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.     

Integrating lean principles and fuzzy bow-tie analysis for risk assessment in chemical industry

In this research, a framework combining lean manufacturing principles and fuzzy bow-tie analyses is used to assess process risks in chemical industry. Lean manufacturing tools and techniques are widely used for eliminating wastes in manufacturing environments. The five principles of lean (identify value, map the value stream, create flow, establish pull, and seek perfection) are utilized in the risk assessment process. Lean tools such as Fishbone Diagram, and Failure Mode and Effect Analysis (FMEA) are used for risk analysis and mitigation. Lean principles and tools are combined with bow-tie analysis for effective risk assessment process. The uncertainty inherent with the risks is handled using fuzzy logic principles. A case study from a chemical process industry is provided. Main risks and risk factors are identified and analyzed by the risk management team. Fuzzy estimates are obtained for the risk factors and bow-tie analysis is used to calculate the aggregated risk probability and impact. The risks are prioritized using risk priority matrix and mitigation strategies are selected based on FMEA. Results showed that the proposed framework can effectively improve the risk management process in the chemical industry.     

RAPID-N: Rapid natech risk assessment and mapping framework

Natech accidents at industrial plants are an emerging risk with possibly serious consequences. For the mitigation of natech risk, authorities need to identify natech prone areas in a systematic manner. In order to facilitate probabilistic natech risk mapping, a unified methodology was developed that is based on the estimation of on-site natural hazard parameters, determination of damage probabilities of plant units, and assessment of probability and severity of possibly triggered natech events. The methodology was implemented as an on-line, extensible risk assessment and mapping software framework called RAPID-N, which allows rapid local and regional natech risk assessment and mapping with minimal data input. RAPID-N features an innovative data estimation framework to complete missing input data, such as on-site natural hazard parameters and plant unit characteristics. The framework is also used for damage assessment and natech consequence analysis, and allows easy modification of input parameters, dynamic generation of consequence models according to data availability, and extension of models by adding new equations or substituting existing ones with alternatives. Results are presented as summary reports and interactive risk maps, which can be used for land-use and emergency planning purposes by using scenario hazards, or for rapid natech consequence assessment following actual disasters. As proof of concept, the framework provides a custom implementation of the U.S. EPA's RMP Guidance for Offsite Consequence Analysis methodology to perform natech consequence analysis and includes comprehensive data for earthquakes. It is readily extendible to other natural hazards and more comprehensive risk assessment methods.     

Prevention and mitigation of injuries and damages arising from the activity of subliminal enterprises: A case study in Slovakia

The paper focuses on risk sources under no legislative pressure in the field of prevention of major accidents. Despite this, they can represent significant sources of risk of accidents.The aim of the paper is to present the results of the risk assessment associated with the operation of enterprises not regulated by the SEVESO III Directive (the so-called subliminal enterprises), to provide information on possible operational problems and to verify the applicability of recognized risk analysis methods for these specific sources of risk. Last but not least, its purpose is to point out that subliminal enterprises, due to their location close to residential areas or areas with a high concentration of population, pose a serious risk to the population.The paper summarizes the results of the quantitative risk assessment of a specific enterprise not included in the Seveso Directive – a filling station. Filling stations are frequently located in built-up areas with a dense coefficient of habitability. Due to their number, location (e.g. close to residential areas), frequency of occurrence of persons in the area and handling of dangerous substances during normal operation, they can have negative or even tragic consequences to the life and health of the population.Due to the non-existent risk assessment methodology for enterprises with subliminal quantities of dangerous substances and the lack of a systematic search for risk sources, a risk assessment procedure for these companies is designed.     

