Human error analysis in furnace start-up operation using HEART under intuitionistic fuzzy environment

To address human error in system reliability, Human Reliability Analysis (HRA) is an essential issue. Human Error Assessment and Reduction Technique (HEART) as a rather straightforward technique for HRA has successfully been used in many areas to predict human error probability (HEP). However, knowledge acquisition of experts during assessed proportion of affect (APOA) calculation is subjected to vagueness and ambiguity. To overcome this challenge, in this paper Intuitionistic Fuzzy (IF) set due to their advantage to represent more fuzzy information than a classical fuzzy set adopted through APOA calculation. To demonstrate this hybrid approach short for, IF-HEART, the furnace start-up operation is handled, since analysis shows that most of explosions and losses occur during furnace start-ups operation. Further, a sensitivity analysis is carried out to approve the proposed integrated approach. In addition to its academic contribution, the results of the paper enable to improve the overall safety level of a furnace by taking into account potential human error.     

Risk assessment tools incorporating human error probabilities in the Japanese small-sized establishment

Although it has been estimated that as many as 80% of all occupational accidents have human errors as a cause, no risk assessment tools incorporating human-related elements have been developed for small companies. Human error probability (HEP) and human error analysis (HEA) have been used for large-scale, safety-critical industries for last three decades, but these tools are not suitable for smaller, more general industries that comprise the majority of accident settings.Here, we describe and verify a risk assessment tool that includes human-related elements for small companies. The tool expands on traditional risk assessment methods, such as matrix, risk graph and numerical scoring method, by adding human-related elements. The tool is easy-to-use in occupational environments, and includes assessments of human behavior and potentially outdated machinery at work place.     

Application of fuzzy logic to explosion risk assessment

Safety and health of workers potentially being at risk from explosive atmospheres are regulated by separate regulations (ANSI/AIHA in USA and ATEX in the European Union). The ANSI/AIHA does not require risk assessment whereas it is compulsory for ATEX. There is no standard method to do that assessment. For that purpose we have applied the explosion Layer of Protection Analysis (ExLOPA), which enables semi-quantitative risk assessment for process plants where explosive atmospheres occur. The ExLOPA is based on the original work of CCPS for LOPA taking into account an explosion accident scenario at workplace. That includes typical variables appropriate for workplace explosion like occurrence of the explosive atmosphere, the presence of effective ignition sources, activity of the explosion prevention and mitigation independent protection layers as well as the severity of consequences. All those variables are expressed in the form of qualitative linguistic categories and relations between them are presented using expert based engineering knowledge, expressed in the form of appropriate set of rules. In this way the category of explosion risk may be estimated by the semi-quantitative analysis. However, this simplified method is connected with essential uncertainties providing over or under estimation of the explosion risk and may not provide real output data.In order to overcome this problem and receive more detailed quantitative results, the fuzzy logic system was applied. In the first stage called fuzzification, all linguistic categories of the variables are mapped by fuzzy sets. In the second stage, the number of relation between all variables of analysis are determined by the enumerative combinatorics and the set of the 810 fuzzy rules “IF-THEN” is received. Each rule enables determination of the fuzzy risk level for a particular accident scenario. In the last stage, called defuzzification, the crisp value of final risk is obtained using a centroid method. The final result of the risk presents a contribution of each risk category represented by the fuzzy sets (A, TA, TNA and NA) and is therefore more precise and readable than the traditional approach producing one category of risk only. Fuzzy logic gives a possibility of better insights into hazards and safety phenomena for each explosion risk scenario. It is not possible to receive such conclusions from the traditional ExLOPA calculation results. However it requires the application of computer-aided analyses which may be partially in conflict with a simplicity of ExLOPA.The practical example provides a comparison between the traditional results obtained by ExLOPA and by fuzzy ExLOPA methods.     

Usage of human reliability quantification methods.

Human reliability quantification (HRQ) methods are becoming increasingly important in risk and accident assessment in systems these terms are usually related to (hi-tech industrial systems, including nuclear and chemical plants). These methods began to intensively develop after numerous accidents caused by human error or inadequate activity of people who controlled and managed complex technological processes. For already existing systems, but also for new ones, it is important to assess the possibility of an accident. Determination of possible preventive activities, which include the influence of human error on the safety of a system, is also required. These are the main goals of the HRQ method. Using Absolute Probability Judgment (APJ) and Success Likelihood Index Methods (SLIM) HRQ techniques in control and management centers in electro-power systems in Belgrade and railway traffic in Nis (both in Serbia and Montenegro) are shown in this paper.     

