基于左右模糊排序法的海上浮动核电站设备可靠性评估

为了评估海上浮动核电站设备的可靠性,通过专家评价对设备的失效情况进行分析,改进岭形隶属度函数,使用左右模糊排序法将模糊数转化为模糊概率,从而建立了海上浮动核电站设备失效概率模型。以海上浮动核电站冷却剂泵和非能动余热排出系统为算例验证模型的有效性,结果表明,提出的方法适用于海上浮动核电站设备可靠性评估,可为海上浮动核电站安全分析提供理论基础。     

基于Bayesian网络的常减压装置设备故障概率分析

为分析影响常减压蒸馏装置平稳运行的设备失效模式及故障部件,基于1 151条设备故障数据,采用Bayesian网络分析方法,分别对离心泵、压缩机、电动机构建基于Bayesian网络的设备故障概率分析模型,分析故障部件、失效模式、故障后果之间的定量概率关系。研究结果表明：离心泵、压缩机、电动机停运的关键致因部件分别为轴承箱密封故障、活塞环故障、轴承故障,同时得到导致设备停运的故障部件敏感度排序。研究结果有助于提高设备故障风险防范及检维修工作效率,同时可为备件优化方案提供思路。     

电站锅炉承压部件失效模式分析

为了将故障模式影响和危害性分析FMECA(Failure Mode Effects and Criticality Analysis,FMECA)与故障树分析FTA(Fault Tree Analysis,FTA)故障模式失效理论引入电站锅炉承压部件安全工程评定领域,建立了以电站锅炉承压部件失效模式分析的正向FTF(FMECA To FTA,FTF)分析模型,对电站锅炉承压部件进行模糊FMECA综合评价。分析了电站锅炉承压部件的失效机理和多因素影响,确定了承压设备的评价因素集合和模糊评价矩阵,以及各级指标因素权重分配的规则,并对电站锅炉承压部件失效的综合评判矩阵模型进行一级评价。采用模糊综合评价的危害度分析CA(Criticality Analysis,CA)结果提供底事件概率并开展定性、定量FTA,以此对电站锅炉承压部件系统失效的发生概率、危害严重程度进行故障模式分析,选择电站锅炉承压部件的故障模式作为顶事件建立事故树,采用Bow-tie模型对电站锅炉蒸汽管道、给水管道、省煤器管、过热器及再热器管、水冷壁管、高温集箱、减温器、锅筒、启动分离器9类主要承压部件失效进行定性和定量分析。结果表明,通过正向FTF法将Bowtie模型引入风险致因并与危害后果相关联,对FMECA进行了系统全面的补充,从而进一步推进了该方法在电站锅炉承压部件系统安全可靠性及失效模式分析中的应用。     

基于FMEA的自动扶梯故障模式危害度研究

本文采用FMEA方法对自动扶梯各系统及部件的失效模式及故障原因进行了分析,建立了自动扶梯驱动主机、梯级链、导轨系统、扶手带等关键部件故障树模型,提出了重要部件故障危害度评估方法,研究了基于RCM的自动扶梯维护与检验技术,有利于实现自动扶梯科学维修,降低事故发生频率,对提高设备使用安全可靠性和智能运维管理能力具有参考作用。     

基于改进二元语义的滑坡诱发管道失效可能性评估北大核心CSCD

为评估滑坡诱发管道失效的可能性,识别导致管道失效的主要因素,建立基于改进二元语义的滑坡诱发管道失效可能性评估模型。首先,构建由致灾影响因素、承灾敏感程度和监测治理情况3方面组成的滑坡诱发管道失效可能性评估指标体系;然后,采用网络层次分析法(ANP)和变异系数法确定主客观权重,并基于最小偏差求组合权重;最后,应用改进二元语义的相关分析模型对滑坡诱发管道失效可能性进行分析计算。分析结果表明,将最小偏差理论和改进二元语义结合用于滑坡诱发管道失效可能性分析,使评估结果更加符合工程实际。     

