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.     

Test case based risk predictions using artificial neural network

INTRODUCTION: The traditional fuzzy-rule-based risk assessment technique has been applied in many industries due to the capability of combining different parameters to obtain an overall risk. However, a drawback occurs as the technique is applied in circumstances where there are multiple parameters to be evaluated that are described by multiple linguistic terms. METHOD: In this study, a risk prediction model incorporating fuzzy set theory and Artificial Neural Network (ANN) capable of resolving the problem encountered is proposed. An algorithm capable of converting the risk-related parameters and the overall risk level from the fuzzy property to the crisp-valued attribute is also developed. Its application is demonstrated by a test case evaluating the navigational safety within port areas. RESULTS: It is concluded that a risk predicting ANN model is capable of generating reliable results as long as the training data takes into account any potential circumstance that may be met. IMPACT ON INDUSTRY: This paper provides safety assessment practitioners with a novel and flexible framework of modelling risks using a fuzzy-rule-base technique. It is especially applicable in circumstances where there are multiple parameters to be considered. The proposed framework also enables the port industry to manage navigational safety in a rational manner.     

Fuzzy logic-based approach for identifying the risk importance of human error

In the system reliability and safety assessment, the focuses are not only the risks caused by hardware or software, but also the risks caused by “human error”. There are uncertainties in the traditional human error risk assessment (e.g. HECA) due to the uncertainties and imprecisions in Human Error Probability (HEP), Error-Effect Probability (EEP) and Error Consequence Severity (ECS). While fuzzy logic can deal with uncertainty and imprecision. It is an efficient tool for solving problems where knowledge uncertainty may occur. The purpose of this paper is to develop a new Fuzzy Human Error Risk Assessment Methodology (FHERAM) for determining Human Error Risk Importance (HERI) as a function of HEP, EEP and ECS. The modeling technique is based on the concept of fuzzy logic, which offers a convenient way of representing the relationships between the inputs (i.e. HEP, EEP, and ECS) and outputs (i.e. HERI) of a risk assessment system in the form of IF–THEN rules. It is implemented on fuzzy logic toolbox of MATLAB using Mamdani techniques. A case example is presented to demonstrate the proposed approach. Results show that the method is more realistic than the traditional ones, and it is practicable and valuable.     

极端海况下海洋石油结构的风险评估

根据中国海上石油工业缺乏独立的风险评价体系的现状 ,笔者对极端海况进行了环境荷载的联合概率分析 ,利用随机模拟技术 ,求解结构的失效概率 ,提出结构失效分析的新方法 ,并利用DNV提供的历史数据 ,对结构失效的后果做了适当分析。以埕北 12 C井组平台作为实例 ,对平台甲板高程 (AirGap)失效分析进行了实例计算。结果表明 ,使用多维联合极值分布理论及相应的求解方法 ,是离岸工程结构物风险评估的重要手段。     

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.     

Modeling and application of risk assessment considering veto factors using fuzzy Petri nets

Risk assessment is important for plant safety, and fuzzy set theory is useful for such assessment because many risk factors have fuzzy characteristics. In this study, veto factors for risk assessment are taken into account. Weighted fuzzy Petri nets (WFPN) with inhibitor arcs are proposed to model relationships between risk factors and establish the risk assessment structure considering veto factors. Definitions of WFPNs as well as the enabling rule and execution rule are provided. The modeling approach for the assessment combining normal factors with veto items is discussed. The proposed fuzzy risk assessment approach is illustrated by an example of the assessment of production installations and process technology of plants that deal with hazardous chemicals. Veto factors and non-veto factors are presented and the assessment structure based on WFPNs is established. Using the factor data of a plant, an assessment value is obtained through the operation of WFPNs and the verification of the approach is discussed.     

