旧设备租赁的周期预防维护策略优化

针对具有一定年龄的旧设备租赁的特殊性,提出周期预防维护策略。该策略综合考虑设备的年龄、预防维护、小修以及惩罚机制等多种因素对成本的影响,建立以出租方维护成本最小化为目标的周期预防维护模型。经算例分析,研究表明,该方法是有效的,并且在实际维护过程中是易于操作的。     

考虑维修时间和惩罚的租赁设备维护策略研究

针对租赁设备维修时间的不确定性,建立考虑维修时间随机性的等周期预防性维护策略。该策略在考虑租赁设备维修时间随机性的同时,综合考虑对出租方的维修惩罚,包括维修时间惩罚、故障总次数惩罚以及可用度惩罚等因素对总成本的影响。从出租方的角度出发,建立以出租方总成本最小为目标的预防性维护策略优化模型。用MATLAB仿真求解出模型的最优预防性维护计划。算例分析表明,考虑租赁设备维修时间随机性和维修惩罚使租赁设备的维护更符合实际情况,能为租赁企业提供有效的设备维护策略。     

基于故障状态演化的租赁设备定周期多维护策略研究

为同时保证设备承租方对租赁设备的可用度,以及优化设备出租方的设备维护成本,提出了基于故障状态的定周期检测的多维护方式策略。首先,对租赁设备进行定周期检测,基于设备故障率来选择相应的维护策略,采取役龄回退的方式描述采取不同的维护策略后设备状态的恢复情况。其次,综合考虑周期维护成本、小修成本、惩罚成本和租赁延迟成本,建立了以出租方成本最低为目标的多维护策略优化模型。通过数学建模和数理统计方法,利用MATLAB仿真进行算例分析,将其与定周期单一预防性维护策略进行对比,证明了对租赁设备进行定周期多策略维护,其维护效果较单一预防性维护有较大的提升。     

EPON环境下相关设备的维护工作分析

文章针对EPON技术本身的特征,以及其网络结构主要成分和功能做出了必要说明,而后基于此就其体系中设备如何展开有效维护的问题展开了逐步深入的讨论,对于切实打造强健的EPON网络工作体系有着一定的积极价值。     

考虑租赁延迟的设备预防维护策略优化研究

根据租赁设备的维护实际情况,给出了租赁延迟的定义,提出一种更接近设备运行真实情况的周期预防维护策略模型。该策略综合考虑设备的休眠期、预防维护和小修等因素对维护费用的影响,从出租方角度出发,建立以维护总费用最小化为目标的周期预防维护模型,并给出模型取得最优策略的相关理论证明和最优值的求解算法。最后是算例分析,研究表明,该策略符合租赁设备维护的实际情况,可为租赁企业提供有效的设备维护解决方案。     

谈光传输设备故障分析与维护

随着电信业传输网络的不断发展和壮大,光传输设备已经广泛的应用在电信行业的网络传输中。因此,如何有效地做好光通信设备的日常维护工作,确保其安全稳定地运行,是非常重要的。本文介绍了传输光网络的情况,分析了光传输设备故障及主要排除技术方法,最后提出光传输设备维护注意事项。     

光纤传输设备维护探讨

本文结合实际工程状况,对光纤传输设备中的常见故障以及具体定位问题进行分析,有针对性地提出维修与维护对策,以实现光纤传输设各安全、稳定地运行。     

光传输设备故障类型与维护措施

光传输设备,其具有频带宽、损耗低、不受电磁波干扰、图像质量稳定等优点,加之设备与材料的成本较低,从而被广泛应用于各种数据、信号的传输服务行业领域,因此对光传输设备的维护工作就显得更为重要,就光传输设备的故障类型与维护措施进行简要的分析、探讨。     

浅析给水设备的维护管理

随着我国经济的快速发展以及城市化进程不断加快,尤其是随着高层建筑的不断增多,在高层建筑中,给水设备对人们日常生活的影响越来越显著。这直接导致人们开始重视给水设备的质量。     

简析巴可数字电影放映设备维护及常见故障处理

电影放映设备的正常运行在电影放映过程中尤为重要.为保证电影顺利放映,提升观众的观影体验,避免设备故障影响观影效果,从而影响影院口碑,造成影院经济损失.本文通过对巴可数字电影放映设备日常使用中的设备维护及常见故障的处理方法进行简单阐述,旨在减少电影设备故障的出现,同时能更快地处理一些设备的紧急故障,以更好、更快地恢复电影...     

Investigating reliability improvement of second-hand production equipment considering warranty and preventive maintenance strategies

A cost model for optimal reliability improvement of warranted second-hand production equipment is developed. The second-hand production equipment of age x is subjected to an upgrade action of a certain level u before it is sold with a Free Repair Warranty. We look at determining the optimal upgrade level when not performing and when performing periodic preventive maintenance (PM) during the warranty period. Two different PM strategies are considered: (a) periodic PM actions having the same efficiency level; (b) periodic multi-phase PM actions with a maintenance efficiency level which varies according to the phase. The proposed model aims at helping the dealer to find the optimal upgrade level to perform before selling the second-hand equipment, and to assess whether performing PM actions during the warranty period, according to a specific maintenance strategy, is worthwhile in terms of cost reduction. Numerical experimentations considering each PM scenario are performed in order to investigate how each PM strategy impacts the improvement level to be performed and the associated total expected cost. The obtained results showed that the expected total cost incurred by the dealer is governed by a sensitive trade-off between the warranty servicing cost and the costs associated with the reliability improvement, and with the PM performed during the warranty period. It is also found that the proposed new periodic multi-phase PM policy with an increasing maintenance efficiency level yields lower upgrade levels, inducing lower costs for the dealer.     

