A framework to estimate the risk-based shutdown interval for a processing plant

Petrochemical plants and refineries consist of hundreds of pieces of complex equipment and machinery that run under rigorous operating conditions and are subjected to deterioration over time due to aging, wear, corrosion, erosion, fatigue and other reasons. These devices operate under extreme operating pressures and temperatures, and any failure may result in huge financial consequences for the operating company. To minimize the risk and to maintain operational reliability and availability, companies adopt various maintenance strategies. Shutdown or turnaround maintenance is one such strategy. In general, shutdown for inspection and maintenance is based on the original equipment manufacturer's (OEM) suggested recommended periods. However, this may not be the most optimum strategy given that operating conditions may vary significantly from company to company.The framework proposed in this work estimates the risk-based shutdown interval for inspection and maintenance. It provides a tool for maintenance planning and decision making by considering the probability of the equipment or system for failure and the likely consequences that may follow. The novel risk-based approach is compared with the conventional fixed interval approach. This former approach, characterized as it is by optimized inspection, maintenance and risk management, leads to extended intervals between shutdowns. The result is the increase in production and the consequent income of millions of dollars.The proposed framework is a cost effective way to minimize the overall financial risk for asset inspection and maintenance while fulfilling safety and availability requirements.     

成套装置动态风险管理专家系统

传统的设备管理模式造成设备非计划停机次数较多、故障频繁、可靠性和可用性不高等问题。为了解决上述问题,开发了成套装置动态风险管理专家系统,该系统包括动态风险监控、数据存储、失效模式及损伤机理判别、动态风险评估、风险辅助分析5个流程。该系统通过GIS平台进行展示,使用户可以直观、方便地查找、定位管线和容器位置,实现了高风险设备的风险展示、管道剩余寿命不足报警功能和管道冲蚀图例展示。将该专家系统进行了工程应用,得到容器和管道的潜在损伤机及其风险等级,针对不同风险等级的设备,生成了不同的检维修策略,为工程应用带来了很大的方便。     

Risk-based maintenance (RBM): a quantitative approach for maintenance/inspection scheduling and planning

The overall objective of the maintenance process is to increase the profitability of the operation and optimize the total life cycle cost without compromising safety or environmental issues. Risk assessment integrates reliability with safety and environmental issues and therefore can be used as a decision tool for preventive maintenance planning. Maintenance planning based on risk analysis minimizes the probability of system failure and its consequences (related to safety, economic, and environment). It helps management in making correct decisions concerning investment in maintenance or related field. This will, in turn, result in better asset and capital utilization.

This paper presents a new methodology for risk-based maintenance. The proposed methodology is comprehensive and quantitative. It comprises three main modules: risk estimation module, risk evaluation module, and maintenance planning module. Details of the three modules are given. A case study, which exemplifies the use of methodology to a heating, ventilation and air-conditioning (HVAC) system, is also discussed.     

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.     

Using data mining technology to explore causes of inaccurate reliability data and suggestions for maintenance management

Reliability data reflects equipment safety and provides a reference for setting inspection period, thereby serving as crucial information for the implementation of equipment integrity management policies. The calculation foundation of reliability data is maintenance records of adequate data quality. However, maintenance records of doubtful quality are common. Despite excluding poor quality recodes and using only the remaining maintenance recodes to calculate the reliability data, the calculated results generally lack a sufficient degree of confidence. This study applied data mining technology, including quality metrics, the association rule, and clustering, to explore the cause of low-quality maintenance data. The results revealed that the low data quality of maintenance records was due to ineffective maintenance policies, the low integrity of key system columns, nonadherence to the policy, and misunderstanding of column definitions. The proposed method successfully identified the causes of low-quality maintenance records. By incorporating the method into the function module of a CMMS, operators can equip the system with self-diagnosis, self-supervision, and continuous optimization functions.     

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.     

