飞利浦Achiva 3.0T磁共振梯度故障分析与维修

目的：通过对飞利浦磁共振Achiva 3.0T的2例梯度系统的故障进行分析、检修和总结，熟悉飞利浦磁共振梯度系统的组成及常用维修方法。方法：了解飞利浦Achiva 3.0T磁共振系统的结构、组成，通过维修手册提供的维系方法，逐步进行完成故障的处理。结果：通过对故障的总结，积累了设备维护方面新的经验，节约了维修时间，降低了维修成本，保障了患者的就诊需求，通过分析故障产生的原因对院内设备进行预防性维护，降低了设备的故障率。     

考虑设备维修与维护的装配作业车间动态生产仿真研究

装配作业车间生产调度的关键是动态协同产品各零件的生产进度以满足产品的齐套需求。设备的随机故障将会扰乱已有的生产计划,给各零件之间的进度协同带来更高的挑战。预防性维护能够提高设备的可靠度以减少故障的发生,但过度的维护又会减少生产加工的时间。从调度规则构成属性的角度分析设备故障将带来的影响,并提出一种考虑设备故障的改进型调度规则。通过仿真试验分析了企业常见的3种预防性维护策略对车间性能的影响和7种代表性调度规则的性能。试验结果表明:预防性维护策略对车间有明显的影响;且考虑了设备故障的调度规则有一定的改进效果。     

可靠度约束下不完全预防性维护经济优化模型EI北大核心CSCD

为解决可修系统设备因维修计划不合理而导致故障频发和资源浪费的问题,在利用包含役龄回退因子和故障率递增因子的混合故障率函数描述设备劣化过程的基础上,建立有限时间内基于可靠度约束的单设备动态不完全预防性维护模型。以铁路某轨道电路设备为例进行维修优化仿真,在设备最低工作可靠度限制下,以更换周期内总维修费用率最小为优化目标,确定其最佳预防性维修次数与弹性维修周期,并对比了无可靠度约束等维修周期维护模型的优化结果。研究表明,本维护模型能够有效保证设备高可靠运用,更好地降低设备故障率、节省维修费用,为制定最佳维修策略提供参考依据。     

可靠度约束下不完全预防性维护经济优化模型

为解决可修系统设备因维修计划不合理而导致故障频发和资源浪费的问题,在利用包含役龄回退因子和故障率递增因子的混合故障率函数描述设备劣化过程的基础上,建立有限时间内基于可靠度约束的单设备动态不完全预防性维护模型。以铁路某轨道电路设备为例进行维修优化仿真,在设备最低工作可靠度限制下,以更换周期内总维修费用率最小为优化目标,确定其最佳预防性维修次数与弹性维修周期,并对比了无可靠度约束等维修周期维护模型的优化结果。研究表明,本维护模型能够有效保证设备高可靠运用,更好地降低设备故障率、节省维修费用,为制定最佳维修策略提供参考依据。     

振动检测技术在大型电机预测性维修上的应用

目前,设备维护开展以预防性维修为主,随着设备运行时间的增长,设备出现重大停机故障的风险大大增加,常规的预防性维修不能满足现场的需求,需要引入状态检测,进行预测性维修。预测性维修可以提前预知设备故障,避免严重设备故障的发生,同时,可以针对性的指导设备维修,减少维护的时间和成本。振动监控是预测性维修的重要手段,通过专用传感器对设备的振动参数收集与分析,可以准确判断设备运行状态,预知设备故障。     

基于案例的动态RCM维修管理模式及共应用分析

介绍了动态RCM、设备重要度分析和设备故障模式风险分析的原理,并结合30万t／年尿素设备动态RCM实施过程,详细介绍了设备重要度分析、设备故障模式风险分析和维修维护策略制定的过程。实践证明：动态RCM对于确定预防性维修需求、优化维修制度具有重要应用价值。     