基于直觉三角模糊TOPSIS的高铁列车调度指挥人因失误风险排序

针对高速铁路调度指挥人因风险排序问题,从人因失误概率、人因失误探测度、人因失误重要度和事故严酷度四个方面构建风险评价指标体系。考虑到人因风险指标的模糊性和不确定性,用直觉三角模糊数描述各指标值,基于直觉模糊熵计算指标客观权重,然后建立基于TOPSIS法的高铁列车调度指挥人因失误风险排序模型。最后,基于实例验证了排序模型的实用性。     

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.     

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.     

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.     

Determination of human error probabilities in maintenance procedures of a pump

The “human factor” constitutes an important role in the prediction of safe operation of a facility. Hence, information about human capacities and behaviours should be applied methodically to increase the safety of a systematic process. This paper provides an analysis of human factors in pre- and post-maintenance operations. For possible failure scenarios, this paper considers the procedures for removing process equipment from service (pre-maintenance) and returning the component to service (post-maintenance). In this study, a pump is used as the test example. For each scenario, the human error probability (HEP) is calculated for each activity, using the Human Error Assessment and Reduction Technique (HEART) which is commonly implemented technique in industry, can also be applied in the analyses of safety cases. HEART is a reliable technique for comparing HEP and its approach is based on the degree of error recovery. Consequences are also assessed for each activity in this methodology. The final value of risk for each activity is assigned by combining error likelihood and related consequences. When the calculated risk is beyond acceptable levels, risk management strategies are provided to increase the safety of the maintenance procedures. The most probable human errors for a considered case study are related to the activities of “draining lines” and “open valves”. These two activities have high HEPs, which are 9.57E−01 and 9.62E−01, respectively.     

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。     

Developing a new fuzzy inference system for pipeline risk assessment

The problem of less and/or even lack of information and uncertainty in modeling and decision making plays a key role in many engineering problems; so that, it results in designers and engineers could not reach to sure solutions for the problems under consideration. In this paper, an application of the fuzzy logic for modeling the uncertainty involved in the problem of pipeline risk assessment is developed. For achieving the aim, relative risk score (RRS) methodology, one of the most popular techniques in pipeline risk assessment, is integrated with fuzzy logic. The proposed model is performed on fuzzy logic toolbox of MATLAB^® using Mamdani algorithm based on experts' knowledge. A typical case study is implemented and a comparison between the classical risk assessment approach and the proposed model is made. The results demonstrate that the proposed model provides more accurate, precise, sure results; so that, it can be taken into account as an intelligent risk assessment tool in different engineering problems.     

Technical,human, and organizational factors affecting failures of firefighting systems (FSs) of atmospheric storage tanks: Providing a risk assessment approach using Fuzzy Bayesian Network (FBN) and content validity indicators

Most risk assessment methods have problems such as uncertainty, static structure, and lack of validation. Also, in most of these studies, less attention has been paid to human, managerial, and organizational issues. Therefore, this study proposes a risk assessment method based on the Fuzzy Bayesian Network (FBN) to prevent failure of firefighting systems (FFSs) in the atmospheric Storage Tanks of a Petrochemical Industry. The first stage of the study is the development of a fault tree (FT) and investigation of basic events (BEs). In this study, content validity indices and brainstorming technique were used to validate the FT structure and reduce the uncertainties of Completeness, Modeling, and Parameter. After determining the probability of basic events (BEs) by the expert team opinions and fuzzy logic, events were transmitted to the Bayesian Network (BN) and then analyzed with deductive and inductive reasoning, followed by sensitivity analysis in the GeNIe software. Finally, results of a case study in the Atmospheric Storage Tanks of the Methanol Floating Roof of a Petrochemical Industry showed that FBN simulation and FT validation could provide a practical way to determine FFSs probabilities, identify impactful events, and reduce the above uncertainties. Also, taking account of hidden factors of events, such as organizational and managerial factors, can help managers to prevent FFSs in tanks.     

An Investigation of Stress Level and Human Reliability Analysis of Two Security Companies in Taiwan

This article presents the results of an evaluation and comparison study of three subjective techniques for determining human reliability under stress for work performed at two Taiwanese security companies. Stress levels at security companies were estimated by using the Unified Tri-service Cognitive Performance Assessment Battery and 40 participants from two similar-sized companies. Experiment results (memory searching task and mathematical processing task) indicated that the participants were under high levels of stress. Three subjective techniques (Success Likelihood Index Method, Technique for Human Error Rate Prediction, and Human Error Assessment and Reduction Technique) for estimating human error probability were evaluated and compared by using 20 experts for six tasks. The comparison criteria are interjudge consistency and accuracy. Of the three human error probability tests studied, the Technique for Human Error Rate Prediction and Success Likelihood Index Method were more consistent than the Human Error Assessment and Reduction Technique. The same relationship occurred in the comparison of accuracy. Thus, the Human Error Assessment and Reduction Technique may need to be modified in some way if it is to be useful. It was already known that this technique required modifications in error-producing conditions and nominal human unreliability. Our work presents additional evidence to substantiate this.     

