带有一个冷贮备部件的两部件串联系统机会维修策略

针对带有一个冷贮备部件的两部件串联系统,本文首先提出一种预防维修与机会维修相结合的维修策略,运用更新报酬定理求得长期运行情况下的单位时间期望维修成本函数的表达式,然后研究最优的机会维修阀值,运用微分学理论求解最优解,最后用实例验证理论的正确性,从实际例子说明本文提出的维修策略可明显节约维修成本,为相应的带有冷贮备的多部件串联系统的维修策略分析提供参考,对企业设备的维修有实际指导意义。     

基于休假时间和基准可靠度的冷贮备二维预防维修策略

研究由两个不同型部件和一个修理工组成的冷贮备可修系统,其中部件1具有优先使用权.为了延长系统的工作时间,考虑对部件1进行非定期预防维修和故障维修相结合的维修策略,并以部件1的故障次数N和预防维修间隔T为二元维修策略(N,T),利用几何过程和更新过程等数学理论,建立以修理工单位时间内平均休假时间为目标函数、以费用率和平均停机时间为约束条件的优化模型,最后运用实例验证了模型的有效性.     

延迟时间生产系统预防维修策略和X-bar控制图联合经济设计

针对生产过程输出质量特性服从正态分布的单部件延迟时间生产系统,研究了预防维修策略和X-bar控制图联合经济设计问题.首先,在将延迟时间系统界定为受控、失控、故障3种结果状态基本内容前提下,根据维修时系统可能存在的实际状态和控制图监测结果关系,分析构建了生产系统维修方式和控制图监测的耦合机制;在此基础上,以期望单位时间最小成本为目标,以系统维修成本、产品质量抽检成本、不合格品的生产费用、维修停机生产损失为考虑成本内容,利用更新过程理论建立了生产系统预防维修策略和X-bar控制图联合决策数学模型;然后基于数值仿真示例,利用遗传算法对模型的求解进行了分析验证.实例分析结果表明,文章模型可行有效.最后,利用部分因子试验设计方法对模型参数进行了敏感性分析.     

基于修理设备的冷贮备可修系统的维修策略

本文研究了两同型部件,一个修理设备组成的冷贮备可修系统.在故障部件不能"修复如新"的条件下,分别以系统中部件1故障次数N,工作时间T和(N,T)为维修策略,利用更新过程和几何过程,求出修理设备经长期运行单位时间内平均停工时间表达式.并在部件寿命的分布函数和修理时间的分布函数已知的情况下,以部件1故障次数N为策略证明存在最优N*使修理设备经长期运行单位时间内平均停工时间最长.最后,通过数值例子验证最优策略的存在性.     

自保护相依多部件系统的预防维修建模及策略优化

自保护技术作为自愈技术的一种,能够使系统在环境或工况条件变化的干扰下以较高可靠性运行。本文构建了一个新的具有相依主要部件和辅助部件的系统可靠性模型,其中主要部件的退化速率与工作中的辅助部件的数量有关。此外,基于定期检测和预防维修策略,本文利用半再生过程技术求解了系统的长期运行平均成本,并以长期运行平均成本最小化为目标给出了系统的最优预防维修策略。最后,以镗刀系统为例,利用所提方法给出了预防更换阈值和检测周期的最优值,以期望为实际维修行为决策提供理论参考。     

基于成本优先级的部件维修策略分析

现实中,系统由于任务、环境等因素,无法实时对故障部件进行维修。因此需要在任务间隔期间或对故障部件进行维修的同时对系统各部件进行预防性机会维修。本文考虑系统期望维修成本,提出了基于部件维修优先级的预防性维修策略。首先把系统期望维修成本分为失效部件维修成本、失效部件导致系统故障的成本和预防性维修其他部件的成本,提出了基于成本的二态和多态系统部件维修优先级度量方法,并在两种场景下分析了如何选择预防性维修部件。其次针对多态系统,研究了基于成本重要度的部件最佳维修水平,并讨论了成本约束下的部件预防性维修策略。最后以某型预警机系统为例进行验证,结果表明,基于成本的预防性维修策略不仅与故障部件位置和相关成本有关,而且还与可用于预防性维修的其他部件重要性有关。     

有延迟修理的两部件串联系统的预防维修策略

研究由两个部件串联组成的系统的预防维修策略, 当系统的工作时间达到T时进行预防维修, 预防维修使部件恢复到上一次故障维修后的状态. 当部件发生故障后进行故障维修, 因为各种原因可能会延迟修理. 部件在每次故障维修后的工作时间形成随机递减的几何过程, 且每次故障后的维修时间形成随机递增的几何过程. 以部件进行预防维修的间隔T和更换前的故障次数N组成的二维策略(T,N)为策略, 利用更新过程和几何过程理论求出了系统经长期运行单位时间内期望费用的表达式, 并给出了具体例子和数值分析.     

