基于三阶段时间延迟模型的设备预防维修策略

针对设备劣化过程中出现多种非正常状态的问题,提出基于三阶段时间延迟理论的设备维修模型.首先,设备从缺陷到故障的过程并不只服从同一分布,因此,基于三阶段时间延迟模型,将设备故障分为初始缺陷、严重缺陷和故障3个状态,不同阶段定义不同的分布函数以模拟设备的劣化过程;其次,分析设备缺陷、故障发生的时刻与阈值时间点之间的关系,对维修情况进行分类,建立维修总期望费用模型,以单位时间维修费用最小为决策目标,求解出最佳预防维修周期时间和最佳阈值时间;最后,利用遗传算法求解数学模型,通过算例分析验证模型的有效性.所提出方法有助于企业根据维修计划定期进行预防维修检测,根据不同情况对设备出现的初始缺陷状态和严重缺陷状态进行预防维修.     

n中取相邻n-1好的可修系统的可靠性分析

研究了n中取相邻n-1好的直列可修系统,假定每个部件的工作时间和维修时间都 是指数分布且故障部件能"修复如新"时,求出了该系统的可靠度和首次故障前的平均时间等可靠性指标的精确表达式.     

具有马氏相依和维修有优先权的线性相邻2/n(F)可修系统

研究了一个线性相邻2/n(F)可修系统.假定每个部件的工作时间和维修时间均为 负指数分布,且故障部件能够修复如新,但系统中的部件是马氏相依的.利用广义转移概率的 定义和关键部件优先维修的规则,求得了该系统的状态转移概率.当n已知时,获得了该系统 的一些重要的可靠性指标.     

具有单重休假和修复不如新的两部件温贮备系统

研究了修理工单重休假且由两个不同型部件和一个修理工组成的可修型温贮备系统. 系统考虑了在工作故障和贮备 故障都不能 “修复如新”, 部件 1 是修复非新而部件 2 修复如新的条件下, 假设部件的工作寿命、贮备寿命、故障后的修理时间和贮备故障后的修理时间均服 从不同的指数分布, 修理工休假服从一般连续型分布. 运用几何过程理论、补充变量法、 拉普拉斯变换及拉普拉斯--司梯阶变换, 得到了系统的可用度、可靠度和系统首次故障前平均时间等可靠性指标. 最后, 通过数值模拟验证了结果的有效性.     

基于二阶段时间延迟的多产品生产系统生产与维修联合优化研究

针对多产品生产部件串联系统的生产和维修问题进行了研究,提出了基于二阶段时间延迟的联合优化模型。首先,基于生产周期分段理论,将整个周期等分成若干单位时间段,生产与维修共用每段时间,且若干时间段后采取一次预防维修。其次,考虑生产系统的实际生产时间、可用生产时间和维修耗费时间,建立了生产计划与维修计划总成本模型。其中,维修计划考虑缺陷和故障维修费用、维修检查费用,以及非正常状态下设备运行可能产生的不合格产品损失费用;生产计划考虑生产成本、库存成本、延期未交货成本和维修停机后恢复生产的设备启动成本。最后,通过算例分析,计算最优预防维修周期和各单位时间段各产品产量,验证了模型的有效性。     

不可"修复如新"的两相依部件的并联系统的可靠性分析

研究了两相依部件的并联可修系统,在部件的故障分布服从二维指数分布、两个维修分布 为一般分布、且故障部件不能"修复如新的假设下",利用几何过程和补充变量法求出了该系统 的主要可靠性指标.     

基于服务性能合同模式下单部件系统视情维修策略研究

针对供应商系统维修的低效率以及维修成本参数较难获得的问题,提出了基于服务性能合同模式(PBC)下的单部件系统最优视情维修策略模型。首先,基于Gamma分布,描述单部件系统连续递增的退化过程,依据系统实时检测状态与预防维修阈值、故障阈值之间的关系,实施不同的维修策略;其次,分析单位更新周期内的检测次数和使故障设备恢复如新的维修方式,以供应商利润率最大化为目标函数,以最佳维修阈值与检测间隔时间为决策变量,建立以利润为中心的视情维修优化模型;最后,利用改进灰狼算法求解数学模型,通过算例验证所提出模型的有效性,并进行了各维修费用参数对目标函数以及最优维修策略的灵敏度分析。     

考虑缺货的模糊随机缺陷生产系统

针对不可靠的生产过程,研究了生产故障时间为模糊随机变量且允许缺货的缺陷生产系统.建立含缺货费和模糊随机重修费的经济生产批量模型.基于可信性理论,建立其期望费用模型,揭示了费用函数的性质,并证明了使费用最小的最优生产时间的存在性和唯一性,从而确定了最优生产时间的上下界.基于此,设计了最优生产时间的二分法求解过程.最后通过算例验证了所提出模型的有效性,并分析了缺货费用、重修费用和缺陷产品比例对最优生产策略的影响.     