降低电梯制动试验检验风险的研究

为有效预防因电梯制动试验失效导致的设备损坏或人员受伤事故,本文通过研究国家相关和安全技术规范对电梯制动试验检验的要求,分析设置电梯制动试验的检验目的,对影响电梯制动试验失效的危险源进行辨识和逐一进行分析,并提出相应地措施和做好制动试验失效的安全保护,从而降低电梯制动试验的检验风险,确保检验安全。     

基于改进二元语义的滑坡诱发管道失效可能性评估

为评估滑坡诱发管道失效的可能性,识别导致管道失效的主要因素,建立基于改进二元语义的滑坡诱发管道失效可能性评估模型。首先,构建由致灾影响因素、承灾敏感程度和监测治理情况3方面组成的滑坡诱发管道失效可能性评估指标体系;然后,采用网络层次分析法（ANP）和变异系数法确定主客观权重,并基于最小偏差求组合权重;最后,应用改进二元语义的相关分析模型对滑坡诱发管道失效可能性进行分析计算。分析结果表明,将最小偏差理论和改进二元语义结合用于滑坡诱发管道失效可能性分析,使评估结果更加符合工程实际。     

人因视角下连续管作业失误影响因素辨识

连续管作业常发生卡钻、工具失效、连续管失效、设备故障等事故,为预防连续管作业人因失误事故的发生,应用人因分析与分类系统(HFACS)识别出30个影响因素,采用决策试验与评价试验法(DEMATEL)和解释结构模型法(ISM)研究影响连续管作业人因失误的关键因素、复杂关联关系及影响程度,建立了连续管作业人因失误影响因素的递阶解释结构模型。结果表明：工艺设备变化、人力资源、安全管理制度、设计的合理性、生理状况、心理状态、资源环境和技术环境等因素是造成连续管作业人因失误的根源性因素和深层因素,资金资源、运营操作、设备的管理、经济环境及监督岗位设置等是直接影响因素;连续管作业人因失误风险的发生甚至恶化的关键原因是因素之间相互影响;对关键因素的识别和预警可减少连续管作业人因失误风险的发生。研究结论可为提高连续管作业安全管理水平提供决策参考。     

核电站中处理人的行为问题的系统方法

引发事件的失误原因或者作为行为趋向的一部分统称为人的行为问题.总结出了核电站中处理人的行为问题的系统方法,即从问题的识别与描述、事件调研、原因分析到开发纠正行动这样一个过程.结合核电站实际,着重介绍了人误原因的识别,如根原因分析技术和起因树.     

基于失效模式的电力企业事故分析系统构建

为确保电力企业安全生产高效运行，根据事故致因理论和安全系统过程的基本原理，建立基于失效模式的事故分析系统，分析已发生的事故、违章、未遂等管理失效点的数据，揭示人员行为表现形式。结果表明：人为、组织、管理等因素共同导致管理流程失效；人因失误和管理失效是事故发生的最主要原因，占比均达40%以上，组织管理失效占比达到11%以上，而设备原因占比仅为6%;传统分析方式对组织和制度原因分析较少，多从个人角度找原因，管理原因深度不够，多停留在事件表面。通过事故分析，确定对应的失效模式，找到对应的解决策略，识别与控制潜在的安全风险。     

An integrated off-on line approach for increasing stability and effectiveness of automated controlled systems based on pump dependability—case study: Offshore industry

Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standard methodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshore industry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries are considered according to OREDA classification. The approach identifies the critical pump and their fault through which the major hazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is then performed for the worst pump which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection which ultimately enhance overall operational effectiveness.     

An extension to Fuzzy Fault Tree Analysis (FFTA) application in petrochemical process industry

Fault Tree Analysis (FTA) is an established technique in risk management associated with identified hazards specific to focused fields. It is a comprehensive, structured and logical analysis method aimed at identifying and assessing hazards of complex systems. To conduct a quantitative FTA, it is essential to have sufficient data. By considering the fact that sufficient data is not always available, the FTA method can be adopted into the problems under fuzzy environment, so called as Fuzzy Fault Tree Analysis (FFTA). This research extends FFTA methodology to petrochemical process industry in which fire, explosion and toxic gas releases are recognized as potential hazards. Specifically, the case study focuses on Deethanizer failure in petrochemical plant operations to demonstrate the proposed methodology. Consequently, the study has provided theoretical and practical values to challenge with operational data shortage in risk assessment.     

