基于动态信息技术的设备主动维护预知平台的设计

石化企业规模大、设备种类繁多且分布广,为规范设备的管理流程、提高设备的管理水平及设备可靠性,提高企业的经济效益和安全性,建立了基于Oracle数据库与RBI和RCM技术的设备预知维护信息平台,并结合RBI及RCM技术信息输入与安全评价方法,实现设备的故障预知及维护规范。该平台与石化的生产运行管理相结合,可实现设备的信息化管理,在及时排除设备故障隐患的同时,保障设备的正常运行,为改善企业生产安全现状和提高设备管理水平,提供了新的方法。     

Research and application of risk and condition based maintenance task optimization technology in an oil transfer station

Oil transfer stations of PetroChina mostly scatter in Gobi, mountain areas or other sparsely populated areas, inconvenient transportation and absent professional engineers often delay the best time to repair the machines. Time-or interval-based maintenance (TBM) accounts for almost 100%, while, On-condition maintenance and other proactive maintenance are seldom adopted. TBM not only can't prevent happens of equipment fault but also cause the waste of the maintenance resource. In order to allocate maintenance resources reasonably, ascertain the minimum preventive maintenance requirement, ensure the reliability, availability and safety, this paper carries out a research on Risk and Condition Based Maintenance (RCBM) task optimization technology. Utilizing the internet of things (IOT), real-time database, signal-processing, Gray Neural Network, probability statistical analysis and service oriented architecture (SOA) technology, a Risk and Condition Based Indicator Decision-making System (RCBIDS) is built. RCBIDS integrates RCM, condition monitoring system (CMS), key performance management module, file management module, fault and defect management module, maintenance management module together, which aims to realize remote condition monitoring, maintenance technical support services (TSS), quantitative maintenance decision-making, and to ensure the Reliability, Availability, Maintainability and Safety (RAMS). The Predictive Maintenance Indicator model, reliability prediction model and Key Performance Indicator (KPI) model, which are embedded in the RCBIDS, are constructed separately. An engineering case shows that the risk and condition based maintenance task optimization technology can be used to optimize maintenance content and maintenance period, to minimize maintenance deficiencies and maintenance surplus, and to prolong the lifespan of equipment.     

石油化工储存装置定量风险评价方法研究

提出通过基础失效概率数据库、事故树分析、事件树分析3种方式来确定重大事故的发生概率.阐述了外界气象条件和人员分布情况对风险的影响和确定方法,给出了利用区域网格方式计算装置在平面某点的个人风险叠加模型和社会风险计算方法.最后,研制开发了石油化工储存装置定量风险评价软件,利用该软件计算了某化工厂4个储存装置所产生的个人风险...     

输油气站场综合风险评价技术研究

为完善国内输油气站场综合风险评价技术,提出一种站场综合风险评价模型。该模型基于模糊集理论,重点对传统的RCM与RBI技术进行改进与完善。将故障(失效)后果划分为伤亡后果、经济损失、环境影响和无形损失;采用模糊推理系统代替原有的算法进行计算设备风险,将动设备与静设备的风险转换为统一标度,得到站场综合风险值;最后采用雷达图显示站内设备的风险分布状况。实例分析表明,所建立的综合风险评价模型能够有效地解决定性风险与定量风险的融合问题,可为输油气站场的风险管理提供决策依据。     

Recursive Operability Analysis as a decision support tool for Risk-Based Maintenance

This work was developed with the support of MEMC, one of the most important producers of ultra-pure silicon wafers for electronic applications throughout the world. The availability of ultra-pure water is of prime importance in the silicon production process. In order to maximize the availability of UP water, MEMC has developed a preventive maintenance program and a detailed record of each maintenance intervention is recorded. This has allowed a complete failure rate data bank to be developed. In order to optimize the maintenance intervention, a Recursive Operability Analysis (ROA) has been used as a decision support tool. The results of the ROA, coupled with the failure rates, have made it possible to calculate the expected number of events (ENE) of various top events (TEs). The magnitude of each TE has been estimated on the basis of the monetary losses provoked by each event. The risk then has been calculated and the events ranked on this basis. Maintenance policies have been optimized with the aim of reducing the risk of the top ranked events.     