基于半Markov决策过程的劣化系统检测与维修优化模型

针对系统劣化阶段持续时间、检测间隔时间和维修时间都服从一般分布的情况, 提出了一类基于半马氏决策过程的劣化系统检测与维修优化模型. 利用位相型分布近似一般分布简化了求解过程, 并提出了相应的改进值迭代算法. 最后通过算例验证了模型与迭代算法的可行性.     

带工作休假和工作故障的M/M/1/N排队系统性能分析

本文在可修M/M/1/N排队系统中引入了启动时间、工作休假和工作故障策略.在该系统中,服务台在休假期间不是完全停止工作,而是处于低速服务状态.设定服务台在任何时候均可发生故障,当故障发生时立刻进行维修.且当服务台在正规忙期出现故障时,服务台仍以较低的服务速率为顾客服务.服务台的寿命时间和修理时间均服从指数分布,且在不同的时期有不同的取值.同时,从关闭期到正规忙期有服从指数分布的启动时间.本文建立此模型的有限状态拟生灭过程(QBD),使用矩阵几何方法得到系统的稳态概率向量,并应用基本阵和协方差矩阵理论,计算出系统稳态可用度、系统方差、系统吞吐率、系统稳态队长及各系统稳态概率等系统性能指标.同时,通过数值实验对各系统参数对系统性能的影响进行了初探.文中的敏感性分析体现了这种方法的有效性和可用性.实验表明,文中提出的模型,可有效改善仅带有工作休假或工作故障策略排队模型的系统性能.     

An Inspection Policy for Deteriorating Processes Using Delay-Time Concept

A method for determining the discrete time points of inspection for a deteriorating single-unit system under condition-based maintenance is developed. The system is in a normal state, a symptom state or a failed state. A delay-time model is utilized to describe the transition of the states. The transition time from a normal state to a symptom state and that from a symptom state to a failed state are derived assuming continuous deteriorating processes based on a reaction rate model which is categorized as a failure physics model. Failed-dangerous and failed-safe probabilities of an imperfect inspection are considered. A method for minimizing the long-run average cost per unit time is formulated. The characteristics and sensitivity of the proposed method are investigated.     

Optimal design for inspection and maintenance policy based on the CCC chart

In this paper, the concept of cumulative count of conforming chart (CCC chart) is applied in inspection and maintenance planning for systems where minor inspection, major inspection, minor maintenance and major maintenance are available. Several inspection and maintenance plans are defined and studied quantitatively. Analytic expressions of relevant statistics and their expectations are derived. These inspection and maintenance plans are optimized from an economic consideration.     

相依多模失效下冷贮备系统最优切换及视情维护决策

针对存在冲击影响的冷贮备系统,研究其最优切换及视情维护决策问题.首先,在系统结构和切换式运行和维护特性分析的基础上,制定基于周期切换和状态检测的切换式离线视情维护策略;其次,建立累积冲击过程影响下系统退化所致的软失效和极端冲击过程所致的硬失效竞争可靠性模型;再次,通过分析两类冲击过程影响下系统运行与备用设备交替使用、维修过程中的状态转移特性,重点推导各检测周期时刻系统状态概率分布的迭代计算模型;然后,以系统平均费用率最小为目标,建立解析决策模型,以求解系统的最优切换周期和维护阈值.最后,以矿井主通风系统为案例验证策略及模型的有效性,并分析模型对参数的灵敏度.结果表明,系统的最优维修策略随机冲击影响的不同而变化显著.     

基于马尔可夫过程的健康状态评估模型

故障预测与健康管理（PHM）的思想是通过状态监测和诊断技术获取装备状态和故障信息,预测其故障发展趋势,采取更有针对性的维修措施,从而大大提高装备维修管理的精确化。对装备系统的健康状态进行评估是实施PHM的基础,研究了基于马尔可夫过程的健康评估问题,运用马尔可夫模型方法,将部件系统退化过程描述为有限状态转移过程,建立了基于马尔可夫的健康状态评估模型,对PHM系统进行评估并对剩余寿命进行预测,最后进行了案例分析,验证了模型的可行性。     

Risk assessment model of mining equipment failure based on fuzzy logic

The systematic maintenance of mining machinery and equipment is the crucial factor for the proper functioning of a mine without production process interruption. For high-quality maintenance of the technical systems in mining, it is necessary to conduct a thorough analysis of machinery and accompanying elements in order to determine the critical elements in the system which are prone to failures. The risk assessment of the failures of system parts leads to obtaining precise indicators of failures which are also excellent guidelines for maintenance services. This paper presents a model of the risk assessment of technical systems failure based on the fuzzy sets theory, fuzzy logic and min–max composition. The risk indicators, severity, occurrence and detectability are analyzed. The risk indicators are given as linguistic variables. The model presented was applied for assessing the risk level of belt conveyor elements failure which works in severe conditions in a coal mine. Moreover, this paper shows the advantages of this model when compared to a standard procedure of RPN calculating – in the FMEA method of risk assessment.     

