A condition-based maintenance policy for a production system under excessive environmental degradation

In this paper a condition-based maintenance model is proposed for a single-unit system of production of goods and services. The system is subject to random deterioration which impacts not only the product quality but also the environment. We assume that the environment degrades whenever a specific level of system deterioration is reached. The proposed maintenance model aims to assess the degradation in such a way to reduce the deterioration of the environment. To control this deterioration, inspections are performed and after which the system is preventively replaced or left as it is. Preventive replacement occurs whenever the level of the system degradation reaches a specific level threshold. The objective is to determine optimal inspection dates which minimize the average total cost per unit of time in the infinite horizon. Cost function is composed of inspection and maintenance costs in addition to a penalty cost due to environmental deterioration. The maintenance optimization model is formally derived. On the basis of Nelder–Mead method, inspection dates as optimal solutions are computed. A numerical example is provided to illustrate the proposed maintenance model.     

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.     

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.     

Optimal maintenance policy for equipment subject to random deterioration and random failure A modern control theory approach

The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example.     

Maintenance of deteriorating single server queues with random shocks

We consider the maintenance of single server queues in which the deterioration of a server is subject to random shocks. Shock arrivals deteriorate the server by a random amount. A maintenance policy is proposed whereby the server is repaired whenever its state is above a specified maintenance level. We present the system size distribution and sojourn time distribution. We derive the long run average cost, considering holding cost and repair cost. We analyze the proposed maintenance policy based on the cost analysis.     

基于服务性能合同模式下单部件系统视情维修策略研究

针对供应商系统维修的低效率以及维修成本参数较难获得的问题,提出了基于服务性能合同模式(PBC)下的单部件系统最优视情维修策略模型。首先,基于Gamma分布,描述单部件系统连续递增的退化过程,依据系统实时检测状态与预防维修阈值、故障阈值之间的关系,实施不同的维修策略;其次,分析单位更新周期内的检测次数和使故障设备恢复如新的维修方式,以供应商利润率最大化为目标函数,以最佳维修阈值与检测间隔时间为决策变量,建立以利润为中心的视情维修优化模型;最后,利用改进灰狼算法求解数学模型,通过算例验证所提出模型的有效性,并进行了各维修费用参数对目标函数以及最优维修策略的灵敏度分析。     

A repairable system with imperfect coverage and reboot: Bayesian and asymptotic estimation

System characteristics of a two-unit repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the coverage factor for an operating unit failure is possibly considered. Time to failure and time to repair of the operating units are assumed to follow exponential distributions. In addition, the recovery time and reboot time of the failed units also follow exponential distributions. When time to failure, time to repair, recovery time and reboot time are with uncertain parameters, a Bayesian approach is adopted to evaluate system characteristics. Monte Carlo simulation is used to derive the posterior distribution for the mean time to system failure and the steady-state availability. Some numerical experiments are performed to illustrate the results derived in this paper.     

Risk based opportunistic maintenance model for complex mechanical systems

The essence of the complex mechanical system can be considered as an open system. There exist coupling relationships between various parts in the system and also between different fault modes, which result in multiple fault propagation paths. Considering the safety, benefits and maintenance loss, parameters such as downtime losses, minimal repair costs, corrective, preventive and opportunistic maintenance costs, should be analyzed comprehensively to investigate the influence of different maintenance strategies.A new risk based opportunistic maintenance (RBOM) model considering failure risk is proposed in the paper. It helps to convert the negative random factors caused by single faults to a favorable opportunity of preventive defense against failure for other slight degraded components in advance, so the overall economic losses could be reduced. The global optimization algorithm is further developed to realize RBOM policy. Case studies are provided to illustrate the proposed approaches, with sensitivity analysis of the position, time, style and criterion of the RBOM strategy. Comparative study with the widely used maintenance policy demonstrates the advantage of the proposed method can significantly reduce the maintenance cost and failure risk, and are expected to bring immediate benefits to the energy industry.     