考虑机会维修的等风险预防性维修策略优化

研究了对流水线生产系统进行等风险预防性维修策略优化的问题。预防性维修计划中包括不完全预防性维修和预防性替换，突发故障用最小维修处理。为了减少预防性维修造成的停产损失，一些预防性维修活动将根据机会维修阈值归并在一起进行。采用遗传算法在满足系统可靠性的前提下，以最小化维修成本为目标优化预防性维修计划。首先建立预防性维修的优化模型；然后设计了模型求解的遗传算法；最后在Emplant仿真环境下，将算法求解的最优预防性维修计划应用到生产系统仿真模型中进行评价，并与传统的故障替换策略进行了比较。     

基于案例的动态RCM维修管理模式及其应用分析

介绍了动态RCM、设备重要度分析和设备故障模式风险分析的原理,并结合30万t／年尿素设备动态RCM实施过程,详细介绍了设备重要度分析、设备故障模式风险分析和维修维护策略制定的过程。实践证明：动态RCM对于确定预防性维修需求、优化维修制度具有重要应用价值。     

基于可靠性的列车预防性多梯度机会维修策略

针对现有城市轨道列车车辆检修策略中的过维修和欠维修，以及机会维修单一等问题，提出一种基于可靠性的预防性多梯度机会维修策略。通过分析历史故障数据，对不同部件设置不同等级的机会维修阈值，建立了灵活的多梯度机会维修策略。在维修策略中引入故障率递增因子和役龄回退因子，采用故障性维修、预防性维修、多梯度机会维修和预防性更换相结合的维护方式，得出总成本最低的最佳预防性维修周期和维修次数。以某城市轨道列车检修为例进行实例仿真表明，相比单部件顺序维修策略，所提基于可靠性的多梯度机会维修策略可有效减少停车次数、节省维护费用、提高运营效率，从而为城市轨道列车的预防性维修提供科学依据和理论参考。     

基于仿真的多部件设备机会维修多目标决策优化方法

提出一种基于仿真的多部件设备机会维修多目标决策优化方法，考虑了多种维修方式、多种机会维修策略、非预期故障的随机持续时长和成本以及随机的预防性维修时长，利用蒙特卡洛仿真计算系统可用度和总成本，多目标粒子群算法进行求解最佳维修方式。将该方法应用到电子组装线的某生产设备，结果显示，同时考虑了随机故障和预防性维修的机会维修策略具有更优的Pareto前沿，能够进一步优化系统可用度与系统总成本，并对可用度和总成本的随机分布进行了分析。     

Joint optimization of spare parts inventory and maintenance policies using genetic algorithms

In general, the maintenance and spare parts inventory policies are treated either separately or sequentially in industry. However, since the stock level of spare parts is often dependent on the maintenance policies, it is a better practice to deal with these problems simultaneously. In this study, a simulation optimization approach using genetic algorithms (GAs) has been proposed for the joint optimization of preventive maintenance (PM) and spare provisioning policies of a manufacturing system operating in the automotive sector. A factorial experiment was carried out to identify the best values for the GA parameters, including the probabilities of crossover and mutation, the population size, and the number of generations. The computational experiments showed that the parameter settings given by the proposed approach achieves a significant cost reduction while increasing the throughput of the manufacturing system.     

An efficient architecture for scheduling flexible job-shop with machine availability constraints

This paper investigates flexible job-shop problem (FJSP) with preventive maintenance activities. Makespan is considered as an optimal criterion for this problem. The contribution of this study could be divided into two parts: (1) since the preventive maintenance policies are not pondered in most prior FJSPs, we apply an enforceable and easily extendable preventive maintenance policy on FJSP; (2) in order to figure the problem out, an effective learnable genetic architecture, LEGA, which is established in previous articles for FJSPs, is expanded to integrated FJSP and preventive maintenance which is named preventive maintenance and LEGA. All operators and parameters are then calibrated by means of the Taguchi experimental design. For the evaluation of the proposed architecture, a benchmark with conscientious care is employed.     

