Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

乙炔干燥变温吸附装置安全性分析与燃爆事故预防对策

针对乙炔变温吸附装置的燃爆事故问题,采用HAZOP方法对该装置进行安全性分析,找出存在的安全隐患,提出整改措施,指出装置发生燃爆事故的可能性;又将该装置可能发生的燃爆事故作为顶上事件,利用FTA方法进行分析,得到了装置发生燃爆事故的可能原因,制定了预防发生燃爆事故的对策。通过将HAZOP和FTA分析方法结合使用,有效地识别出乙炔装置存在的隐患,降低了装置操作的危险性,预防了燃爆事故的发生,值得推广应用。     

Integration of process control protection layer into a simulation-based HAZOP tool

This paper discusses the framework methodology behind the proposed simulation-based HAZOP tool. Simulation-based approach is one of the many ways to support conventional HAZOP by its automation. Compared to knowledge-based and other approaches, a HAZOP software tool based on deviations simulation is able to examine the investigated process more into detail and so find root causes of hazardous consequences. Another advantage is the ability to identify also potential hazards which did not occur in the past and might be overlooked. The presented framework methodology uses a layer of protection analysis (LOPA) concept of independent protection layers (IPLs) testing. Control system integrated into the raw process design represents the first of various protection layers of the LOPA concept. As a case study, a CSTR chemical production with nonlinear behavior under Proportional-Integral-Derivative (PID) actions as the predominant type of classical feedback control strategy is used. The presented tool identifies hazardous regimes under conditions when control loop introduces hazardous consequences or even acts synergically with existing hazardous events. Risk derived from different consequences is ranked by the risk assessment matrix (RAM) as a part of the conventional quantitative HAZOP study.     

An extended HAZOP analysis approach with dynamic fault tree

An extended hazard and operability (HAZOP) analysis approach with dynamic fault tree is proposed to identify potential hazards in chemical plants. First, the conventional HAZOP analysis is used to identify the possible fault causes and consequences of abnormal conditions, which are called deviations. Based on HAZOP analysis results, hazard scenario models are built to explicitly represent the propagation pathway of faults. With the quantitative analysis requirements of HAZOP analysis and the time-dependent behavior of real failure events considered, the dynamic fault tree (DFT) analysis approach is then introduced to extend HAZOP analysis. To simplify the quantitative calculation, the DFT model is solved with modularization approach in which a binary decision diagram (BDD) and Markov chain approach are applied to solve static and dynamic subtrees, respectively. Subsequently, the occurrence probability of the top event and the probability importance of each basic event with respect to the top event are determined. Finally, a case study is performed to verify the effectiveness of the approach. Results indicate that compared with the conventional HAZOP approach, the proposed approach does not only identify effectively possible fault root causes but also quantitatively determines occurrence probability of the top event and the most likely fault causes. The approach can provide a reliable basis to improve process safety.     

Uncertainty reduction for improved mishap probability prediction: Application to level control of distillation unit

At all levels, the understanding of uncertainty associated with risk of major chemical industrial hazards should be enhanced. In this study, a quantitative risk assessment (QRA) was performed for a knockout drum in the distillation unit of a refinery process and then probabilistic uncertainty analysis was applied for this QRA. A fault tree was developed to analyze the probability distribution of flammable liquid released from the overfilling of a knockout drum. Bayesian theory was used to update failure rates of the equipment so that generic information from databases and plant equipment real life data are combined to gain all available knowledge on component reliability. Using Monte Carlo simulation, the distribution of top event probability was obtained to characterize the uncertainty of the result. It was found that the uncertainty of basic event probabilities has a significant impact on the top event probability distribution. The top event probability prediction uncertainty profile showed that the risk estimation is improved by reducing uncertainty through Bayesian updating on the basic event probability distributions. The whole distribution of top event probability replaces point value in a risk matrix to guide decisions employing all of the available information rather than only point mean values as in the conventional approach. The resulting uncertainty guides where more information or uncertainty reduction is needed to avoid overlap with intolerable risk levels.     