Replacement and standby redundancy policies in a deteriorating system with aging and random shocks

This study investigates the state-dependent maintenance policy in a multistate deteriorating production system with standby redundancy, assuming that the production system consists of one production unit and one single-server service center, and the key component of the production unit deteriorates over time. The key component deteriorates either from the current operating state to the next inferior operating state, due to aging, or from the current operating state to the failure state, due to a random shock. The deteriorating key component is replaced with a standby, according to a certain replacement policy, and sent to the service center for perfect repair; once completing the service, it joins the standbys for later production use. Both the sojourn time of a key component in each operating state, except the failure state, and the service time of a key component at the service center are assumed to be exponentially distributed. Taking into account the annual operating profit, measured in terms of production utilization and yield percentage of perfect items, and the annual operating costs, including the costs of key components and maintenance, this study jointly selects the operating state for replacing deteriorating key components and the level of standby redundancy in the system under the profit maximization objective. Numerical examples are given to illustrate the maintenance policies for systems with different transition probabilities in the deteriorating process, and the influence of transition probabilities on the maintenance policies are discussed.     

Multi-objective imperfect maintenance optimization for production system with an intermediate buffer

In several production systems, buffer stocks are built between consecutive machines to ensure the continuity of supply during interruptions of service caused by breakdowns or planned maintenance actions. However, in previous research, maintenance planning is performed individually without considering buffer stocks. In order to balance the trade-offs between them, in this study, an integrated model of buffer stocks and imperfective preventive maintenance for a production system is proposed. This paper considers a repairable machine subject to random failure for a production system by considering buffer stocks. First, the random failure rate of a machine becomes larger with the increase of the number of random failures. Thus, the renewal process is used to describe the number of random failures. Then, by considering the imperfect maintenance action reduced the age of the machine partially, a mathematical model is developed in order to determine the optimal values of the two decision variables which characterize the proposed maintenance strategy and which are: the size of the buffer stock and the maintenance interval. The optimal values are those which minimize the average total cost per time unit including maintenance cost, inventory holding cost and shortage cost, and satisfy the availability constraint. Finally, a heuristic procedure is used to solve the proposed model, and one experiment is used to evaluate the performance of the proposed methods for joint optimization between buffer stocks and maintenance policy. The results show that the proposed methods have a better performance for the joint optimization problem and can be able to obtain a relatively good solution in a short computation time.     

Two-unit repairable systems with common-cause shock failures and fuzzy parameters: parametric programming approach

This article, proposes a procedure to construct the membership functions of the system characteristics of a two-unit repairable system in series and parallel, which is subject to individual failures and common-cause shock failures. Time to individual failure and common-cause shock failure of the operating units are assumed to follow fuzzified exponential distributions. In addition, time to repair of the failed units also follow fuzzified exponential distributions. The α-cut approach is used to extract from the fuzzy repairable system a family of conventional crisp intervals for the desired system characteristics, determined with a set of parametric nonlinear programs using their membership functions. A numerical example is solved successfully to illustrate the practicality of the proposed approach. Since the system characteristics are governed by the membership functions, more information is provided for use by designers and practitioners. The successful extension of the parameter spaces to fuzzy environments permits the repairable system to have wider practical applications.     

冷/温混合贮备系统最优切换及视情维修决策

针对周期性切换冷/温混合贮备系统,研究其最优切换以及视情维修决策,在系统劣化建模的基础上,分析系统结构和切换式运行维修特性,制定基于周期切换和检测的离线视情维修策略.首先,通过分析系统运行与备用设备交替使用、维修过程中的状态转移特性,推导各检测周期时刻系统状态概率分布模型以及各维修活动的概率;然后,以系统有限时间范围内平均费用率最小为目标建立解析优化模型,以决策最优切换周期和维护阈值,并采用遗传算法对模型进行求解;最后,以汽轮发电机定子冷却水泵系统为对象验证策略和模型的正确性和有效性,并对参数进行灵敏度分析.实验结果表明,所提出离线视情维修策略能够有效地降低系统的维修成本.     

