现代企业设备管理信息化的技术与方法（八）

3.合理维修周期分析一个实用可行的维修周期分析方法,是最小费用周期法。在系统中,将定期维修、故障维修及其他维修分别进行维修费用与维修间隔时间的统计分析,在一个分析期内,一个级别的维修(大修、中修、小修)至少需要五次以上的记录。其分析的数据采集模型如图11。假定A为定期维修(小修),共发生了七次;B为故障维修及其他维修,共进行了三次,设备运行总时间TH=1800小时,定期维修周期T1=200小时,则计划维修平均费用F=3700/7=529元平均故障维修费用GF=2650/3=883元假定在发生故障前进行维修,可节省维修费用F1=(883-529)×3=1062元,则合理…     

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.     

基于可靠性的设备全寿命周期维修时刻决策建模研究

基于可靠性理论,研究了设备维修决策量化分析方法。阐述了预知性维修时刻对其设备安全性和经济性的影响,然后运用可靠性理论建立了以设备全寿命周期内单位时间维修费用支出最小为原则的最佳维修时刻优化模型。通过实例验证了该模型的正确性和实用性,可有效适用于设备最佳维修时刻的确定。     

试论设备维修的经济技术和综合计划管理

多年来,许多工厂设备维修推行修理周期结构和修理复杂系数为主要依据的计划预修制度,由于经济性较差,已被越来越多的单位所修正。有的单位逐步演变到按需修理,有的单位甚至回到事后修理,修理体制极其混乱。另一方面,设备大修费用全由企业负担,而设备中修(或项修)和日常维护费用又都打入车间成本,因此,车间就争报大修,不报中修,避免小修,致使有的设备修理过剩,而许多该修的设备却得不到修理,形成了一种畸形的设备维修计划。     

工业设备预防性维修策略及其效果评估

采用随机变量评估工业设备预防性维修的效果,以单位时间平均维修费用最低为目标,并假定评估预防性维修效果的参数服从均匀分布,构建维修策略的优化模型并进行数值仿真.仿真结果表明,采用随机参数的预防性维修模型能有效降低故障率增长趋势,减少单位时间平均维修费用,具有更好的优化结果,可以为维修计划的制定和现场的作业调度提供决策支持.     

租赁设备的检修及租金的收取

租赁是一种集约化的设备管理模式,可以提高设备的利用率,充分发挥设备的投资效益.租赁设备的检修工作是租赁工作中的一个重要环节,抓好这一环节是延长设备使用寿命的关键.租赁设备租金的收取原则则是促进租赁工作进一步发展的重要因素之一.一、检修煤炭行业租赁对象大部分为采、掘、运等可移动设备,租赁设备中、小修和日常维修一般由使用单位负责,大修由租赁站负责.1.中、小修和日常维护:应做到天天有维护,周周有维修,月月有小修,季季有中修.设备在使用过程中,因故障或部件损坏影响正常运转,而大修又未到时,应由租用单位负责进行中修,费用自理;设备租赁期满,交还租赁站时,设备必须完好.验收不合格需进行中修的费用由租用单位负责.2.大修:租赁站统一安排大修计划,委托和签订大修合同.大修费根据设备完好或损坏状况由租赁站商承修单位按规定提收.租赁站对委托大修的设备要进行中检和监督修理进度并组织验收,合格后,办理结算及交接手续.设备大修完毕后,应设定保修期并预留20%大修理费,保修期内出现修理质量问题,由承修单位免费修理,未出现质量问题,大修理预留费应按期付给承修单位.在设备租用期间(不含保修期)出现带病运转或因事故停产等情况,租用单位可向租赁站申请租用替换设备或部件,租赁站要根据情     