Performance evaluation of process industries resilience: Risk-based with a network approach

Risk management can be defined as coordinated activities to conduct and control an organization with consideration of risk. Recently, risk management strategies have been developed to change the approach to hazards and risks. Resilience as a safety management theory considers the technical and social aspects of systems simultaneously. Resilience in process industries, as a socio-technical system, has four aspects of early detection, error-tolerant design, flexibility, and recoverability. Meanwhile, process industries' resilience has three phases: avoidance, survival, and recovery, determining the transition between normal state, process upset event, and catastrophic event. There may be various technical and social failures such as regulatory and human or organizational items that can lead to upset or catastrophic events. In the avoidance phase, the upset event is predicted, and thus, the system remains in a normal state. For the survival phase, the system state is assumed to be an upset process event, and the system tries to survive through the unhealthy process conditions or remains in the same state, probably with low performance. In the recovery phase, the system is supposed to be catastrophic, and the emergency barriers are prioritized to show the severity of the consequences and response time, leading to a resumption of a normal state. Therefore, a resilience-based network can be designed for process industries to show its inherent dynamic transition in nature. In this study, network data envelopment analysis (DEA), as a mathematical model, is used to evaluate the relative efficiency of the process industries regarding a network transition approach based on the system's internal structure. First, a resilience-based network is designed to consist of three states of normal, upset, and catastrophic events. Then, the efficiency of each industrial department, which is defined as decision-making units (DMUs), is evaluated using network DEA. As a case study, a refinery that is considered a critical process industry is assessed. Using the proposed model shows the efficient and inefficient DMUs in each of three states of normal, upset, and catastrophic events of the process and the projection onto efficient frontiers. Besides calculating the network efficiency, the performance of each state is extracted to precisely differentiate between DMUs. The results of this study, which is one of the fewest cases in the area of performance evaluation of process industries with a network approach, indicated a robust viewpoint for monitoring and assessment of risks.     

Fuzzy dynamic risk-based maintenance investment optimization for offshore process facilities

A methodology for maintenance planning is developed which helps in improving the reliability of the components and safety performance in process facilities. This methodology helps design an optimum safety maintenance investment plan by integrating the optimization techniques and a fuzzy dynamic risk-based method. Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) is applied to deal with uncertain data. The proposed approach employs multi-experts’ knowledge which helps to optimize the maintenance investments. A separator system in an offshore process facility platform is selected as a case study to demonstrate the application of the proposed methodology. A practical example in the separator system is surveyed and potential failures and Basic Events (BEs) are identified. Finally, a risk-based maintenance plan is provided for future safety investment analysis. The results indicate that the developed methodology estimates the risk more accurately, which enhances the reliability of future process operations.     

Fuzzy logic for piping risk assessment (pfLOPA)

This paper explores the application of the fuzzy logic for risk assessment of major hazards connected with transportation of flammable substances in long pipelines. As a basis for risk assessment, the framework of the fuzzy Layer of Protection Analysis (fLOPA) was used. fLOPA presents a new approach to risk assessment based on two assumptions: 1. different effects of the layer of protection functions on particular elements of the risks (frequency and severity of consequence), and 2. the application of fuzzy logic system (FLS) composed of three elements: fuzzification, inference process and defuzzification. A further calculation follows LOPA methodology with the use of fuzzy logic system where fuzzy risk matrix is used for risk assessment. A typical case study comprising section of a long pipeline failure is performed and a comparison between the classical LOPA approach and fuzzy approach is made.     

Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry

Introduction: Underground mining is considered one of the most hazardous industries and is often associated with serious work-related fatalities; this paper addresses job-related hazards and associated risks. Method: A risk assessment approach is proposed (Pythagorean fuzzy environment) and a case study is carried out in an underground copper and zinc mine. Results: Results of the study demonstrate that hazards can be categorized into different risk levels via compromised solutions of the fuzzy approach. Conclusion: The study provides a theoretical contribution by suggesting a Pythagorean fuzzy numbers-based VlseKriterijumska Optimizacija I Kompromisno Resenje (PFVIKOR) approach. Moreover, it contributes to improving overall safety levels of underground mining by considering and advising on the potential hazards of risk management. Practical applications: The proposed approach will improve the existing safety risk assessment mechanism in underground copper and zinc mining.     