Building an Executive Information System for Maintenance Efficiency in Petrochemical Plants—An Evaluation

This study used the manufacturing process in the petrochemical industries as an example and developed a dedicated maintenance programme and executive information system (EIS) for this industry. The software for EIS was established on a CMMS platform, with logical and extractive analysis used to store the information in a KPI databank. The system developed can provide plant managers and engineers with a complete summary of information and keep them updated regarding the present status of their maintenance efforts. The objective of this study was to establish a management system for maintaining knowledge in the petrochemical industries, such as the management of standard operating procedures (SOPs), historical records and the analysis of data for the facility. To design the software, a review of petrochemical facility was purposed to enhance the maintenance efforts and facilitate the decision-making process. The main functions of the system include asset reliability analysis, failure analysis and maintenance benefit cost analysis. For the petrochemical industry, the impact of safety and environment caused by equipment malfunction is more substantial than that of other industries. If executives can manage essential points effectively and make decisions according to a key performance index, risks to safety and environment, which result from equipment malfunction, can be decreased and safety can be enhanced for petrochemical refineries.     

Improved qualitative fault propagation analysis

Fault propagation analysis is the cornerstone to assure safe operation, optimized maintenance, as well as for the management of abnormal situations in chemical and petrochemical plants. Due to plant complexity and dynamic changes in plant conditions, current approaches have major limitations in identifying all possible fault propagation scenarios. This is due to the lack of realistic equipment and fault models. In this paper, practical framework is proposed to synthesize and assess all possible fault propagation scenarios based on robust modeling methodology. Fault models are constructed where deviations are identified and associated with symptoms, faults, causes, and consequences. Fault models are tuned using real time process data, simulation data, and human experience. The proposed system is developed and applied on case study experimental plant.     

Risk-based maintenance policy selection using AHP and goal programming

Maintenance policy selection is a multiple criteria decision making. The criteria often considered are cost and reliability of maintenance. There has been a growing interest in using risk of accidents as a criterion for maintenance selection. This paper presents an approach of maintenance selection based on risk of equipment failure and cost of maintenance. Analytic hierarchy process (AHP) and goal programming (GP) are used for maintenance policy selection. A case study in a benzene extraction unit of a chemical plant was done. The AHP results show that considering risk as a criterion, condition based maintenance (CBM) is a preferred policy over time-based maintenance (TBM) as CBM has better risk reduction capability than TBM. Similarly, considering cost as a criterion, corrective maintenance (CM) is preferred. However, considering both risk and cost as multiple criteria, the AHP–GP results show that CBM is a preferred approach for high-risk equipment and CM for low risk equipment.     

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 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.     

稠油热采井管柱失效动态风险分析研究

为保证稠油热采井筒管柱的安全运行,采用故障树与贝叶斯网络相结合的方法开展稠油热采井管柱失效风险分析,应用故障树分析方法定性识别管柱失效诱因,建立稠油热采井管柱失效场景演化模型,并将故障树转化为贝叶斯网络模型,应用贝叶斯网络对管柱失效风险进行定量分析,得出热采井管柱失效的关键致因和管柱失效的动态失效概率,以新疆油田某区块热采井的管柱失效为对象进行了案例分析。研究结果表明,该方法可为稠油热采井管柱失效风险分析及井筒完整性管理提供理论支撑和工程设计参考。     

以可靠性为中心的维修思想

随着以可靠性为中心的维修(RCM)在国际上的推广和应用,其理论和方法的研究逐渐受到人们的重视.从RCM的定义和基本思路出发,介绍了以可靠性为中心的维修思想的形成和发展过程、RCM原理的基本内容.最后介绍了RCM的发展动态,并就RCM的研究方向进行了探讨.     

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.     

Reliability and availability modeling of Subsea Xmas tree system using Dynamic Bayesian network with different maintenance methods

Subsea Xmas tree is a vital equipment for offshore oil and gas development. Aiming at the fault mode of subsea Christmas tree system under production conditions, the fault tree of subsea tree system was established, which was transformed into Dynamic Bayesian network, and the reliability and availability of subsea tree system with different repair states are quantitatively analyzed. In this paper, the DBNs are partially verified by the method based on three axes. The results show that the reliability of subsea vertical tree system is slightly higher than that of subsea horizontal tree system. After repair and maintenance, the performance of subsea tree system has been significantly improved, and the improvement of the system performance by preventive maintenance is more obvious. Compared with the perfect repair, the performance of the system with imperfect repair is not significantly reduced. Compared with perfect repair & preventive maintenance, the performance of the system with imperfect repair & preventive maintenance is slightly reduced. In addition, the influence of failure rates and degradation probability on reliability and availability is analyzed. By comparing the influence of failure rates on the system performance of non-maintenance and maintenance, it is found that the change of failure rates has the greatest influence on the reliability and the least influence on the availability of perfect repair & preventive maintenance. By comparing the performance of each component in the subsea tree system, it is found that the failure rates has the most obvious influence on the chock module, and gate valve and tree cap have the most significant influence on the reliability of the system. In order to improve the reliability of subsea tree system, it is necessary to improve the reliability of chock module, gate valve and tree cap.     