Importance and uncertainty analysis of flue gas scrubber systems with extreme reliability parameter values

Although reliability analyses have been used to improve the reliability of industrial systems, generic reliability data from publications, such as component failure intensities and repair times, are used to calculate reliability measures instead of the real reliability data collected from the plant. One reason is that the repair history of the components is not well managed in the plant. In this work, the effect of extreme reliability parameter values on system reliability and unavailability is studied. To do this, importance and uncertainty analysis of the components of flue gas scrubber systems is carried out, and results calculated with the extreme reliability parameter values are compared with those with the mean reliability values of the systems. The different reliability parameter values can give us totally different ranks of the components critical to the reliability of the representative scrubber system. Consequently, the effort to establish a reliable database is emphasized to perform accurate reliability analysis of the system.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

Measuring and analyzing adaptive capacity at management levels of resilient systems

Resilience engineering (RE) is capable of handling disruptive events and controlling their consequences in process industries such as petrochemical plants. This study aims at analyzing the level of adaptive capacity and identifying effective factors on developing adaptive capacity in the organizational structure of process industries. The data of this study were obtained through direct observation and a structured questionnaire in a petrochemical plant. Managers at all levels participated in the survey. Data envelopment analysis (DEA), which is a mathematical approach, was used to compute and analyze the role of the factors contributing to adaptive capacity. The results indicated that reporting safety issues played a central role in enhancing adaptive capacity at all management levels. Both middle management and low-level management emphasized the importance of management commitment, whereas top-level management considered flexibility as a vital factor in managing disruptions and reducing accidents. The findings of this study could be useful for managers and other decision-makers to improve safety in process industries.     

Improvement of integrity management for pressure vessels based on risk assessment - A natural gas separator case study

The process of oil and gas processing plant is complex, the types of pressure vessels are rich, and the functions are critical. However, the working medium is mostly untreated medium, and the hazard factors are complex, which poses a threat to the safe production of oil and gas processing plant. Based on PDCA cycle, this paper establishes a six-step links of integrity management for sustainable improvement of pressure vessels. The typical failure modes of pressure vessels are determined, and the fishbone diagram of risk factors under each failure mode is compiled. Risk quantification and classification of pressure vessels based on failure modes (RBFM) is innovatively proposed. Avoiding incalculable failure frequency index, the process quantification of failure possibility is formed according to the development of hazard factors. A failure consequence calculation model based on the leakage affected area was established. Combined with the failure probability level and risk level, the hierarchical inspection strategy for pressure vessels under different failure modes is established. Finally, the method is applied to the natural gas separator of H processing plant. The research results show that RBFM proposed in this paper can meet the requirements for rapid and accurate risk assessment of pressure vessels in oil and gas processing plant. This paper establishes a safe production barrier for the pressure vessel and improves the intrinsic safety of the equipment.     

Development of a risk-based maintenance (RBM) strategy for a power-generating plant

The unexpected failures, the down time associated with such failures, the loss of production and, the higher maintenance costs are major problems in any process plant. Risk-based maintenance (RBM) approach helps in designing an alternative strategy to minimize the risk resulting from breakdowns or failures. Adapting a risk-based maintenance strategy is essential in developing cost-effective maintenance policies.The RBM methodology is comprised of four modules: identification of the scope, risk assessment, risk evaluation, and maintenance planning. Using this methodology, one is able to estimate risk caused by the unexpected failure as a function of the probability and the consequence of failure. Critical equipment can be identified based on the level of risk and a pre-selected acceptable level of risk. Maintenance of equipment is prioritized based on the risk, which helps in reducing the overall risk of the plant.The case study of a power-generating unit in the Holyrood thermal power generation plant is used to illustrate the methodology. Results indicate that the methodology is successful in identifying the critical equipment and in reducing the risk of resulting from the failure of the equipment. Risk reduction is achieved through the adoption of a maintenance plan which not only increases the reliability of the equipment but also reduces the cost of maintenance including the cost of failure.     

