一般概率分布下考虑预防性维修的ADC 模型可信赖度

克服了马尔可夫假设条件的限制,假定系统寿命、修复性维修和预防性维修的修复时间均遵从一般概 率分布．利用离散时间模型在数值计算方面的优势,建立了离散时间下系统正常工作、修复性维修和预防性维修三 个状态之间的转移关系,在此基础上建立了一般概率分布下考虑预防性维修的ADC 模型的可信赖度D．数值算例 说明了该评估方法有助于选择合适的预防性修复周期来提高系统的效能．     

参数对预防性维修模型的影响分析与仿真

为了给可修部件预防性维修提供科学合理的理论依据,基于随机理论中的连续时间马尔科夫过程,建立了可修部件的预防性维修模型,分析和仿真了预防性维修模型中的维修率及检查率变化对模型稳态值影响。基于可修部件的预防性维修模型,也就是其状态转移图,计算出预防性维修模型的稳态值,分析检查率及维修率对稳态值影响,得出维修率及检查率对可修部件预防性维修模型影响的理论依据。最后借助Matlab软件对所分析出的结果进行了仿真验证。结果表明,理论分析与仿真结果是一致的。明白参数对可修部件预防性维修模型稳态值的影响对正确的选取参数,从而对获得期望的稳态值有一定的帮助。     

基于有效度和维修成本的预防性维修方法

针对机械系统预防性维修周期的盲目性和难预测性,为了对机械系统中的零部件故障加以有效控制,在保证机械系统有效度的同时节约维修成本,研究了多部件连接机械系统预防性维修周期的确定方法.以系统有效度为约束条件,以维修成本最低为目标,以预防性维修周期为变量,建立系统维修优化模型.最后以故障分布形式为威布尔分布的机械系统为例进行仿...     

电站锅炉给水系统维修模型的研究

介绍了可维修性、修复率、平均修复时间、可用度等基本术语.利用马尔可夫过程理论建立了电站锅炉给水自控系统的维修模型,据此模型求得该自控系统的可用度.     

基于仿真的生产设备预防性维修周期研究

为了对生产系统中的设备故障加以有效的控制，从而减少设备故障的发生，文章对生产设备的预防性维修周期问题进行了研究。通过建立生产设备预防性维修的费用模型，利用仿真的方法对不同维修策略的预防性维修周期进行优化选择。该模型综合考虑了修复性维修成本、预防性维修成本和生产损失成本。最后以故障分布形式为威布尔分布的设备为例进行仿真实验，得出设备最优维修周期结果，并阐述了经济原则对预防性维修周期的影响。     

全寿命周期下退化的大规模系统预防性维修策略优化

单元退化情形下,考虑全寿命周期的大规模系统可靠性设计与预防性维修策略的综合优化问题将变得更为复杂.针对单元失效服从威布尔分布的情形,考虑多单元联合的预防性维修模式,构建可靠性约束下大规模系统全寿命周期成本优化模型.单元数量众多带来的组合规模指数增长问题将导致非线性择优困难,利用遗传算法编程快速求解全局最优解,包括设计阶段的单元可靠性和使用阶段的系统预防性维修周期.最后通过典型算例分析验证模型与算法的正确性和有效性,探究维修改善因子、单元可靠性和预防性维修周期等决策变量间的相互关系.研究成果有助于简化系统工程师的可靠性工程设计过程,具有一定的理论和应用价值.     

基于时间应力的装备预防性维修间隔期决策

针对装备服役年限延长,故障率上升的现状,建立了不同数学分布下时间应力因子的求解模型.根据所得模型,对现实使用条件下装备的预防性维修间隔期进行了分析确定.为装备使用与保障部门合理地使用维护提供了依据,从而延长装备的寿命,最大限度地发挥其效能;为改革现行的装备维修制度提供参考.     

考虑车辆调度的周期性预防维修模型

维修中心对客户周期性的预防性维修通常只针对单设备进行优化,很少考虑维修车辆的调度问题,因此所得的方案往往不具有操作性.根据设备的故障规律,在研究合理的预防维修次数、维修间隔的前提下,充分考虑维修车辆的调度问题,对维修中心的成本因素进行分析并在满足设备可靠性的基础上建立了维修中心的成本最小化模型.通过仿真分析,得到最优的预防性维修次数,维修间隔和维修车辆路径,证明了模型的可行性和科学性,为维修中心的周期性预防维修提供决策支持.     