SPA–fuzzy method based real-time risk assessment for major hazard installations storing flammable gas

For monitoring and control of major hazard installations storing flammable gas, the risk based warning/early-warning is very important. A set-pair analysis (SPA) based fuzzy assessment method (SPA–fuzzy) is proposed for the real-time risk assessment in this paper. Based on principle of SPA and fuzzy logic theory, the likelihood of accident occurrence and the consequence of the accident can be assessed, and the risk value or risk degree can be evaluated. The method takes advantage of the data acquired from the real-time safety monitoring system, so that the varying of the risk can be revealed during an accident developing. The risk assessment simulation of VCE accident caused by gas leaked from LPG tank is performed. It is shown that SPA–fuzzy method has the same risk value as that assessed by normal fuzzy method.     

AHP-Fuzzy方法在火力发电厂风险评价中的应用

火力发电厂在国民生产中占有重要地位,但也具有多种风险因素,一旦发生事故所带来的损失十分严重。为了了解其风险情况,必须进行风险评价。应用AHP建立了评价指标体系,并应用模糊数学中的隶属度函数和综合评价方法求出发电厂风险状况。实例证明,本评价方法有效、可行。     

基于模糊保护层的池火灾事故风险分析

为计算引发池火灾事故的风险值,提高事故风险的量化水平,判断现有风险控制措施是否满足风险容忍度的要求,为制定减缓风险措施提供依据,给出了新的池火灾风险评估模型。基于传统的保护层分析模型(LOPA),结合模糊集合理论,引入模糊风险矩阵进行风险评估,构建适用于引发池火灾事故的模糊保护层(fL OPA)风险分析模型。该模型的特点是将模糊逻辑和保护层分析结合,减少了传统保护层分析方法计算过程中的不确定性因素,引入严重度减少指数(SRI)概念,使严重度计算、风险评估更加准确。运用该模型对原油储罐泄漏池火灾事故风险进行分析,给出风险决策方案,判断现有保护措施是否能控制风险在可容忍范围内,实例验证了模型的可行性。     

AFRA – Heuristic expert system to assess the atmospheric risk of sulphide waste dumps

In 2006, an unprecedented atmospheric confined space accident took place in a sampling shed at the Sullivan Mine in Kimberley, British Columbia. This accident suggests that a risk assessment should be carried out on a regular basis at mine reclamation sites for many years after closure. In this paper, an Atmospheric Fuzzy Risk Assessment (AFRA) tool is described that can assess atmospheric risk given heuristic and measured data at such sites. It can also serve to transfer knowledge about atmospheric hazards in an enclosed structure. The system uses fuzzy logic to input and output information and to perform weighted inferencing. The paper describes the developmental process as well as system verification and validation based on a number of known test and reference waste dumps. AFRA is a heuristic expert system based on fuzzy logic and the first tool that was developed to assess the atmospheric risk of mine waste dumps. The atmospheric risk is estimated by fuzzy Mamdani system given the values of four major elements of risk comprising of: gas generation, gas emission, gas confinement, and human exposure. The ability of AFRA to adapt its risk assessment to different climate conditions is explained. There are many physical, chemical, and environmental factors which fluctuate over time affecting oxygen-depletion in waste dumps. AFRA can help mining engineers and mine managers recognize this type of danger when conducting a confined space inventory at a reclamation site.     

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.     

基于LOPA逻辑的罐区多米诺效应定量风险评估*

为了更好地降低化工企业罐区事故造成多米诺效应的风险,提出1种基于保护层分析（LOPA）的定量风险评估程序。首先,阐述基于保护层分析(LOPA)逻辑的多米诺定量风险评估流程,即引入包括可用性、有效性及3种逻辑门定义及量化的安全屏障定量评估;然后,利用LOPA的分析逻辑将安全屏障融入多米诺定量风险评估框架中;最后,选取2×2 000 m3苯乙烯罐区为对象,识别防火层与喷淋冷却系统2种安全屏障并开展基于LOPA逻辑的罐区多米诺效应定量风险评估,得出安全屏障能有效地降低多米诺事故发生频率及罐区个人风险的结论。研究结果表明:该分析方法可为化工企业开展多米诺效应定量风险评估提供参考。     

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.