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。     

Environmental risk source management system for the petrochemical industry

We identify environmental risk sources within the petrochemical industry with a bow-tie analysis, evaluate environmental risk sources with an integrated environmental risk assessment index, and classify environmental risk sources considering both environmental consequences and management costs. Furthermore, we develop a routine management system for environmental risk sources based on browser/server model and web-GIS technology. The system has four main functions: petrochemical enterprise registration and declaration, environmental risk source information correction and confirmation, environmental risk source evaluation and classification, and environmental risk source management. The system runs with the following sequential steps. (1) Petrochemical enterprises register and declare their environmental risk source information. (2) The registered environmental risk source information is checked, corrected and confirmed by local environmental officials. (3) The probability and intensity of environmental risk are calculated for all registered petrochemical factories. (4) All environmental risk sources are classified into high, medium and low risk sections based on their potential regional environmental and ecological impacts. (5) The system provides recommendations on the routine risk management based on empirical expert opinions. The software provides an effective tool for safety production of petrochemical enterprises and can be applied by local governments for environmental risk source management.     

Risk analysis for oil & gas pipelines: A sustainability assessment approach using fuzzy based bow-tie analysis

Vast amounts of oil & gas (O&G) are consumed around the world everyday that are mainly transported and distributed through pipelines. Only in Canada, the total length of O&G pipelines is approximately 100,000 km, which is the third largest in the world. Integrity of these pipelines is of primary interest to O&G companies, consultants, governmental agencies, consumers and other stakeholder due to adverse consequences and heavy financial losses in case of system failure. Fault tree analysis (FTA) and event tree analysis (ETA) are two graphical techniques used to perform risk analysis, where FTA represents causes (likelihood) and ETA represents consequences of a failure event. ‘Bow-tie’ is an approach that integrates a fault tree (on the left side) and an event tree (on the right side) to represent causes, threat (hazards) and consequences in a common platform. Traditional ‘bow-tie’ approach is not able to characterize model uncertainty that arises due to assumption of independence among different risk events. In this paper, in order to deal with vagueness of the data, the fuzzy logic is employed to derive fuzzy probabilities (likelihood) of basic events in fault tree and to estimate fuzzy probabilities (likelihood) of output event consequences. The study also explores how interdependencies among various factors might influence analysis results and introduces fuzzy utility value (FUV) to perform risk assessment for natural gas pipelines using triple bottom line (TBL) sustainability criteria, namely, social, environmental and economical consequences. The present study aims to help owners of transmission and distribution pipeline companies in risk management and decision-making to consider multi-dimensional consequences that may arise from pipeline failures. The research results can help professionals to decide whether and where to take preventive or corrective actions and help informed decision-making in the risk management process. A simple example is used to demonstrate the proposed approach.     

Shelter-in-place risk assessment for high-pressure natural gas wells with hydrogen sulphide and its application in emergency management

This paper provides a risk assessment method of sheltering in-place for high-pressure natural gas wells with hydrogen sulphide. In this paper, the shelter-in-place risk is estimated by integrating the health consequences of an individual taking one kind of emergency response to the emergency orders of sheltering in place from the emergency decision makers and the probability of the corresponding emergency response action. The probability of the corresponding emergency response action in the proposed method is estimated through the accident probability analysis and the probability analysis of taking a certain response action. The health consequence estimation is based on air exchange rate test of the shelter buildings as well as accident consequence calculation. The evaluation of shelter-in-place risks based on “as low as reasonably practicable (ALARP)” guidelines was employed to provide suggestions for emergency management under both normal conditions and off normal conditions. A case study of risk assessment of sheltering in the local residential houses in Xuanhan County of Sichuan Province, China was taken as an example to illustrate the proposed risk assessment process of shelter-in-place and its application in the decision-making process for emergency management.     

基于模糊Bow-tie模型的深水海底管道定量风险评价研究

为有效评价深水海底管道风险,提出一种新的模糊Bow-tie模型定量风险评价方法。综合运用Bow-tie图、模糊集以及德尔菲法,定量分析油气泄漏概率。进一步利用层次分析法(AHP)研究油气泄漏后果的严重程度,给出泄漏后果因素的权重系数选择方案。同时,结合风险矩阵,实现对高风险深水海底管道的定量风险评价。将上述方法用到具体海底管道工程中,得出目标海底管道泄漏概率属于A级,泄漏后果属于Ⅲ级,泄漏风险为高风险,这一结果与实际情况较为符合。     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

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.     