基于大数据的电力企业资产组维修策略优化研究

汇总过去若干年的电力设备故障数据,运用大数据分析方法,把故障预测技术引入到预防性维修的实践中,提出一种基于大数据的预防性维修策略。首先,根据由状态检测信息得到剩余寿命的预测结果,以预防性维修时的剩余寿命为阀值制定预防性维修策略。然后,根据更新过程理论,建立以电力设备的预防性维修阀值和预测间隔期为优化变量,综合考虑电力设备维修成本、客户满意度、电量销售、停电损失、维修时机选择等约束条件呢,以电力设备平均维修费用最小和电力设备可用度最大为优化目标的预防性维修优化模型。采用人群搜索算法进行优化求解,得到系统最佳的预防性维修阀值和维修预测间隔期。最后,通过引入算例,对所建模型优化仿真求解,得到电力设备最佳的预测周期,在保证电力设备可用度的同时,使电力设备的平均维修费用最小,验证了所建模型的可行性和有效性,从而提高电力企业的整体效益。     

两部件系统视情维修与生产调度的联合优化模型

为了解决生产调度过程中由系统维护维修产生的资源闲置和时间成本增加问题,将系统维修与生产调度联合建模.在众多学者将系统作为整体进行生产调度与维修研究的基础上,考虑系统内各组成部件之间的复杂关系.针对具有经济相关性的两部件系统,以调度作业加工顺序、预防性维修阈值、机会维修阈值作为决策变量,考虑到两部件同时维修比单部件独立维修更为经济,将机会维修引入到建模之中,制订机会维修、预防性维修、故障后更换的视情维修与生产调度结合的联合策略,通过劣化状态空间划分法给出生产调度过程中所有维修组合及其对应维修概率,推导出联合概率密度函数,建立以最小化总加权期望完成时间为目标的联合优化模型.通过数值实验和灵敏度分析验证所提出的策略及模型的有效性.     

A hybrid genetic algorithm to minimize the periodic preventive maintenance cost in a series-parallel system

This study presents a hybrid genetic algorithm (GA) to optimize the periodic preventive maintenance model in a series-parallel system. The intrinsic properties of a repairable system, including the structure of reliability block diagrams, maintenance priority of components, and their maintenance periods, are considered in developing the proposed hybrid GA. The importance measure of components is employed to account for these properties, identify important components, and determine their maintenance priorities. The optimal maintenance periods of these important components are then determined to minimize total maintenance cost given the allowable worst reliability of a repairable system using the GA search mechanism. An elitist conservation strategy is applied to retain superior chromosomes in the iterative breeding process to accelerate the approach toward the global optimum. Furthermore, the response surface methodology is utilized to systematically determine crossover probability and mutation probability in the GA instead of using the conventional trial-and-error process. A case study demonstrates the effectiveness and practicality of the proposed hybrid GA in optimizing the periodic preventive maintenance model in a series-parallel system.     

Availability optimisation of repairable system with preventive maintenance policy

This article investigates optimal steady availability of a repairable system with six states. Both preventive maintenance and corrective maintenance are considered in this article. By probability argument, the system is described as an abstract Cauchy problem. Using the method of strong continuous semi-group theory, we derive the steady availability of the system. Finally, the optimal time to carry out preventive maintenance is analysed theoretically and numerical examples are presented.     

Preventive maintenance scheduling for repairable system with deterioration

Maintenance as an important part in manufacturing system can keep equipment in good condition. Many maintenance policies help to decrease the unexpected failures and reduce high operational cost such as conventional preventive maintenance. But these conventional preventive maintenance policies have the same time interval T that may easily neglect system’s reliability, because the system deteriorates with increased usage and age. Hence, this study has developed a reliability-centred sequential preventive maintenance model for monitored repairable deteriorating system. It is supposed that system’s reliability could be monitored continuously and perfectly, whenever it reaches the threshold R, the imperfect repair must be performed to restore the system. In this model, system’s failure rate function and operational cost are both considered by the effect of system’s corresponding condition, which helps to decide the optimal reliability threshold R and preventive maintenance cycle number. Finally, through case study, the simulation results show that the improved sequential preventive maintenance policy is more practical and efficient.     