Methodology for computer aided fuzzy fault tree analysis

Probabilistic risk assessment (PRA) is a comprehensive, structured and logical analysis method aimed at identifying and assessing risks of complex process systems. PRA uses fault tree analysis (FTA) as a tool to identify basic causes leading to an undesired event, to represent logical dependency of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event.To conduct a quantitative fault tree analysis, one needs a fault tree along with failure data of the basic events (components). Sometimes it is difficult to have an exact estimation of the failure rate of individual components or the probability of occurrence of undesired events due to a lack of sufficient data. Further, due to imprecision in basic failure data, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising out of subjectivity of the data.This paper presents a methodology for a fuzzy based computer-aided fault tree analysis tool. The methodology is developed using a systematic approach of fault tree development, minimal cut sets determination and probability analysis. Further, it uses static and dynamic structuring and modeling, fuzzy based probability analysis and sensitivity analysis.This paper also illustrates with a case study the use of a fuzzy weighted index and cutsets importance measure in sensitivity analysis (for system probabilistic risk analysis) and design modification.     

基于模糊评判和RCM的CTCS-3级车地通信子系统维修决策

CTCS-3级车地通信子系统是列控系统的重要组成部分之一,且列控系统需求的列车位置、行车许可、临时限速等安全信息都由其提供,因此,对其进行可靠性分析具有十分重要的意义。采用贝叶斯网络对系统进行可靠性分析,并对维修方式进行了讨论。首先,根据车地通信子系统的功能与结构构建其贝叶斯网络模型。然后,综合考虑维修性、共因失效等因素,对车地通信子系统进行可靠性分析。最后,在可靠性分析的基础上运用模糊综合评判法对其进行维修决策。结果表明:利用贝叶斯网络的双向推理,不仅可以计算出车地通信子系统的可靠度,还可以有效识别系统的薄弱环节;若不考虑车地通信系统冗余结构中的共因失效,则得到的可靠性指标会偏于乐观。地面GSM-R单元失效是引起车地通信子系统失效的关键事件,因此针对此薄弱环节进行状态维修检查能够有效降低事故的发生概率。     

基于动态贝叶斯网络的石化装置火灾事故动态风险分析

为揭示石油炼化装置事故风险动态特性和事故情景演变路径,在对石化装置进行风险因素分析的基础上构建石化装置火灾事故故障树,基于贝叶斯网络非常规突发事故的演变过程,构建情景演变下的动态贝叶斯网络模型,在综合考虑应急措施的基础上,利用MATLAB软件和联合概率公式计算出各种事故场景的状态概率.以丙烯精馏装置火灾事故为例,结果表...     

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。     

ATA方法在交通事故分析中的应用

从系统工程学的角度出发,将广泛应用于系统安全研究中的事故树分析方法(ATA)应用到交通事故的分析。根据组成交通系统的四大因素(人、车、路和环境因素),总结和归纳了引起交通事故的原因。运用Fault Tree绘制软件,绘制了交通事故的事故树图。对交通事故基本事件概率的算法进行分析,提出用以平衡样本局限性的误差修正系数。并根据事故树基本原理和算法,对交通事故事故树进行最小割集分析、基本事件重要度分析和顶上事件发生概率的定性定量分析。     

基于DFTA的电梯制动器可靠性分析

电梯制动器是电梯最重要的安全部件之一,故研究其可靠性具有重要意义.首先分析了电梯制动器的故障机理并建立了动态故障树模型,其次利用二元决策图和马尔科夫方法对故障树进行了分析计算,得到了影响系统可靠性的相关指标以及制动器的薄弱环节,最后提出了改进措施和建议,为电梯制动器的设计、维修保养及检验提供了科学依据.