Optimal preventive maintenance policy for electric power distribution systems based on the fuzzy AHP methods

In power distribution systems, with their great vastness and various outage causes, one of the most important problems of power distribution companies is to select a suitable maintenance strategy of system elements and method of financial planning for the maintenance of system elements with the two objectives of decrease in outage costs and improvement of system reliability. In this article, a practical method is introduced for the selection of a suitable system elements maintenance strategy; moreover, to plan the preventive maintenance budget for the system elements, two methods are offered: the cost optimization method and the fuzzy Analytic Hierarchy Process (AHP) method. In the former method, a new model of system maintenance cost is offered. This model, based on system outage information, the elements maintenance costs are determined as functions of system reliability indices and preventive maintenance budget. The latter method, too, a new guideline is introduced for considering the cost and reliability criteria in the trend of preventive maintenance budget planning. In this method, the preventive maintenance budget for the elements is determined based on relative priority of elements with reliability criteria. © 2015 Wiley Periodicals, Inc. Complexity 21: 70–88, 2016     

Joint production and preventive maintenance scheduling for a single degraded machine by considering machine failures

Production scheduling and maintenance planning are two interdependent issues that most often have been investigated independently. Although both preventive maintenance (PM) and minimal repair affect availability and failure rate of a machine, only a few researchers have considered this interdependency in the literature. Furthermore, most of the existing joint production and preventive maintenance scheduling methods assume that machine is available during the planning horizon and consider only a possible level for PM. In this research, an integrated model is proposed that coordinates preventive maintenance planning with single-machine scheduling to minimize the weighted completion time of jobs and maintenance cost, simultaneously. This paper not only considers multiple PM levels with different costs, times and reductions in the hazard rate of the machine, but also assumes that a machine failure may occur at any time. To illustrate the effectiveness of the suggested method, it is compared to two situations of no PM and a single PM level. Eventually, to tackle the suggested problem, multi-objective particle swarm optimization and non-dominated sorting genetic algorithm (NSGA-II) are employed and their parameters are tuned Furthermore, their performances are compared in terms of three metrics criteria.     

带有多重休假及预防维修的冲击模型二维更换策略

研究了修理工带有多重休假且定期检测的累积冲击模型.为了延长系统的运行时间,在检测时考虑了预防维修.将事后维修和预防维修结合起来运用于可修系统,且假定预防维修能够"修复如新",而事后维修为"修复非新".以系统的检测周期和故障次数为二维决策变量,选取系统经长期运行单位时间内期望费用为目标函数.并通过数值分析,求出了最优策略.     

Age-dependent production planning and maintenance strategies in unreliable manufacturing systems with lost sale

In this paper, we formulate an analytical model for the joint determination of an optimal age-dependent buffer inventory and preventive maintenance policy in a production environment that is subject to random machine breakdowns. Traditional preventive maintenance policies, such as age and periodic replacements, are usually studied based on simplified and non-realistic assumptions, as well as on the expected costs criterion. Finished goods inventories and the age-dependent likelihood of machine breakdowns are usually not considered. As a result, these policies could significantly extend beyond the anticipated financial incomes of the system, and lead to crises. In order to solve this problem, a more realistic analysis model is proposed in this paper to consider the effects of both preventive maintenance policies and machine age on optimal safety stock levels. Hence, a unified framework is developed, allowing production and preventive maintenance to be jointly considered. We use an age-dependent optimization model based on the minimization of an overall cost function, including inventory holdings, lost sales, preventive and corrective maintenance costs. We provide optimality conditions for the manufacturing systems considered, and use numerical methods to obtain an optimal preventive maintenance policy and the relevant age-dependent threshold level production policy. In this work, this policy is called the multiple threshold levels hedging point policy. We include numerical examples and sensitivity analyses to illustrate the importance and the effectiveness of the proposed methodology. Compared with other available optimal production and maintenance policies, the numerical solution obtained shows that the proposed age-dependent optimal production and maintenance policies significantly reduce the overall cost incurred.     