基于寿命预测的预防性维护维修策略

针对退化分布函数难以估计的复杂系统,研究了剩余寿命预测及预防性维护维修最优决策问题,提出一种基于复杂系统剩余寿命有效预测的预防性维护维修策略。在系统退化状态分布函数未知的条件下,由已知的设备寿命分布函数预测其平均剩余寿命,以平均剩余寿命为阈值制定预防性维护维修策略。根据更新过程理论,建立了以系统的预测间隔、预防性维护阈值为优化变量和最小化平均维护维修费用为目标函数的优化模型。采用微粒群算法进行优化求解,得到系统最佳的预测周期和维护维修阈值,并使系统长期运行的平均费用率最低。分别以在翼寿命符合威布尔分布的民航发动机和寿命分布符合正态分布的航海设备电控罗经中的某型变压器为例,验证了所提维护维修策略的可行性。     

考虑非完美维修的实时剩余寿命预测及维修决策模型

准确的剩余寿命预测是对设备进行预防性维护维修决策的关键。利用随机滤波理论,基于当前时刻及之前的历史状态监测信息,由已知的设备初始寿命分布函数建立非完美维修策略下的实时剩余寿命分布函数预测模型。同时考虑非完美维修效果与时间相关性,提出一种以平均剩余寿命为阈值的非完美预防性维护及更换的维修策略,建立了以系统的预防性维护及预防性更换阈值为优化变量和最小化平均维护维修费用为目标函数的优化模型。采用微粒群算法进行优化求解,得到系统最佳的预防性维护及预防性更换阈值,并使系统长期运行平均费用率最低。以初始寿命符合威布尔分布的疲劳裂纹为例,验证了该实时剩余寿命分布预测方法及非完美维护维修策略的可行性。     

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。     

基于改善因子的系统部件维修间隔优化方法

针对民用飞机系统部件维修间隔优化问题进行研究。为了描述维修活动对系统的影响,引入改善因子描述维修活动对工龄的恢复效应,在不完全维修模型的基础上,构建了以单位时间总维修成本最小为目标函数的周期性不完全预防维修优化模型,得到了不完全维修条件下最佳预防维修时间间隔和最佳维修次数。最后,采用航空公司的实例进行验证,表明模型是可行的。     

Optimal inspection policy for three-state systems monitored by variable sample size control charts

This paper presents the expected long-run cost per unit time for a system monitored by an adaptive control chart with variable sample sizes: if the control chart signals that the system is out of control, the sampling which follows will be conducted with a larger sample size. The system is supposed to have three states: in-control, out-of-control, and failed. Two levels of repair are applied to maintain the system. A minor repair will be conducted if an assignable cause is confirmed by an inspection, and a major repair will be performed if the system fails. Both the minor and major repairs are assumed to be perfect. We derive the expected long-run cost per unit time, which can be used to obtain the optimal inspection policy. Numerical examples are conducted to validate the derived cost.     

基于半马尔可夫过程的冷备系统维护策略优化

为了提高系统的可靠性，构建了两机冷备系统，提出了基于半马尔可夫过程的冷备系统预防性维护模型，该模型考虑随机失效、退化失效两种失效形式，采用了小修、大修、预防性维护相结合的维护方式。基于半马尔可夫理论及再生点技术分析了系统运行中的状态变化过程，建立了马尔可夫更新方程组。通过拉普拉斯变换求得系统首次平均失效时间和稳态可用度的函数表达式，并分别以系统首次平均失效时间和稳态可用度为可靠性指标求解最佳预防性维护策略。最后通过实例分析了不同参数变化对系统可靠性及最佳预防性维护周期的影响。实验结果表明，所提出的建模方法对解决冷备系统维护决策具有指导意义。     

用遗传算法优化制造设备的预防性维修周期模型

建立了预防性维修周期间故障的递推关系式，给出了有限时间区间的设备预防性维修策略的非线性优化模型。该模型综合考虑了维修成本、预防性维修成本和生产损失成本，克服了无限时间区间稳态分析操作性差的缺点，并以故障分布形式为威布尔分布的设备为例，用遗传算法进行优化。计算结果显示，遗传算法能以极快的收敛速度达到全局最优，具有较高的计算效率。模型可为维修计划的制定和现场的作业调度提供决策支持和信息支持。     

Joint optimization of lot-sizing and maintenance policy for a partially observable two-unit system