[轨道交通运维技术]风险视角下的动车组部件多级非完美维修策略

为了降低动车组部件在一个寿命周期内的维修总成本,以动车组五级修程时需要更换的部件为研究对象,基于现行的分级检修制度,提出一种动车组部件多级非完美预防性维修策略。以故障对动车组运行安全和对动车组晚点的影响以及故障维修难易程度作为故障风险的评价指标,使用层次分析法和评分法量化评价部件的故障风险。将动车组部件非完美维修方式划分为初级维修、中级维修和高级维修三个级别,克服了以往模型中非完美维修方式单一、忽视实际维修中普遍采用多级非完美维修方式的不足。算例仿真结果表明,提出的维修策略可使动车组部件在一个寿命周期内保持更高的可靠度水平且总成本也有所减少。     

基于状态的单部件维修策略优化方法

为降低装备中关键单部件的预防性维修费用,把部件劣化过程看成离散状态变换的过程,提出了部件从投入使用开始到发生一次故障进行修复的平均时间间隔、平均检查次数、平均预防性维修次数和平均维修总费用的计算表达式.以单位时间内平均总维修费用最小化为目标,建立了基于状态的预防性维修策略优化模型及其求解方法.实验结果表明,本方法可以快速确定部件的检查时间间隔和预防性维修状态,有效地降低单位时间内平均总维修费用.     

电动车组系统部件预防性维修可靠度的研究

针对电动车组系统部件的预防性维修,引入役龄回退因子的概念,建立预防性维修前后故障率的递推关系,对预防性维修后的可靠度进行了预估,为电动车组的修程优化提供了改进方向.     

Scheduling sequence-dependent setup time job shops with preventive maintenance

Although many researchers have proposed different techniques to integrate production scheduling and preventive maintenance, these techniques have some drawbacks. For example, some of them are so intricate that one cannot easily implement them, or some strongly exploit specific features of the original studied problem that one cannot apply them to other problems. We hereby propose two techniques that are easy to understand and code, yet simplistically adaptable to any other machine-scheduling problems. This paper investigates job shop scheduling with sequence-dependent setup times and preventive maintenance policies. The optimization criterion is to minimize makespan. Four metaheuristics based on simulated annealing and genetic algorithms as well as adaptations of two metaheuristics in the literature are employed to solve the problem. The performances of the proposed algorithms are evaluated by comparing their solutions through two benchmarks based on Taillard’s instances.     

Performance Analysis of an FMS Operating Under Different Failure Rates and Maintenance Policies

Flexible manufacturing Systems (FMSs) typically operate at 70–80% utilization, which is much higher than the utilization of traditional machines that can operate with as low as 20% utilization. A result is that an FMS may incur four times more wear and tear than a traditional system. This requests the execution of effective maintenance plans on FMSs. While maintenance actions can reduce the effects of breakdowns due to wear-outs, random failures are still unavoidable. It is important to understand the implications of a given maintenance plan on an FMS before its implementation. This paper discusses a procedure that combines simulation and analytical models to analyze the effects of corrective, preventive, and opportunistic maintenance policies on the performance of an FMS. The FMS performance is measured by its operational availability index, which is determined using the production output rate of the FMS under a variety of time between failure distributions and different operational conditions. The effects of various maintenance policies on FMS performance are simulated and the results are compared to determine the best policy for a given system.     

基于性能测试的电主轴预防性维修方法研究

针对电主轴预防性维修问题,首先通过电主轴结构分析和常见故障分析,获得电主轴故障多发部位和故障原因;然后针对分析得到的电主轴故障多发部位,设计电主轴预防性维修体系,通过设计故障多发部位性能测试方案和评价标准,得到电主轴预防性维修方法;最后将设计的预防性维修方法应用于长期服役的精密数控机床电主轴,验证了所提电主轴预防性维修方法的有效性。实验结果表明:所提电主轴预防性维修方法可有效识别出电主轴早期性能退化,为预防性维修和性能退化趋势监测提供了有效依据。     

PGA算法优化的航空装备预防性维修综合决策研究

考虑预防性维修次数和周期对航空装备故障率的影响,将役龄回退因子和故障率递增因子引入到故障率函数中,以有限时间内装备的维修费用最小和平均可靠度最大为优化目标,建立了一种变周期预防性维修综合决策模型。采用改进的Pareto遗传算法(Pareto Genetic Algorithm,PGA)对模型进行优化求解。以某型航空发动机为例对模型进行了验证,得到了10组Pareto最优集,确定了最佳的预防性维修次数及周期。仿真结果表明该模型在保证有效可靠度的基础上大大减少了维修费用。