考虑不完全检测的冲击模型最优维修策略

针对制造系统中设备检测不完全的情形,研究基于不完全检测的冲击模型的周期检测、维修联合策略．通过定期检测获知系统的劣化状态以进行必要的预防性维修．在假设系统是退化的且有k个不同故障状态的条件下,以最小化系统运行成本为目标,以检测周期T、系统更换前故障次数Ⅳ为联合决策变量,利用更新过程理论建立了系统平均费用率C（T,N）的数学模型,并且给出最优联合策略的数值算法．最后借助数值例子演示了该模型,分析了检测水平对系统运行成本的影响．     

A preventive maintenance policy for a continuously monitored system with correlated wear indicators

A continuously monitored system is considered, that gradually and stochastically deteriorates according to a bivariate non-decreasing Lévy process. The system is considered as failed as soon as its bivariate deterioration level enters a failure zone, assumed to be an upper set. A preventive maintenance policy is proposed, which involves a delayed replacement, triggered by the reaching of some preventive zone for the system deterioration level. The preventive maintenance policy is assessed through a cost function on an infinite horizon time. The cost function is provided in full form, and tools are provided for its numerical computation. The influence of different parameters on the cost function is studied, both from a theoretical and/or numerical point of view.     

Reliability Analysis of a One-Unit System with Unrepairable Spare Units and its Optimization Applications

It is assumed that a unit is either in operation or is in repair. When the main unit is under repair, spare units which cannot be repaired are used. In this system the following quantities are of interest: (i) The time distribution and the mean time to first-system failure, given that the n spare units are provided at time 0. (ii) The probability that the number of the failed spare units are equal to exactly n during the interval (0, t], and its expected number during the interval (0, t]. These quantities are derived by solving the renewal-type equations.Two optimization problems are discussed using the results obtained, viz.: (i) The expected cost of two systems, one with both a main unit and spare units and the other with only spare units is considered. (ii) A preventive maintenance policy of the main unit is considered in order to minimize the expected cost rate. Some policies of the two problems are discussed under suitable conditions. Numerical examples are also presented.     

Optimization of a fully adaptive quality and maintenance model in the presence of multiple location and scale quality shifts

This paper presents a new model for the economic-statistical optimization of a Variable-Parameter Shewhart control scheme. The proposed model can be utilized to monitor processes where apart from multiple independent assignable causes, affecting both the mean and variance, failures can also occur. Each time an alarm is issued by the control scheme, preventive maintenance actions are initiated, whereas, corrective maintenance actions are required after a failure. The more realistic assumption of imperfect preventive maintenance actions has been considered. The optimal parameter values are selected through a bi-objective optimization problem formulated by the long-run average cost per time unit minimization, and the long-run expected availability maximization, subject to statistical constraints. A real case example is presented to illustrate the application of the model. An extended numerical investigation is utilized to evaluate the superiority of the proposed model.     

Tramcar Maintenance

This article describes the work done to determine age limits for preventive replacements and overhauls in tramcar maintenance, where opportunities are provided by a failed component or an essential overhaul. A brief review of existing literature is also presented and two pair-wise suboptimal preventive replacement policies are considered. These policies are applicable to any "n" component system with subassemblies, where the cost of dismantling and assembling the various sub-units is of the same order as the cost of new parts. The results of a search to find more economical control limits are also presented.     

Towards An Intelligent Maintenance Optimization System

This paper is concerned with the evaluation and enhancement of the maintenance routines of large and complex technical systems. An ‘intelligent decision support system’ approach is suggested as a method for overcoming the difficulties associated with the scale, variability and changeability of such systems. The main features of the proposed intelligent maintenance optimization system (IMOS) are identified. A prototype system is then presented and its main mathematical models of maintenance are introduced. Some sample test data and the results produced from them are presented. Other aspects discussed include dealing with censored data, optimization criteria, the development of a maintenance model selection rule base, the recognition of data patterns and models' robustness. Results of IMOS system validation against expert advice have shown a high measure of consistency.     

Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system

This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.     

A novel optimal preventive maintenance policy for a cold standby system based on semi-Markov theory

A novel optimal preventive maintenance policy for a cold standby system consisting of two components and a repairman is described herein. The repairman is to be responsible for repairing either failed component and maintaining the working components under certain guidelines. To model the operational process of the system, some reasonable assumptions are made and all times involved in the assumptions are considered to be arbitrary and independent. Under these assumptions, all system states and transition probabilities between them are analyzed based on a semi-Markov theory and a regenerative point technique. Markov renewal equations are constructed with the convolution of the cumulative distribution function of system time in each state and corresponding transition probability. By using the Laplace transform to solve these equations, the mean time from the initial state to system failure is derived. The optimal preventive maintenance policy that will provide the optimal preventive maintenance cycle is identified by maximizing the mean time from the initial state to system failure, and is determined in the form of a theorem. Finally, a numerical example and simulation experiments are shown which validated the effectiveness of the policy.     