Risk-based reliability assessment under epistemic uncertainty

Existing risk in production systems has a direct relationship with unreliability of these systems. Under such circumstances, the approach to maximize the reliability should be replaced with a risk-based reliability assessment approach. Calculating the absolute reliability for systems and complex processes, when we are not provided with any data on failure, is extremely complex and difficult. Until now, studies of reliability assessment have been based on the probability theory, in which the failure time is anticipated after determining the type of size distributions. However, in this paper, the researchers have developed an approach to apply the possibility theory instead of the probability theory. Instead of using absolutely qualitative methods, this new approach applies the Dempster–Shafer Theory. It is obvious when there are insufficient data; an index is needed to make a decision. Then, a novel method is proposed and used in a real case study in order to determine the reliability of production systems based on risk when the available data are not sufficient, helping us to make decisions. After calculating the failure probability and analyzing the assessment matrix and risk criteria, we may conclude that the failure risk of equipment is reduced while the system reliability is increased.     

基于DHGF算法和三角模糊数的装备研制风险评价

针对风险管理方法难以对装备研制风险进行有效评价的问题,提出基于DHGF算法和三角模糊数的装备研制风险评价方法。运用德尔菲法建立装备研制风险的综合评价指标体系。基于三角模糊数和层次分析法(AHP)计算评价指标的权重。利用灰色系统理论确定评价灰类,计算灰色评价系数,得出灰色评价权向量和权矩阵。形成综合评判矩阵,进行模糊运算,求得综合评价结果。算例表明,该方法可有效用于装备研制风险的评价。     

The weighted risk analysis

Safety and risk assessment are characterised by aspects, like subjectivity and objectivity. In this paper, relations between safety and risk are described. When a risk analysis is performed, it is important to realise that decision-making about risks is very complex, and not only technical aspects but also economical, environmental, comfort related, political, psychological and societal acceptance are aspects that play an important role. In order to balance safety measures with aspects, such as environmental, quality, and economical aspects, a weighted risk analysis methodology is proposed in this paper. This paper also provides a theoretical background regarding the scope of safety assessment in relation to the decision-making in complex urban development projects adjacent to or above transport routes of hazardous materials. In Western Europe, such projects are realised due to shortage of space. The weighted risk analysis is an interesting tool comparing different risks, such as investments, economical losses and the loss of human lives, in one-dimension (e.g., money), since both investments and risks could be expressed solely in money. Finally, the weighted risk analysis approach is applied in a case study of Bos and Lommer, Amsterdam.     

油气储运设施事故风险指数模糊逻辑评估方法

油气储运设施风险是其事故发生概率和事故后果的综合度量,而事故概率和后果的定量评估结果往往是具有不确定性的数据,以确定性风险评估准则为基础的传统风险矩阵法和风险值法显然难以评估油气储运设施风险。为此提出开展油气储运设施事故风险的模糊逻辑推理法,首先,对风险矩阵的概率语言等级和损失语言等级的边界进行定量划分;然后,建立油气储运设施风险矩阵模糊集和模糊逻辑推理规则;最后,通过风险模糊推理运算和模糊风险解模糊化以确定油气储运设施的风险水平。实例应用与分析表明,利用推荐方法可得到较为详尽的风险数据信息,不但风险指数更加清晰,而且其所属风险等级类别也更加明确,评估结果能更好地指导油气储运设施的风险管理。     

基于模糊重心的建筑物火灾危险性评价

以传统的模糊评价理论为基础,介绍了一种新的模糊评价方法——模糊重心评价法,该方法采用模糊区间的打分格式,选择矩阵一致性容易判断和改进的模糊层次分析法来处理指标体系的权重,这种方法既方便了评测专家表达测评意见,又充分利用了专家的评定意见,因而有利于提高评价的准确性。根据实际调研情况,建立评价指标体系,对某商场进行了火灾危险性评价,得出了满意结果,提出了指标重心的合理排序是建筑消防安全管理工作的依据和重点。     

危险评价中的数据环境

本文通过分析危险评价的数据来源、数据的准确程度和危险评价模型，论述了数据环境与危险评价的关系，指出了数据的不确切必然会影响到危险评价质量，但应用数据进行危险评价是完全必要的。关键是如何提高数据的精确程度和模型的真实程度，使评价结果更趋准确、可靠。     