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.     

A blended hazard identification methodology to support process diagnosis

A novel hazard identification methodology applied to process systems is presented in this paper. This blended hazard identification (BLHAZID) methodology blends two different types of HAZID methods: the function-driven and component-driven approach. The BLHAZID method is based on a conceptual framework called the Functional Systems Framework, which describes structure–function–goal relationships in process systems.The goals of the BLHAZID methodology are to generate outcomes that contain a high coverage of hazards, describe detailed failure causality in process systems and express this knowledge in a structured form for effective reused in subsequent applications, such as fault diagnosis, operator training, design reviews, fault and event tree construction and hazard updates to satisfy major hazard facility requirements.Both the BLHAZID methodology and the Functional Systems Framework were developed with involvement and advice from two major industrial partners. An industrial case study of a benzene saturation unit is presented to illustrate how the BLHAZID methodology operates in practice.     

A risk-based approach to design warning system for processing facilities

Alarm flooding is a major safety issue in today's processing facilities. Important recommendations are available for alarm management; however, they are often violated in practice, especially in the alarm systems implemented through the distributed control system. An effective process alarm prioritization and management system is desired for a safe and effective operation of a process facility.In present work, authors address two main issues related to an alarm system – the reliability and the prioritization of the alarms. The main objective is to deal with the alarm-flooding problem in process facilities. A multi alert voting system based on sensor redundancy approach is proposed to improve the reliability. A quantitative risk-based alarm management approach is proposed to address the flooding issue. In the risk-based approach, an integrated model consisting of the probability (P), the impact (I) of the potential hazards, and the process safety time is proposed to prioritize these raised alarms.The proposed approach is further explained by a reactor system with pressure and temperature variable monitoring and controls, where the hazards associated with two alerts caused by over high pressure and over high temperature are analyzed and integrated with response time for alarms generation and prioritization.     

电炉生产系统工伤事故控制技术的研究

本文是综合应用安全系统工程的原理和方法,控制生产系统的工伤事故,并采用系统辨识理论,辨识生产中的潜在危险和后果,定量评价潜在危险的危害程度和发生概率;综合应用数理统计、工程逻辑、故障树、事件树、管理失误和风险树等多种分析方法,对电炉炼钢生产的原料、冶炼、铸锭、天车、电气、机械等子系统进行了事故发生可能性的预分析和安全状况评价。据分析评价结果,结合生产实际和管理现状,制定了控制事故的综合技术对策,并开发了一系列适合于我国企业安全管理实际需要的计算机软件。     

The role of behavioral factors on safety management in underground mines

Traditional approaches on the prevention of accidents/injuries in mines reached its limit of effectiveness in improving safety performance and a fresh approach is utmost required. Behavioral safety analysis has been identified as an effective alternative in many industries. This paper is therefore sought to examine the role of behavioral factors on the occurrence of mine accidents and injuries through a case study. Data were collected from two neighboring underground coalmines operating under a large public sector organization of India. High–low plots and t-test were done to explore the differences between behavioral characteristics of accident involved (case) and non-involved (control) workers. How these differences could cause accidents/injuries in mines was estimated through structural equation modeling. The case study results show that accident group of workers (cases) are more job dissatisfied, negatively affected, and highly risk taking compared to the non-accident group of workers (controls). The accident model path analysis shows that negative affectivity, job dissatisfaction, and risk taking behaviors predict an increased number of injuries in mines. Apart from direct influences to work injuries, negative affectivity and job dissatisfaction make workers to take more risks and behave unsafely. These findings contribute to the design of safety programs including safety training, which should be behaviorally motivated. Mine safety management of the case study mines should outskirt their age old belief that accidents/injuries are due to hazardous nature of mining and only engineering control and regulatory monitoring are sufficient for improving safety of the mines. The multivariate analysis also shows that experience bears no relationships with work injury indicating that a less experienced worker is equally likely to be injured as an experienced worker. It implies that experience though helps workers in understanding the physical hazards, however, avoiding the imminent danger is much more behavioral. The variables negative affectivity, job dissatisfaction, and risk taking behaviors are therefore crucial in avoiding accident/injuries in mines.     