铁路安全预警系统的研究与设计

铁路安全预警系统是向铁路企业安全监察部门提供辅助安全管理决策服务的管理信息系统。该系统在充分利用现有铁路企业信息资源的基础上 ,运用现代安全系统工程的理论和方法 ,对铁路安全监察部门所掌握的数据资料进行加工处理 ,分析预测铁路运输生产系统的安全状况与不利因素 ,从而在管理决策层次上实现铁路安全监察对铁路安全事故的超前预防与控制。笔者全面阐述了该系统的设计背景、设计思想 ,并对系统的信息平台以及逻辑设计进行了详细的分析。铁路安全预警系统的实施 ,将对实现铁路企业安全监察工作信息化、科学化、现代化起到积极重要的推动作用。     

改进的DEMATEL法在航空公司外委维修安全风险分析中的应用

为有效识别和分析外委维修安全风险因素间复杂的影响关系,提出了群决策DEMATEL分析方法。该方法以语言变量和三角模糊数之间的转换为基础,通过群决策理论集结专家信息建立直接影响矩阵;利用DEMATEL分析法对外委维修的安全风险因素进行辨识,实现定性定量相结合的分析。以某航空公司为例,采用该方法分析了14个对外委维修安全影响显著的风险因素。结果表明,在外委维修过程中,航空公司和承修商应重点监控7个原因型因素和中心度排序靠前的6个因素。     

中国民航业安全风险监测与仿真研究

根据系统安全的思想,通过对航空安全历史数据的分析和专家经验,从人员、设备设施、环境和组织管理4个方面,提出中国民航机务、空管、飞行、机场4个分系统安全风险监测指标体系,共102个风险因素指标,并合成为27个行业安全风险监测指标。以民航历史数据为样本,建立资源优化神经网络(RON)模型,将安全风险监测指标与中国民航安全指数相联系,分析安全指数的关键影响因素,达到安全管理决策支持的目的。通过建立的风险监测指标体系和RON模型,可以实现民航整个行业、各分系统及单个指标的安全风险监测和预警。     

基于条码技术的特种设备检测数据溯源平台的研究和应用

利用先进成熟的计算机技术和自动识别技术对特种设备相关业务进行管理已经成为提高效率、节约资源、减少浪费的必要手段,本院研发的“基于条码技术的特种设备检测数据溯源平台”（以下简称溯源平台）,能够实现特种设备全过程的数据动态存储,并全部实现闭环管理,这是国内目前的检验软件没能实现的,本文对该软件的研究目的、研究过程及实现功能等情况作了较为详细的介绍。     

面向客户的特种设备数据服务平台研发与应用

特种设备数据服务平台是基于B／S结构开发的信息管理系统,能面向客户并实现监察机构、检验机构、使用机构三方数据联动,把客户特种设备管理、收费系统、网上报检、历年检验报告查询、检验进度查询、委托业务管理、用户点对点资料传输等实现一站式服务。项目的应用为监察机构、检验机构和企业实现数据资源高效管理,简化业务办理流程,加强企业对特种设备管理的力度提供技术支持。     

民航机务维修系统安全风险监测

从人的因素、飞机的因素、环境因素和管理因素4方面分析了民航机务维修系统安全风险影响因素,结合专家调查意见建立了机务维修系统安全风险监测指标体系,并给出各个指标的含义及其衡量方法。根据机务维修系统安全风险指标及其数据特点,建立了行业机务维修系统安全风险模糊综合评价模型,并进行实例分析。结果表明,采用笔者建立的指标体系和风险模型可以方便地进行机务维修系统的安全风险评价和预警,从而找出主要的安全风险影响因素,为采取安全风险管理措施提供依据。     

基于巡检的高速公路桥梁安全监测与维护研究

针对高速公路桥梁安全评价与维护的需要,在对现行高速公路桥梁安全监测、数据处理方法分析的基础上,应用设备状态监测原理,提出高速公路桥梁安全监测及安全趋势预测的方法。根据我国目前公路桥梁养护技术规范、高速公路桥梁养护运行模式,构建由人、物、理、程四部分组成的基于巡检的高速公路桥梁安全监测与维护体系,该体系实施过程分为准备、巡检、分析和维护4个阶段,即,在不影响高速公路桥梁正常运营下,通过巡检获取桥梁关键部位的状态参数并进行分析和评价桥梁状态,由专家系统或专家评价桥梁病害类型和维护方案。该体系还可对桥梁安全状态进行预判,满足高速公路桥梁预防性养护的需求,其实施将有助于提高高速公路桥梁的管理与维护水平。     

船舶设备事故中的人为因素分析与控制研究

根据设备维修系统设备维修的人为失误环节和船员失误分析模式以及轮机管理人员具有明感知设备的运行状态、隐感知设备的故障趋势等特点,实施有效管控措施。结合航运市场特性,基于设备可靠度,提出风险性和经济性的维修方式策略,可大幅提高航运公司的安全航运水平和经济效益。利用维修系统的信息流,建立了船舶设备维修管理信息系统,整合设备运行状态、船员的综合素质状态及组织管理信息,以便于阻断导致事故发生的事件链,提高航运公司的船舶运输安全。     

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.     

