转换为模糊数,采用左右模糊排序法将模糊数转换为模糊失效概率值。研究了偏差后果严重程度的划分标准,并根据偏差原因概率和偏差后果严重程度确定风险等级,利用风险矩阵得出偏差风险的大小。从而把HAZOP分析方法从定性改进为半定量的分析方法。据此对石油化工装置进行了HAZOP风险分析。     

机械系统的风险概率与经济性安全评价方法研究与应用

针对机械事故频发,为预防和控制事故,依据安全评价发展方向,结合安全系统工程、模糊可靠性理论、人因可靠性技术和安全经济学,从人-机-环3方面分析风险评价因素,建立符合客观实际的风险评价模型,提出包括人为因素、机械设备和环境在内的基本事件失效概率估算方法;以安全经济学的角度将事故严重度量化为风险经济损失,根据每个风险因素的风险概率和风险经济损失来选择风险评价项目,通过检查评价项目状况,最终得出系统风险度,从而形成关于机械系统的定量风险概率与经济性安全评价方法。并给出起重机大车运行机构的工程示例,验证该方法的正确性和可行性。     

Uncertainties in QRA: Analysis of losses of containment from piping and implications on risk prevention and mitigation

Quantitative Risk Assessment (QRA) is commonly used in the chemical industry to support decision-making. Common practices are based on standard methods, such as fault tree, event tree, etc.; in this frame, risk is a function of frequency of events (probability) and associated consequences (negative outcomes), but relevant uncertainties often are not properly taken into account in the derived results. This paper presents the application of an extended risk analysis of loss of containments for a case-study with the following aims: firstly, the uncertainties related to the results of the analysis, which derive from assumption in the application of the standard models, are qualitatively assessed; secondly the application allows evaluating the impact of the uncertainties on the trustworthiness of the results and, finally, commenting about their use in the risk prevention and mitigation.     

An evaluation of maintenance strategy using risk based inspection

Risk based inspection (RBI) methodology was proposed to evaluate the maintenance strategy in industrial process which was constructed in one of the units of Fujian Oil Refinery ISOMAX unit. Using classic definition of risk, both the probability and consequence of accident or failure were investigated respectively under the support of risk-specific code. All equipment in this unit were evaluated and categorized into five risk zone based on the RBI result which covered five levels. In addition, an application of the analytical hierarchy process (AHP) to select the most practicable maintenance strategy for equipment which was located in each risk rating scale was described. To arrange the hierarchic structure and evaluation, four main criteria were defined for pairwise judgments. Finally, four possible alternative strategies were proposed for administrators on the site.     

Uncertainty representation and propagation in quantified risk assessment using fuzzy sets

It is generally acknowledged that there are substantial uncertainties present in any analysis of risk. This paper provides a brief overview of the current techniques used for uncertainty analyses, and highlights their inappropriateness for practical use in the complete risk assessment process. The concept of fuzzy sets as a means for quantifying uncertainty is introduced and a case study demonstrates the application of this method to a simple consequence analysis where parameter uncertainty is considered. The results of this fuzzy analysis are compared with those of a more traditional probabilistic approach using a Monte Carlo simulation. This comparison demonstrates that the novel approach of fuzzy sets is a more appropriate technique due to its non-statistical nature and that the amount of computation required is substantially reduced compared to the traditional probabilistic approach. The versatility of fuzzy set theory suggests that this approach could also be used to quantify other types of uncertainty present in the risk assessment process, including model uncertainty and expert opinion.