Optimal replacement and allocation of multi‐state elements in k‐within‐m‐from‐r/n sliding window systems

This paper proposes a new model that generalizes the linear sliding window system to the case of multiple failures. The considered k ‐within‐ m ‐from‐ r / n sliding window system consists of n linearly ordered multi‐state elements and fails if at least k groups out of m consecutive groups of r consecutive multi‐state elements have cumulative performance lower than the demand W . A reliability evaluation algorithm is suggested for the proposed system. In order to increase the system availability, maintenance actions can be performed, and the elements can be optimally allocated. A joint element allocation and maintenance optimization model is formulated with the objective of minimizing the total maintenance cost subjected to the pre‐specified system availability requirement. Basic procedures of genetic algorithms are adapted to solve the optimization problem. Numerical experiments are presented to illustrate the applications. Copyright © 2015 John Wiley & Sons, Ltd.     

Optimization of maintenance policy under warranty length‐based demand with consideration of both manufacturer and buyer satisfaction

This study proposes a model to optimize postsale services consisting of four factors: (a) the basic warranty length, (b) the extended warranty length, (c) the preventive maintenance level, and (d) the preventive maintenance interval. Furthermore, consumer demand for the product and extended warranty are considered as functions of the length of the basic warranty and extended warranty periods, respectively. Because buyer dissatisfaction with a product can lead to the loss of potential buyers and the switch of current customers to the competitors, both manufacturer and buyer satisfaction are considered in the model. Three comparative studies are done for showing the effectiveness of the model. The first one compares the results of simultaneous optimization from the two perspectives of manufacture and customer with the single‐objective optimization results from each of the mentioned viewpoints. The second comparison studies the provision of extended warranty contract in the proposed model, and the third comparison investigates the effect of preventive maintenance actions on the results of the model.     

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。     

A novel replacement policy for a linear deteriorating system using stochastic process with dependent components

In this study, a mechanical system with linear deterioration and preventive maintenance is considered. The state of the system over time is represented by a semicontinuous stochastic process with dependent components. The system cycles through on and off periods during its lifetime. The state of the system deteriorates linearly as a function of the usage time during on periods. When the system is offline, preventive maintenance is conducted, which improves the system state by a random amount. The system's on and off times and random improvement amounts are assumed to have general distributions. For such a system, our objective is to determine the expected value and variance for the number of preventive maintenance activities needed during the system lifetime and to propose a novel replacement policy for the system based on delay‐time modeling. Finally, the effectiveness of the obtained asymptotic results and the proposed replacement policy are tested through simulation.     

A preventive maintenance policy with sequential checking procedure for a Markov deteriorating system

We consider a repairable system subject to a continuous-time Markovian deterioration while running, that leads to failure. The deterioration degree is measured with a finite discrete scale; repairs follow general distributions; failures are instantaneously detected. This system is submitted to a preventive maintenance policy, with a sequential checking procedure: the up-states are divided into two parts, the “good” up-states and the “degraded” up-states. Instantaneous (and perfect) inspections are then performed on the running system: when it is found in a degraded up-state, it is stopped to be maintained (for a random duration that depends on the degradation degree of the system); when it is found in a good up-state, it is left as it is. The next inspection epoch is then chosen randomly and depends on the degradation degree of the system by time of inspection. We compute the long-run availability of the maintained system and give sufficient conditions for the preventive maintenance policy to improve the long-run availability. We study the optimization of the long-run availability with respect to the distributions of the inter-inspection intervals: we show that under specific assumptions (often checked), optimal distributions are non-random. Numerical examples are studied.     

System availability in a shock model under preventive repair and phase‐type distributions

A device that can fail by shocks or ageing under policy N of maintenance is presented. The interarrival times between shocks follow phase‐type distributions depending on the number of cumulated shocks. The successive shocks deteriorate the system, and some of them can be fatal. After a prefixed number k of nonfatal shocks, the device is preventively repaired. After a fatal shock the device is correctively repaired. Repairs are as good as new, and follow phase‐type distributions. The system is governed by a Markov process whose infinitesimal generator, stationary probability vector, and availability are calculated, obtaining well‐structured expressions due to the use of phase‐type distributions. The availability is optimized in terms of the number k of preventive repairs. Copyright © 2009 John Wiley & Sons, Ltd.