基于IIAHP-Entropy-ssd的采空区遗煤自燃危险性评价模型及应用

为了能够对煤矿采空区遗煤自燃危险性进行准确判定,提出基于IIAHP-Entropy-ssd最优综合赋权模糊评价模型。首先,结合影响采空区遗煤的自燃性及环境影响因素,建立危险性评价指标体系,并确定各评价指标的分级准则;其次,利用区间数代替数值评价打分,并运用可能度互补矩阵进行修正的改进区间数层次分析法（IIAHP）,结合熵权法（Entropy）,根据现场实测数据,得出各评价指标的主、客观权重,并运用离差平方和（ssd）的最大化思想进行最优综合赋权,克服评价过程中主、客观因素对评价结果的影响,运用属性数学理论,建立各评价指标的隶属函数;最后,运用该模型对忻州窑矿8914综放工作面采空区遗煤自燃危险性进行评价,并与现场实际情况进行对比,结果表明:该模型的评价结果与实际情况基本一致,验证了该评价模型的准确性,为采空区遗煤自燃危险性评价提供参考和借鉴思路。     

A fuzzy multi-attribute model for risk evaluation in workplaces

Risk assessment constitutes a critical phase of the safety management process. It basically consists of evaluating the risks involved in the execution of working activities, so as to provide the managers with information suitable to address intervention measures. The most important activity in risk assessment is the risk evaluation task but, despite its importance, national and international regulations have never formalized a standard methodology for addressing it, leaving companies complete freedom to adopt the approach they consider appropriate. As a consequence, companies generally settle on the use of simple methodologies which frequently are not able to emphasize all the main aspects affecting risk in the workplace and to produce a precise ranking of hazardous activities. In this paper, a new methodology for risk evaluation is then proposed with the aim to overcome limitations of the classical approaches. In particular, new factors are introduced to take into account effects of human behavior and environment on risk level, other than the classical injury magnitude and occurrence probability of an accident. The proposed methodology also integrates an estimative approach based on the fuzzy logic theory, which permits more coherence in the evaluation process, producing a very suitable final rank of hazardous activities. Finally, an actual case study is reported to show the capabilities of the new risk evaluation model.     

基于多维云模型的埋地并行油气管道风险评价研究*

为提高风险评价准确性以有效支撑管道完整性维护,保证油气管道在多管并行敷设下安全运行,提出1种基于博弈论-多维云模型的风险评价方法。首先,从并行间距、土壤压实度、土壤导热系数、介质流速、管径、埋深、应急响应时间、上下游截断阀间距等方面建立并行管道风险评价指标体系,为降低传统赋权方法的主观性,通过结合熵权法改进层次分析法（AHP）,从而确定主客观权重,再经博弈论组合赋权法综合计算指标权重;其次,运用多维云模型理论确定风险等级,通过修正各风险评分项的等级区间结合指标权重,计算出各级的综合确定度,并进行等级评判;最后,将该方法应用于工程实例。研究结果表明:所评价管段的指标风险处于中等风险水平,风险可接受,管段的整体风险评价结果良好,有利于并行管道安全管理;实例证明该评价方法具有较好的适用性。     

Integrating major accidents hazard into occupational risk assessment: An index approach

Major Accident Hazard (MAH) and Occupational Safety and Health (OSH) are two separated topics in both industrial practice and legislation; recently, interest is increasing toward an integrated risk assessment mainly forced by the tendency to a more efficient safety management system. The present study proposes a semi-quantitative approach to integrate MAH in OSH risk assessment. The two risk types are characterized by opposite features: the OSH analysis is usually task-based and focused on job profiles, while the MAH analysis is space-based and focused on plant characteristics. The basic idea of the proposed approach is to merge spatial information and job profile features in order to improve OSH assessment; thus, a risk index derived by the recent standard ISO 12100 (2010) has been adapted. In detail, the proposed index combines exposure times of each worker at each plant unit – derived from the OSH analysis – with damage areas derived from MAH analysis allowing a quantitative assessment of the MAH risk level for each individual job profile. The model has been tested in a large petrochemical plant; several hypotheses have been developed in order to validate the model. Results have showed the potentiality of the proposed approach in providing a common and coherent representation of both MAH and OSH risks, according to job profiles and plant units.     