Does your facility have a dust problem: Methods for evaluating dust explosion hazards

The hazards of dust explosions prevailing in plants are dependent on a large variety of factors that include process parameters, such as pressure, temperature and flow characteristics, as well as equipment properties, such as geometry layout, the presence of moving elements, dust explosion characteristics and mitigating measures. A good dust explosion risk assessment is a thorough method involving the identification of all hazards, their probability of occurrence and the severity of potential consequences. The consequences of dust explosions are described as consequences for personnel and equipment, taking into account consequences of both primary and secondary events.While certain standards cover all the basic elements of explosion prevention and protection, systematic risk assessments and area classifications are obligatory in Europe, as required by EU ATEX and Seveso II directives. In the United States, NFPA 654 requires that the design of the fire and explosion safety provisions shall be based on a process hazard analysis of the facility, process, and the associated fire or explosion hazards. In this paper, we will demonstrate how applying such techniques as SCRAM (short-cut risk analysis method) can help identify potentially hazardous conditions and provide valuable assistance in reducing high-risk areas. The likelihood of a dust explosion is based on the ignition probability and the probability of flammable dust clouds arising. While all possible ignition sources are reviewed, the most important ones include open flames, mechanical sparks, hot surfaces, electric equipment, smoldering combustion (self-ignition) and electrostatic sparks and discharges. The probability of dust clouds arising is closely related to both process and dust dispersion properties.Factors determining the consequences of dust explosions include how frequently personnel are present, the equipment strength, implemented consequence-reducing measures and housekeeping, as risk assessment techniques demonstrate the importance of good housekeeping especially due to the enormous consequences of secondary dust explosions (despite their relatively low probability). The ignitibility and explosibility of the potential dust clouds also play a crucial role in determining the overall risk.Classes describe both the likelihood of dust explosions and their consequences, ranging from low probabilities and limited local damage, to high probability of occurrence and catastrophic damage. Acceptance criteria are determined based on the likelihood and consequence of the events. The risk assessment techniques also allow for choosing adequate risk reducing measures: both preventive and protective. Techniques for mitigating identified explosions risks include the following: bursting disks and quenching tubes, explosion suppression systems, explosion isolating systems, inerting techniques and temperature control. Advanced CFD tools (DESC) can be used to not only assess dust explosion hazards, but also provide valuable insight into protective measures, including suppression and venting.     

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.     

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.     

基于风险的报警优先级量化设定方法研究

当前主流报警优先级设定方法操作性不佳,在进行装置报警系统优化时由于考虑维度少而无法较好优化报警系统优先级,针对该问题,建立了基于风险的报警优先级设定新方法。将标定的风险图法应用于报警优先级设定,假定某报警不存在,对出现危险情况的频率、后果严重度、可用时间、避免事故后果的可能性等进行标定,并对危险状况出现频率与可用时间进行矩阵分析,将结果运用于风险图中;针对某柴油加氢装置报警系统,应用该方法进行了报警优先级优化。结果表明:基于风险的报警优先级量化设定方法能够有效应用于优化装置报警优先级;经该方法优化的各级报警,数量分布更接近EEMUA的推荐值;对于“在所考虑的报警不存在时每年发生事故的次数”因素,研究给出3个不同的档次供企业选择,实践中,企业可结合自身可接受标准,作进一步完善。     

Development of generic bow-tie diagrams of accidental scenarios triggered by flooding of industrial facilities (Natech)

Interactions between natural events and industrial installations may lead to dangerous phenomena. According to bibliographical research, the industrial sector is often unprepared for these joint natural and technological or Natech events mainly because of the lack of guidelines on how to apply Natech regulations and the lack of information on the dynamics of Natechs. In order to fill the gaps and provide guidance on Natech risk assessment to operators, a systematic risk analysis methodology was developed and resulted firstly in proposing general reference bow-ties that reconfigure accidental scenarios triggered by flood events. The validation of these scenarios was made in the surface treatment sector. Building on these bow-ties, the risk analysis methodology will be completed and a checklist simple to use, along with a list proposing preventive and protective measures, to be used by operators in order to decrease the vulnerability of their industrial facilities to technological accidents triggered by floods will be developed in future work.     