基于综合重要度的动车组多部件系统机会维修策略研究

针对我国动车组列车现行维修方式,提出基于综合重要度序列的动车组多部件系统机会维修策略,对提高系统可靠度贡献大的关键部件进行准时优先维修。建立部件综合重要度指数计算模型,并依据其对部件维修优先级进行排序。以维修总成本最低为目标计算单部件最优维修周期及时刻,以系统维修总成本最低为目标,以关键部件的维修时刻为系统停机时刻建立考虑重要度的多部件系统机会维修模型。算例选取某型动车组四级修时更换的四部件系统为研究对象,讨论机会维修里程窗的大小及其偏移量对维修效果的影响,对比结果表明,考虑综合重要度的机会维修策略能够在维修费用基本持平的条件下,保证对系统可靠性贡献大的关键部件的可靠性,进而保证系统的整体可靠性。     

有限队列M/G/1排队系统的解析模型

本文应用广义马尔柯夫更新过程研究了M|C|1|N混合制排队系统的随机特性,提出了一种求解系统稳态概率的算法,从而给出了系统稳态运行指标的计算公式。     

基于产品质量控制的设备维修优化模型

根据产品质量和生产该产品的设备退化状态之间的相关性,设计了周期性设备检测与产品质量控制相结合的设备维修策略。该策略是在对设备进行周期性检测的基础上,利用控制图进行产品质量异常波动的检测,结合对设备退化状态的检测选择设备应采取的维修活动。根据这一设备维修策略,利用更新过程理论和统计过程控制方法,构建了基于产品质量控制的设备维修优化模型,并用遗传算法对其进行求解。通过实例仿真验证了该模型的可行性与有效性。     

A sequential condition‐based repair/replacement policy with non‐periodic inspections for a system subject to continuous wear

This paper studies a condition‐based maintenance policy for a repairable system subject to a continuous‐state gradual deterioration monitored by sequential non‐periodic inspections. The system can be maintained using different maintenance operations (partial repair, as good as new replacement) with different effects (on the system state), costs and durations. A parametric decision framework (multi‐threshold policy) is proposed to choose sequentially the best maintenance actions and to schedule the future inspections, using the on‐line monitoring information on the system deterioration level gained from the current inspection. Taking advantage of the semi‐regenerative (or Markov renewal) properties of the maintained system state, we construct a stochastic model of the time behaviour of the maintained system at steady state. This stochastic model allows to evaluate several performance criteria for the maintenance policy such as the long‐run system availability and the long‐run expected maintenance cost. Numerical experiments illustrate the behaviour of the proposed condition‐based maintenance policy. Copyright © 2003 John Wiley & Sons, Ltd.     

������ʷ�����ٽ�״̬�Ŀ�ά��n��ȡk:Gϵͳ�Ŀ��öȷ���

于一个具有历史相依临界状态的可维修n中取k:G系统, 论文给出了当系统平稳时它的可用度, 一个循环中的平均工作时间和平均失效时间. 并且和不具有年龄相依临界状态的可维修n中取k:G系统进行了比较.     

基于蒙特卡洛算法的航空兵场站装备广义维修过程研究

研究了适用于航空兵场站可修装备在多级备件、(s-1,s)库存下的广义维修过程解析模型。基于Monte Carlo算法,迭代产生大量样本数据,经过拟合发现该维修过程依分布收敛于一对数正态分布;再针对该样本分别以OLS(最小二乘),ML(极大似然)估计进行参数推断,得到了其稳态分布函数,通过了拟合优度检验。最后解出了该情况下装备的稳态维修度,稳态可用度等参数。对比simlox模型对该装备的评估结果,数据吻合程度较为理想。     

Availability and maintenance of series systems subject to imperfect repair and correlated failure and repair