A generalized sequential preventive maintenance policy for repairable systems with general random minimal repair costs

A generalized sequential preventive maintenance (PM) policy for repairable systems with general random minimal repair costs is proposed and analysed. After each (planned or unplanned) preventive maintenance, the system has a different failure distribution and the failure rate function increases with the number of preventive maintenances carried out. The criterion for the optimal policy is to minimize the expected cost per unit time for an infinite time span. It is shown that under certain reasonable assumptions, sequential preventive maintenance policy has unique solutions. Various special cases are considered.     

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.     

Scheduling preventive maintenance for oil pumps using generalized proportional intensities models

Percy and Alkali presented generalizations of the proportional intensities model introduced by Cox. They identified several features of these models that are particularly relevant for modelling complex repairable systems subject to preventive maintenance (PM). These include the baseline intensity, scaling factors and explanatory variables. We investigate these aspects in detail and apply the models to five sets of reliability data collected from the main pumps at oil refineries. We use likelihood methods to estimate the model parameters and compare how well the models fit the data. Our analyses suggest that a log‐linear baseline intensity function performs well and that an exponential deterministic scaling function is useful for corrective maintenance. The inclusion of explanatory variables to represent the quality of last maintenance and time since last maintenance also proves to be beneficial. We develop algorithms for simulating the reliability behaviour of a complex repairable system into the future, in order to schedule appropriate maintenance activities, identifying special cases that simplify the algebra. Applying these methods to the oil pump data, we derive recommendations for PM plans and demonstrate that adopting this strategy can lead to substantial savings.     

Sensitivity analysis and comparison of algorithms in preventive maintenance and replacement scheduling optimization models

In this research, new optimization models are developed to determine the optimal preventive maintenance and replacement schedules in repairable and maintainable systems. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability over the planning horizon. Experimental results of a sensitivity analysis on the optimization models are presented and evaluated. These experiments investigate the effect of the parameters on the structure of optimal preventive maintenance and replacement schedules in multi-component systems. Two factorial design experiments based on the cost associated with maintenance and replacement activities and reliability characteristic parameters are constructed and analyzed. In addition, a comprehensive experiment is designed to analyze and compare the efficiency and accuracy of the exact and metaheuristic algorithms.     

A dependability model for TMR system

Much research has been done on the dependability evaluation of computer systems. However, much of this is gone no further than study of the fault coverage of such systems, with little focus on the relationship between fault coverage and overall system dependability. In this paper, a Markovian dependability model for triple-modular-redundancy (TMR) system is presented. Having fully considered the effects of fault coverage, working time, and constant failure rate of single module on the dependability of the target TMR system, the model is built based on the stepwise degradation strategy. Through the model, the relationship between the fault coverage and the dependability of the system is determined. What is more, the dependability of the system can be dynamically and precisely predicted at any given time with the fault coverage set. This will be of much benefit for the dependability evaluation and improvement, and be helpful for the system design and maintenance.     

Optimum preventive maintenance policies for systems subject to random working times,replacement, and minimal repair

This paper proposes, from the economical viewpoint of preventive maintenance in reliability theory, several preventive maintenance policies for an operating system that works for jobs at random times and is imperfectly maintained upon failure. As a failure occurs, the system suffers one of two types of failure based on a specific random mechanism: type-I (repairable) failure is rectified by a minimal repair, and type-II (non-repairable) failure is removed by a corrective replacement. First, a modified random and age replacement policy is considered in which the system is replaced at a planned time T, at a random working time, or at the first type-II failure, whichever occurs first. Next, as one extended model, the system may work continuously for N jobs with random working times. Finally, as another extended model, we might consider replacing an operating system at the first working time completion over a planned time T. For each policy, the optimal schedule of preventive replacement that minimizes the mean cost rate is presented analytically and discussed numerically. Because the framework and analysis are general, the proposed models extend several existing results.