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。     

Occupational risks and the value and modelling of a measurement of severity

In studies of occupational risks, severity, which is a component of the estimation of every risk, appears as a multifaceted entity assessable according to numerous criteria. A method of measuring the degree of severity of the consequences of potentially dangerous events would be of undeniable value to organisations seeking to improve their understanding of the complexity of such events. The need to control severity is highlighted by scientifically acquired improvements in the understanding of occupational risks, by certain new regulatory obligations in Europe, and by some requirements in the financial management of organisations. We put forward a statistical way of integrating several constituent elements of severity and hence of determining a relevant, synthetic, one-dimensional index. This is achieved by means of principal component analysis (PCA), which is used here to calculate a resultant severity, as in some physical measurements. We also investigate how severity may be statistically modelled, with the aim of contributing to the quantitative assessment of occupational risks. The choice of parametric models is detailed and illustrated by the search for a suitable model for workplace accidents in an organisational setting. The practical value of modelling severity is two-fold. First, one is able to study the distribution of the numerical values of severity over a continuum (a theoretically infinite numerical set) rather than through a limited number of arbitrarily defined categories. Second, with a generally applicable parametric model, one can estimate the law of probability of a measurement of severity in a particular situation, notably recent or new. Lastly, the statistical concept of risk curve is defined and discussed. The goal is to incorporate the severity component into the risk assessment in the form of a probability law, thus circumventing the difficulties associated with an analysis of scenarios.     

Improving PHA/LOPA by consistent consequence severity estimation

Most risk analysis methods rely on a qualitative judgment of consequence severity, regardless of the analysis rigor applied to the estimation of hazardous event frequency. Since the risk analysis is dependent on the estimated frequency and consequence severity of the hazardous event, the error associated with the consequence severity estimate directly impacts the estimated risk and ultimately the risk reduction requirements. Overstatement of the consequence severity creates excessive risk reduction requirements. Understatement results in inadequate risk reduction.Consistency in the consequence severity estimate can be substantially improved by implementing consequence estimation tools that assist PHA/LOPA team members in understanding the flammability, explosivity, or toxicity of process chemical releases. This paper provides justification for developing semi-quantitative look-up tables to support the team assessment of consequence severity. Just as the frequency and risk reduction tables have greatly improved consistency in the estimate of the hazardous event frequency, consequence severity tables can significantly increase confidence in the severity estimate.     

Risk analysis in Natech events: State of the art

Natech events (Natural Hazard Triggering Technological Disasters) are industrial accidents caused by natural events such as hurricanes, floods, earthquakes, tsunamis, and so on. In recent decades, the probability of these events occurring has increased, activating the interest of researchers in the study of new methods of risk analysis to prevent and mitigate possible damage to people, the environment, and processing facilities. On the other hand, the concept of multi-hazard is summarized in the combination of two or more threat factors manifested in isolated, simultaneous manner, or by chain reaction, to produce a trigger event of a disaster, where hazardous events can be one or more natural events. Considering that, it is essential to know the progress in risk analysis for Natech events, to identify the gaps for future research. Therefore, in this paper, a systematic review of the Natech events literature with single and multi-hazard approaches was developed. The review was conducted by searching the Science Direct, Web of Science, and Scopus databases for scientific documents. Subsequently, the words Natech and Multi-hazard were taken as keywords, and 208 results were obtained. Then, some management documents were consulted in international organizations to compare academic literature and industrial risk management. In conclusion, the risk analysis methods revised are specific to a particular hazard and apply mainly to earthquakes, floods, and lightning. Regarding a multi-hazard approach, the methods focus on risk mitigation in urban areas without taking into account Natech risk. In the case of industrial risk assessment, some methodologies were found that briefly consider Natech risk in risk assessment processes in industry.