In this paper, we present a new model to find the jointly optimal economic manufacturing quantity (EMQ) and preventive maintenance (PM) policy for a complex production facility. Unlike the previous joint models which dealt with EMQ and maintenance policy considering a single unit production facility and traditional maintenance approaches, we consider a production facility which consists of two modules with economic dependence. The more expensive module (unit 1) is subject to condition monitoring (CM), and only the age information of the second module (unit 2) is available, which follows a general distribution. The deterioration process of unit 1 is modeled as a continuous time hidden-Markov process. CM data is available at the end of each production run, and it provides only partial information about the hidden state of unit 1. The failure state of unit 1 is observable at any time. The objective is to develop a jointly optimal lot sizing and maintenance policy for a two-unit production facility using multivariate Bayesian control approach by minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Also, a formula for the mean residual life (MRL) of the production facility is derived, which is an important statistic for practical applications. A practical example of the wind turbine CM and maintenance is provided and a comparison with other policies shows an outstanding performance of the new model and the control policy proposed in this paper.     

Optimisation of opportunistic maintenance of a multi-component system considering the effect of failures on quality and production schedule: A case study

For a manufacturing equipment, any unplanned breakdown during the production period results into a high production loss. To keep the manufacturing facilities in good condition, preventive maintenance is planned. However, because of limited time and availability of resources, not all the system components can be or need to be repaired/replaced during a planned opportunity. Hence, the unplanned breakdowns can also be considered as an opportunity to do the maintenance activities for other components to take the advantage of economic dependency in multi-component system. However, when the system is under maintenance, it is very conservative to take the decision of maintenance actions on the components because of limited available time and resources. For such situation, this paper consider an opportunistic maintenance model for a multi-component system to take maintenance decision with a constraint on available time and the system availability requirements. The maintenance decisions for each component involves one of the three actions namely, repair, replace or do nothing to achieve the target availability with minimum maintenance cost. The model also considers the effect of component failures on the quality of product being manufactured as well as the production schedule on the machine. The cost of rejections is considered in the total failure cost along with the maintenance and downtime costs. The production schedule delay factor is considered as a constraint for the maintenance decision to account for the effect on production schedule delay. The optimal solution for the model is obtained using three solution methodologies namely simulated annealing, genetic algorithm and sequence heuristics. Using a real-life example of high pressure die casting machine, the opportunistic maintenance approach is demonstrated and results are discussed.     

Planning performance based contracts of repairable system using discrete event simulation

This paper investigates a discrete event simulation approach for managing performance based contracts of repairable systems. We focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose a simulation model to calculate system availability comprehending four performance drivers: life time distribution, repair time distribution, spare parts inventory, and repair facility. This simulation model allows the service supplier to minimize the total cost by optimizing the four performance drivers. In this simulation model, the failure time and repair time can follow arbitrary distribution. This will allow the customer to monitor the supplier’s service through comparing the actual availability and its theoretical value. The costs of three maintenance policies also can be studied under the performance based contracts framework. Two cases are considered in this paper. One is a system containing single unit, one warehouse, and one repair center. Another is a system containing two fleets with different installed units, two spare part warehouses with one for each fleet, and a central repair depot.     

Reliability-based maintenance optimization under imperfect predictive maintenance

The reliability-based maintenance optimization model has been focused by the engineers and scholars but it has never been solved effectively to formulate the effect of a maintenance action on the optimization model.In existing works,the system reliability was assumed to be increased to 1 after a predictive maintenance.However,it is very difficult in the most practical systems.Therefore,a new reliability-based maintenance optimization model under imperfect predictive maintenance (PM) is proposed in this paper.In the model,the system reliability is only restored to Ri (0相似文献   

一种安装及拆卸螺塞环扳手研制

介绍了通过实际修理气动工具而得出的一种新型拆装工具的研制,其是为恢复故障气动工具的使用功能而进行的一项拆卸技术设计,通过使用该种新型拆装螺塞环扳手作为修理故障气动工具,不仅提高了修理效率,延长了气动工具的使用寿命,而且还大大降低了修理难度及修理成本,为企业生产设备的修理提供了最有效的维修保障。     

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。