Multi-phase preventive maintenance policy for leased equipment

This paper proposes a multi-phase preventive maintenance (PM) policy for leased equipment by combining the advantages of both periodic PM and sequential PM. The lease period of the equipment is divided into multiple PM phases. The PM activities within each phase are performed periodically with the convenience of implementation, while the frequency of PM for each phase is different and it gives a gradual increase because of the imperfect effect of PM. A multi-phase PM model is built up based on the age reduction method for imperfect PM with the penalty for equipment failures and overtime of repair involved. The optimal PM intervals for every PM phases are achieved by minimising the cumulative maintenance cost throughout the lease period from the perspective of the lessor. Numerical example shows that the cumulative maintenance cost under the proposed multi-phase PM policy is lower than that under periodic PM policy.     

Improving overall equipment cost loss adding cost of quality

This research has the objective of improving indicators for evaluating losses of equipment. It also proposes a newly developed computing methodology for estimating the quantitative losses in monetary unit. The presented methodology is to calculate losses following overall equipment effectiveness (OEE) consisting of opportunity and production cost losses and also from cost of quality (COQ) approaches. This method eliminates some of OEE's weaknesses and expands scope from overall equipment cost loss (OECL). The proposed calculating methodology is demonstrated by applying to a real manufacturer of equipment. This newly improved model can prioritise problematic equipment more appropriately than OEE and OECL.     

Research on Selection of Equipment Maintenance Modes

1 IntroductionEquipment failure will inevitably occur during a normal production process.Severe equipment failurewill conduce long time deadlock of a production system,lower production efficiency,and add extracost on products.Effective strategy should be adopted so as to reduce failure influence on equipment,reduce production cost and enhance market competition of products.In recent years,high-tech pro-duction equipment are improved,and production rates are more rapid.For the sake of maintain…     

Maintenance Strategies and Failure‐Cost Model for Medical Equipment

This paper proposes a mathematical maintenance model that analyses the effect of maintenance on the survival probability of medical equipment based on maintenance history and age of the equipment. The proposed model is simulated in Scilab using real data extracted from maintenance history of anaesthesia machine from Draeger. The analysis using survival approach reveals that conducting preventive maintenance on the selected medical equipment had a positive impact on survival of equipment. The model is then used to analyse the cost of maintenance scenarios, and an appropriate scenario is proposed for anaesthesia machine. A new failure‐cost model is developed, which may be used to calculate the number of failures of equipment and the annual maintenance cost. The proposed models may be used as a planning tool for selecting maintenance strategies for various medical equipments. Copyright © 2014 John Wiley & Sons, Ltd.     

Optimal imperfect preventive maintenance policy for equipment leased during successive periods

In this paper, we consider randomly failing equipment leased several times during their life cycle with a given warranty period. A mathematical model is developed to determine the optimal efficiency levels of preventive maintenance (PM) to be performed on the equipment between successive lease periods, maximising the expected total profit of the lessor over the equipment life cycle. The model considers the expected leasing revenue as well as the equipment acquisition cost and the average PM and repair costs. PM actions allow reducing the age of the equipment to a certain extent with a corresponding cost depending on the PM level adopted. The efficiency of the PM is determinant of the expected revenue during the next lease period. Given a set of K possible PM levels and the number of lease periods n over the equipment life cycle, K^{n?1 PM} strategies are possible. A genetic algorithm is proposed in order to obtain nearly optimal policies in situations where the number of possibilities K^n?1 is very high. Obtained numerical results are discussed. Small- and big-size instances of the problem are considered in the case of a service company in the oil and gas industry specialised in leasing specific equipment such as separators, to oil companies for production activities with a limited duration of several months like well testing or short production tests.     

A methodology for simultaneous optimisation of design parameters for the preventive maintenance and quality policy incorporating Taguchi loss function

The performance of a production system depends on the breakdown-free operation of equipment and processes. Maintenance and quality control play an important role in achieving this goal. In addition to deteriorating with time, equipment may experience a quality shift (i.e. process moves to out-of-control state), which is characterised by a higher rejection rate and a higher tendency to fail. This paper develops an integrated model for joint optimisation of preventive maintenance interval and control parameters incorporating the Taguchi loss function. We consider two types of maintenance policies: minimal corrective maintenance that maintains the state of the equipment without affecting the age and imperfect preventive maintenance that upgrades the equipment in between ‘as good as new’ and ‘as bad as old’ condition. The proposed model enables the determination of the optimal value of each of the four decision variables, i.e. sample size (n), sample frequency (h), control limit coefficient (k), and preventive maintenance interval (t _PM) that minimises the expected total cost of the integration per unit time. A numerical example is presented to demonstrate the effect of the cost parameters on the joint economic design of preventive maintenance and process quality control policy. The sensitivity of the various parameters is also examined.     

On a new age-replacement policy for items with observed stochastic degradation

A new methodology for preventive maintenance of degrading items is discussed. It combines the classical age-replacement strategy when a system is replaced either on failure or on reaching the predetermined age, with replacement on reaching the predetermined level of deterioration at some intermediate time. Degradation of an item is modeled by the nonhomogeneous gamma process, whereas its failure occurs when this process reaches the predetermined deterministic level. It is shown that the proposed policy outperforms the classical one, i.e., it achieves the lower value of the corresponding long-run cost rate. The detailed numerical illustration is presented, and the relevant sensitivity analysis for the main parameters of the model is performed.