The series system is one of the most important and common systems in reliability theory and applications. This paper investigates availability, maintenance cost, and optimal maintenance policies of the series system with n constituting components under the general assumption that each component is subject to correlated failure and repair, imperfect repair, shut-off rule, and arbitrary distributions of times to failure and repair. Imperfect repair is modeled through the basic idea of the quasi renewal processes introduced by H. Wang, H. Pham, A quasi renewal process and its applications in imperfect maintenance, International Journal of Systems Science 27(10) (1996) 1055–1062; 28(12) (1997) 1329. System availability, mean time between system failures, mean time between system repairs, asymptotic fractional down time of the system, etc., are derived, and a numerical example is presented to compare with the existing models by R.E. Barlow, F. Proschan, Satistical Theory of Reliability of Life Testing, Holt, Renehart & Winston, NY, 1975. Then two classes of maintenance cost models are proposed and system maintenance cost rates are modeled. Finally, properties of system availability and maintenance cost rates are studied. Optimization models to optimize system availability and/or system maintenance costs are developed, and optimum system maintenance policies are discussed through a numerical example.     

考虑非周期检测的视情维修与备件订购联合策略优化

针对单部件系统/关键部件提出视情维修与备件订购联合策略,其中系统退化服从两阶段延迟时间过程且采用非周期检测策略,退化初期以检测间隔T₁检查系统状态,而在第一次识别缺陷状态时,缩短检测周期为T₂、订购备件且进行不完美维修;若系统在随后的退化中被识别处于缺陷状态,执行不完美维修直至超过阈值次数N_max并采取预防性更换,但若在检测周期内发生故障则进行更换。根据系统状态和备件状态分析各种可能更新事件及相应的联合决策,利用更新报酬理论构建最小化单位时间内期望成本的目标函数,优化T₁,T₂, N_max。与对比模型策略相比,算例结果表明所提出的联合策略能有效降低单位时间内的期望成本。     

半马尔科夫下电场可修系统可靠性分析

众所周知,在马尔科夫模型下,在每个状态下的逗留时间服从指数分布,这经常太受限制,尤其是在电场可修系统中,不太适合操作数据要求.因此,提出了利用半马尔科夫过程去研究电场可修系统,而且,利用了马尔科夫更新理论和概率分析方法讨论了电场系统的稳态可用度.最后,通过一个数值例子陈述了获得的结果.     

Tandem behavior of a telecommunication system with finite buffers and repeated calls

The tandem behavior of a telecommunication system with finite buffers and repeated calls is modeled by the performance of a finite capacityG/M/1 queueing system with general interarrival time distribution, exponentially distributed service time, the first-come-first-served queueing discipline and retrials. In this system a fraction of the units which on arrival at a node of the system find it busy, may retry to be processed, by merging with the incoming arrival units in that node, after a fixed delay time. The performance of this system in steady state is modeled by a queueing network and is approximated by a recursive algorithm based on the isolation method. The approximation outcomes are compared against those from a simulation study. Our numerical results indicate that in steady state the non-renewal superposition arrival process, the non-renewal overflow process, and the non-renewal departure process of the above system can be approximated with compatible renewal processes.     

考虑中间库存缓冲区的多目标设备不完美预防维修策略研究

针对考虑库存缓冲区的多目标设备维修问题,以设备维修能力为约束条件,获得随机故障设备的不完美预防维修策略。首先,利用准更新过程,表示出设备的随机故障次数。其次,结合设备故障次数表达式,以最大设备可用度和最小生产总成本为多目标构建不完美预防维修模型,使用粒子群算法求解,优化设备可用度与生产总成本,获得更新周期内的库存量和预防维修周期两个决策变量的最优值。最后,通过算例分析,验证了多目标不完美预防维修模型的可用性。     

Optimal adaptive replacement in a renewal process

In this paper we present an exact method for computing the Weibull renewal function and its derivative for application in maintenance optimization. The computational method provides a solid extension to previous work by which an approximation to the renewal function was used in a Bayesian approach to determine optimal replacement times. In the maintenance scenario, under the assumption an item is replaced by a new one upon failure, the underlying process between planned replacement times is a renewal process. The Bayesian approach takes into account failure and survival information at each planned replacement stage to update the optimal time until the next planned replacement. To provide a simple approach to carry out in practice, we limit the decision process to a one‐step optimization problem in the sequential decision problem. We make the Weibull assumption for the lifetime distribution of an item and calculate accurately the renewal function and its derivative. A method for finding zeros of a function is adapted to the maintenance optimization problem, making use of the availability of the derivative of the renewal function. Furthermore, we develop the maximum likelihood estimate version of the Bayesian approach and illustrate it with simulated examples. The maintenance algorithm retains the adaptive concept of the Bayesian methodology but reduces the computational need. Copyright © 2014 John Wiley & Sons, Ltd.