贫数据条件下海底电缆故障概率评估方法*

为解决贫数据引起海底电缆失效概率评估的不确定性影响,实施有效的海底电缆故障风险管理,提出1种耦合模糊集理论、层次贝叶斯分析（HBA）和贝叶斯网络的海底电缆失效概率评估方法,识别海底电缆失效致因因素,梳理各因素之间的关联关系,并采用贝叶斯网络(BN)构建海底电缆失效模型;根据数据源特点将电缆失效因素分为数据完全缺失和具有稀少的先兆数据,采用模糊集理论(FST)计算完全没有可用数据的失效致因发生概率,通过HBA估计有稀少数据失效致因的发生概率;以失效致因发生概率为输入,通过贝叶斯网络实现海底电缆失效概率的动态评估。研究结果表明:FST-HBA-BN方法可以解决基本风险因素的数据稀缺问题,量化评估海底电缆失效概率,研究结果可为贫数据条件下的电缆失效风险管理提供支撑。     

Development and evaluation of a Naïve Bayesian model for coding causation of workers’ compensation claims

IntroductionTracking and trending rates of injuries and illnesses classified as musculoskeletal disorders caused by ergonomic risk factors such as overexertion and repetitive motion (MSDs) and slips, trips, or falls (STFs) in different industry sectors is of high interest to many researchers. Unfortunately, identifying the cause of injuries and illnesses in large datasets such as workers’ compensation systems often requires reading and coding the free form accident text narrative for potentially millions of records.MethodTo alleviate the need for manual coding, this paper describes and evaluates a computer auto-coding algorithm that demonstrated the ability to code millions of claims quickly and accurately by learning from a set of previously manually coded claims.ConclusionsThe auto-coding program was able to code claims as a musculoskeletal disorders, STF or other with approximately 90% accuracy.Impact on industryThe program developed and discussed in this paper provides an accurate and efficient method for identifying the causation of workers' compensation claims as a STF or MSD in a large database based on the unstructured text narrative and resulting injury diagnoses. The program coded thousands of claims in minutes. The method described in this paper can be used by researchers and practitioners to relieve the manual burden of reading and identifying the causation of claims as a STF or MSD. Furthermore, the method can be easily generalized to code/classify other unstructured text narratives.     

Mitigation of operational failures via an economic framework of reliability,availability, and maintainability (RAM) during conceptual design

Abnormal process situation may lead to tremendous negative impact on sustainability, wellbeing of workers and adjacent communities, company's profit, and stability of supply chains. Failure of equipment and process subsystems are among the primary causes of abnormal situations. The conventional approach in handling failure-based abnormal situations has usually focused on operational strategies. Such an approach overlooks the critical role of process design in mitigating failure, while simultaneously considering the effects of such failure on process economic performance. The aim of this work is to introduce a systematic methodology that accounts for failure early enough during the conceptual design stages. Once a base-case design is developed, the methodology starts by identifying the sources of failure that are caused by reliability issues including equipment, operational procedures, and human errors for a given process system or subsystem. This allows for the identification of critical process subsystem(s) that are more failure-prone or cause greater downtime than other subsystems. Bayesian updating and Monte Carlo techniques are utilized to determine the appropriate distributions for the failure and repair scenario(s), respectively, in question. Markov analysis is used to determine the system availability. Next, the process revenue is described as a function of inherent availability. The effects of failures are incorporated into profitability calculations to establish an economic framework for trading off failure and profitability. In the proposed framework, the economic potential of alternative design scenarios is evaluated and an optimization formulation with the objective of maximizing incremental return on investment (IROI) is utilized to make a design decision. A case study on an ethylene plant is solved to demonstrate the applicability and value of the proposed approach.