Risk assessment: an approach to control hazards in mines

Accidents and injuries related to work are major occupational health problems in most of the industrialized countries.Traditional approaches to manage workplace safety in mines have mainly focused on job redesign and technical aspects of engineering systems.It is being realized that compliance to rules and regulations of mines is a prerequisite;however,it is not sufficient to achieve further reduction in accident and injury rates in mines.Proactive approaches are necessary to further improve the safety standards in mines.Unsafe conditions and practices in mines lead to a number of accidents,which in turn may cause loss and injury to human lives,damages to property,and loss of production.Hazard identification and risk assessment is an important task for the mining industry which needs to consider all the risk factors at workplaces.Applications of risk management approaches in mines are necessary to identify and quantify potential hazards and to suggest effective solutions.In this paper,the following risk estimation techniques were discussed:(i)DGMS(Directorate General of Mines Safety,India)risk rating criterion,and(ii)a matrix based approach.The proposed tools were demonstrated through an application in an opencast coal mine in India.It was inferred that the risk assessment approach can be used as an effective tool to indentify and control hazards in mines.     

煤矿瓦斯爆炸事故隐患及风险的表征方法

为治理煤矿瓦斯爆炸事故隐患,管控其风险大小,基于证据对瓦斯爆炸事故隐患进行了系统辨识,利用逻辑图分析了隐患之间的耦合关系和风险演化路径;从事件发生的可能性、事件自身的严重性以及受体的暴露程度3个方面对瓦斯爆炸风险进行表征,并提出三维风险矩阵对事故风险进行分级评价。该方法可以为瓦斯爆炸事故隐患辨识、风险分析、风险评价以及设计事故预防措施提供借鉴。     

基于事故深度调查的城市交通事故特征分析

为探索适合我国的事故数据深度采集标准,并分析城市道路交通事故特征及致因,基于《道路交通事故深度调查信息采集表》(简称采集表),调查人员随交警赴事故现场随机详细调查87起城市道路交通事故。借鉴"Haddon Matrix"思想建立致因分析矩阵系统,分析事故的致因。发现采集表对事故地点、事故形态及原因项分类更加具体、明确,女性驾驶员的事故发生率略低于男性驾驶员,驾驶员年龄超过60岁后,发生事故的危险性显著提高,"交叉口影响区"事故50%由变更车道引起,非机动车驾驶员未戴安全头盔是造成严重伤害的重要原因。     

Evaluating the stability of a freestanding Mast Climbing Work Platform

Mast Climbing Work Platforms (MCWPs) are becoming more common at construction sites and are being used as an alternative to traditional scaffolding. Although their use is increasing, little to no published information exists on the potential safety hazards they could pose for workers. As a last line of defense, a personal fall-arrest system can be used to save a worker in a fall incident from the platform. There has been no published information on whether it is safe to use such a personal fall-arrest system with MCWPs. In this study, the issues of concern for occupational safety included: (a) the overall stability of the freestanding mast climber during a fall-arrest condition and (b) whether that fall-arrest system could potentially present safety hazards to other workers on the platform during a fall-arrest condition. This research project investigated those safety concerns with respect to the mast climber stability and the workers using it by creating fall-arrest impact forces that are transmitted to the equipment and by subsequently observing the movement of the mast climber and the working deck used by the workers. This study found that when the equipment was erected and used according to the manufacturer's recommendations during a fall-arrest condition, destabilizing forces were very small and there were no signs of potential of MCWP collapse. However, potential fall hazards could be presented to other workers on the platform during a fall arrest. Workers near an open platform are advised to wear a personal fall-arrest system to reduce the risk of being ejected. Due to the increasing use of MCWPs at construction sites, there is a corresponding need for evidence and science-based safety guidelines or regulations and further research should be conducted to continue to fill the knowledge gap with MCWP equipment.