Modelling of BP Texas City refinery accident using dynamic risk assessment approach

Process industries involve handling of hazardous substances which on release may potentially cause catastrophic consequences in terms of assets lost, human fatalities or injuries and loss of public confidence of the company. In spite of using endless end-of-the-pipe safety systems, tragic accidents such as BP Texas City refinery still occur. One of the main reasons of such rare but catastrophic events is lack of effective monitoring and modelling approaches that provide early warnings and help to prevent such event. To develop a predictive model one has to rely on past occurrence data, as such events are rare, enough data are usually not available to better understand and model such behavior. In such situations, it is advisable to use near misses and incident data to predict system performance and estimate accident likelihood. This paper is an attempt to demonstrate testing and validation of one such approach, dynamic risk assessment, using data from the BP Texas City refinery incident.Dynamic risk assessment is a novel approach which integrates Bayesian failure updating mechanism with the consequence assessment. The implementation of this methodology to the BP Texas City incident proves that the approach has the ability to learn from near misses, incident, past accidents and predict event occurrence likelihood in the next time interval.     

Conceptual compression discussion on a multi-linear (FTA) and systematic (FRAM) method in an offshore operation’s accident modeling

Risk assessment can be classified into two broad categories: traditional and modern. This paper is aimed at contrasting the functional resonance analysis method (FRAM) as a modern approach with the fault tree analysis (FTA) as a traditional method, regarding assessing the risks of a complex system. Applied methodology by which the risk assessment is carried out, is presented in each approach. Also, FRAM network is executed with regard to nonlinear interaction of human and organizational levels to assess the safety of technological systems. The methodology is implemented for lifting structures deep offshore. The main finding of this paper is that the combined application of FTA and FRAM during risk assessment, could provide complementary perspectives and may contribute to a more comprehensive understanding of an incident. Finally, it is shown that coupling a FRAM network with a suitable quantitative method will result in a plausible outcome for a predefined accident scenario.     

Risk assessment of chemical process considering dynamic probability of near misses based on Bayesian theory and event tree analysis

With the development of modern automatic control systems, chemical accidents are of low frequency in most chemical plants, but once an accident happens, it often causes serious consequences. Near-misses are the precursor of accidents. As the process progresses, near misses caused by abnormal fluctuation of process variables may eventually lead to accidents. However, variables that may lead to serious consequences in the production process cannot update the risk in the life cycle of the process by traditional risk assessment methods, which do not pay enough attention to the near misses. Therefore, this paper proposed a new method based on Bayesian theory to dynamically update the probability of key variables associated with process failure risk and obtain the risk change of the near-misses. This article outlines the proposed approach and uses a chemical process of styrene production to demonstrate the application. In this chemical process, the key variables include flow rate, liquid level, pressure and temperature. In order to study the dynamic risk of the chemical process with consideration of near misses, according to the accumulated data of process variables, firstly the abnormal probability of the variables and the failure rate of safety systems associated with the variables were updated with time based on Bayesian theory. On the basis of the dynamic probability of key process variables, an event tree of possible consequences caused by variable anomalies was established. From the logical relationship of the event tree, the probability of different consequences can be obtained. The results show that the proposed risk assessment method based on Bayesian theory can overcome the shortcomings of traditional analysis methods. It shows the dynamic characteristics of the probability of different near misses, and achieves the dynamic risk analysis of chemical process accidents.     

智能管道时代的管道风险评价技术展望

当前管道风险评价工作普遍使用半定量方法,通过对该方法的应用现状进行总结分析,得出目前半定量风险评价方法存在的问题,包括录入数据准确性不足、评价结果准确性不高,时效性不强等。通过分析物联网、智能移动终端、云技术、大数据等技术开始在管道的应用前景,展望了智能管道时代管道风险评价发展方向:实现管道风险评价实时动态评价,提高风险评价结果的准确性,实现风险的预测预警等,为未来管道风险评价技术发展提供研究思路。