Optimization of test interval for ageing equipment: A multi-objective genetic algorithm approach

Reducing the unavailability of safety systems at nuclear power plants, by utilizing the probabilistic safety assessment (PSA) methodology, is one of the prime goals in the nuclear industry. In that sense, optimization of test and maintenance activities, which are defined within the technical specifications, represents quite popular and interesting domain. Obtaining optimal test and maintenance schedule is of great significance for improving system availability and performance as well as plant availability in general.On the other side, equipment aging has gradually become a major concern in the nuclear industry since the number of safety systems components, that are approaching their wear-out stage, is rising fast. Nuclear power plants life management programs, considering safety components aging, are being developed and employed. The immense uncertainty associated to the available component aging rates databases poses significant difficulties in the process of incorporation and quantification of the aging effect within the PSA and, subsequently, in the decision-making process.In this paper, an approach for optimization of surveillance test interval of standby equipment with highly uncertain aging parameters, based on genetic algorithm technique and PSA, is presented. A standard standby safety system in nuclear power plant is selected as a case study. A Monte Carlo simulation-based approach is used to assess uncertainty propagation on system level. Optimal test interval is derived on the basis of minimal system unavailability and minimal impact of components aging parameters uncertainty. The results obtained in this application indicate the fact that risk-informed surveillance requirements differ from existing ones in technical specifications as well as show the importance of considering aging data uncertainties in component aging modeling.     

大型石化装置安全阀安全保障综合管理体系应用研究

本文研究采用基于风险的完整性综合管理方法解决大型石化企业安A-N管理中存在的问题。阐述了建立安全阀数据库的基本原则，提出根据失效可能性和风险等级制定安全阀分类管理策略，实现分类管理，进行检验组织优化，制定安全阀失效紧急处置指南，以期形成安全阀安全保障综合管理体系，并建立包括网上报检、备阀备件统计管理、风险定量计算等功能的安全阀管理信息系统，在保障安全阀安全运行的同时，提高管理效能，降低管理成本。     

油气生产过程中集输设施安全管理问题研究

针对油气生产中集输设施安全问题导致的油气泄漏引发的问题,以系统的方法分析其观念、技术、方法对集输设施管理的影响。围绕石油企业降本增效和可持续发展战略目标,从投资、建设、管理、养护各环节,管理体制、运行机制、管理方式等各方面系统研究,通过明确职能、落实责任、制定标准、严格程序、科学奖惩、强化管理等手段,从而树立正确管理理念,完善设施投入机制、监督考核机制、激励约束机制,强化企业管理基础工作等方面,提出与该系统工艺流程相适应的管理模式和方法,以管理优化保障工艺优化,延长设施使用寿命,提高系统运行效率,确保安全生产。     

LPG充装站紧急切断阀失效模式分析

紧急切断阀作为LPG充装站的重要安全附件之一,当遇到突发情况时,可远程控制紧急切断阀迅速关闭,避免事故的进一步蔓延。若LPG充装站紧急切断阀安装位置不合理,或缺乏定期检验检查与维护保养,均可能导致紧急切断失效。通过对LPG充装站紧急切断阀的工作原理及安装位置,常见失效模式分析及预防,定期检验检查及维护保养注意事项进行详细研究,为LPG充装站对紧急切断阀进行年度检查及维护保养和相关检验单位进行定期检验提供参考。     

基于马尔可夫的地面控制井下安全阀可靠性评估

为保障地面控制井下安全阀系统的安全运行，防止系统发生故障，建立了井下安全阀可修复系统的马尔可夫模型；针对系统设备构成复杂及共因故障等问题，基于β因子模型描述共因失效，同时将模型划分为3个独立模块，通过克罗内克积方法合并，评估系统可靠性；参照OREDA可靠性数据，定量求解井下安全阀系统可用度、可靠度以及稳态指标，研究模型中状态转移概率对系统稳态可用度的影响。研究结果表明:井下安全阀系统的可用度随时间增长而迅速到达稳态值；系统检修周期应小于2.5 a；根据可靠性分析结果，运营方应考虑系统经济与可靠性间的博弈关系，合理优化系统冗余结构与维修周期管理，防止井下安全阀系统失效。