加速冲击损伤退化系统剩余寿命预测及预测维修决策

随着检测传感技术的发展,诸如风力发电机叶片等可对其状态进行检测,并依据检测结果进行剩余寿命预测.但此类系统在运行中受环境冲击影响较大,如何对冲击影响下的系统剩余寿命进行预测,并结合预测结果进行经济可靠的维修决策是一个值得研究的问题.对此,针对状态可检测的连续退化系统,研究考虑加速冲击损伤特性下的系统剩余寿命预测及基于预测的维修决策.首先,考虑自然退化和与退化相关的冲击损伤,构建加速冲击损伤退化模型和剩余寿命预测模型;其次,制定基于周期检测的状态维修与预测维修相结合的混合维修策略,并推导不同维修活动的发生概率;然后,构建以长期平均费用率最小为目标,以检测间隔和故障率阈值为决策变量的决策模型,并给出了优化解法;最后,以风力发电机叶片为案例验证模型的适用性和有效性,对系统的参数进行灵敏度分析,并与未考虑加速冲击损伤和未考虑预测的维修决策结果进行对比分析.     

Failure analysis of engineering systems with preventive maintenance and failure interactions

Optimal operation and maintenance of engineering systems heavily rely on the accurate prediction of their failures. Most engineering systems, especially mechanical systems, are susceptible to failure interactions. These failure interactions can be estimated for repairable engineering systems when determining optimal maintenance strategies for these systems. An extended Split System Approach is developed in this paper. The technique is based on the Split System Approach and a model for interactive failures. The approach was applied to simulated data. The results indicate that failure interactions will increase the hazard of newly repaired components. The intervals of preventive maintenance actions of a system with failure interactions, will become shorter compared with scenarios where failure interactions do not exist.     

Competency-based on-the-job training for aviation maintenance and inspection--a human factors approach.

More than 90% of the critical skills that an aviation maintenance technician uses are acquired through on-the-job training (OJT). Yet many aviation maintenance technicians rely on a 'degenerating buddy system', 'follow Joe around', or unstructured approach to OJT. Many aspects of the aviation maintenance environment point to the need for a structured OJT program, but perhaps the most significant is the practice of job bidding which can create rapid turnover of technicians. The task analytic training system (TATS), a model for developing team-driven structured OJT was developed by the author, and first introduced in Boeing Commercial Airplane Group to provide competency-based OJT for aviation maintenance and inspection personnel. The goal of the model was not only to provide a comprehensive, highly structured training system that could be applied to any maintenance and inspection task, but also to improve team coordination, attitude and morale. The first goal was accomplished by following the systems eight-step process, the latter through incorporating human factors principles such as decision making, communication, team building and conflict resolution into the process itself. In general, the process helps to instill mutual respect and trust, enhance goal-directed behavior, strengthen technicians' self-esteem and responsiveness to new ideas and encourage technicians to make worthwhile contributions. The theoretical background of the model is addressed by illustrating how the proven training methodologies of job task analysis and job instruction training are blended with human factors principles resulting in a unique team-driven approach to training. The paper discusses major elements of the model including needs identification, outlining targeted jobs, writing and verifying training procedures, an approval system, sequencing of training, certifying trainers, implementing, employing tracking mechanisms, evaluating, and establishing a maintenance/audit plan. Relevance to industry. TATS has been successfully installed in several maintenance and inspection areas of The Boeing Company. Four major U.S. airlines--United Airlines, TransWorld Airlines, Northwest Airlines, and USAirways have participated in two years of development and field testing in their maintenance operations (assisted by the author and Dr. Barbara Kanki of NASA Ames Research Center).     

Optimal inspection interval for a k-out-of-n system with non-identical components

In this paper, we develop a continuous-time discrete-state model for periodic inspection of a k-out-of-n cold-standby system with non-identical components. A perfect switching system detects the components’ failures, and the failed component(s) are repaired during the next inspection interval, and then added to the standby queue. The system can be in different states depending on the combination of working components and the order of the components on the standby queue at the beginning of an inspection interval. We present a matrix-based approach to determine the system states and calculate the system-states transition probabilities and the transition matrix. We calculate the expected total cost of the inspection intervals by determining the system state at the beginning and end of each inspection interval and calculating the inspection cost matrix. The expected total inspection cost consists of the system downtime cost, components repair cost, system repair cost, and system inspection costs. Finally, we minimize the system’s expected total cost by determining the system’s optimal inspection interval. The results show that determining the optimal inspection interval decreases the system's total inspection interval cost up to 60 % in comparison with the cases when the inspection interval is selected arbitrarily.