复杂系统维护策略最新研究进展: 从视情维护到预测性维护

对于复杂、可修复的工程系统, 设备维护是确保系统安全性、可靠性、可用性的重要手段之一. 系统维护策略已经历修复性维护、定时维护、视情维护等多种维护策略. 其中, 视情维护是目前最受关注的维护策略, 它通过收集和评估系统的实时状态信息进行维护决策, 具有全寿命周期内系统可靠性高、运营维护成本低等优点. 近年来, 随着物联网技术、信息技术和人工智能的快速发展, 一种更新颖的视情维护策略——预测性维护逐渐成为领域研究热点. 本文首先简要回顾了系统维护策略的发展历程; 然后, 重点介绍了视情维护的研究进展, 根据决策支持技术的不同, 将视情维护划分为基于随机退化模型的视情维护和基于数据驱动的预测性维护, 对每类技术的发展分支与研究现状进行了疏理、分析和总结; 最后, 探讨了当前复杂系统维护策略面临的挑战性问题和可能的未来研究方向.     

Bayesian computation for geometric process in maintenance problems

Geometric process modeling is a useful tool to study repairable deteriorating systems in maintenance problems. This model has been used in a variety of situations such as the determination of the optimal replacement policy and the optimal inspection-repair-replacement policy for standby systems, and the analysis of data with trend. In this article, Bayesian inference for the geometric process with several popular life distributions, for instance, the exponential distribution and the lognormal distribution, are studied. The Gibbs sampler and the Metropolis algorithm are used to compute the Bayes estimators of the parameters in the geometric process. Simulation results are presented to illustrate the use of our procedures.     

A shock model with two-type failures and optimal replacement policy

In this paper, a shock model for a repairable system with two-type failures is studied. Assume that two kinds of shock in a sequence of random shocks will make the system failed, one based on the inter-arrival time between two consecutive shocks less than a given positive value δ and the other based on the shock magnitude of single shock more than a given positive value γ. Under this assumption, we obtain some reliability indices of the shock model such as the system reliability and the mean working time before system failure. Assume further that the system after repair is ‘as good as new’, but the consecutive repair times of the system form a stochastic increasing geometric process. On the basis of the above assumptions, we consider a replacement policy N based on the number of failure of the system. Our problem is to determine an optimal replacement policy N* such that the long-run average cost per unit time is minimised. The explicit expression of long-run average cost per unit time is derived, and the corresponding optimal replacement policy can be determined analytically or numerically. Finally, a numerical example is given.     

Simultaneous optimization of repair and control-limit policy in condition-based maintenance

In condition-based maintenance (CBM) planning, collected information from system condition monitoring is the basis of making decision about conducting the maintenance and repair activities. Recently, ample number of studies has been conducted in CBM field especially, in control-limit policy. In control-limit policy, using proportional Hazards model and results of monitoring system condition, one can estimate hazard rate function and its condition’s transition probability matrix. Then, considering replacement costs, optimal control-limit can be determined minimizing the average cost in the long run. The presented model considers repair policy and their implementation cost, and the assumptions of repair during interval inspection is ignored. Then, a model is presented to determine the optimal control-limit and the best repair policy, in which the average total cost per unit time in the long-run, is minimized. At the end, a numerical example is illustrated.     

A reliability based maintenance policy; a case study

Reliability centered maintenance (RCM) incorporates sound guidance for managers who wish to attain high standards of maintenance at their operating plants. Since the amount and type of maintenance which is applied depend strongly on the machine or components age (DFR, CFR or IFR), on its replacement cost as well as on the cost and safety consequences of system failure, a careful analysis of the system components based on their reliability data should be done in order to optimize the maintenance program. This paper describes the methodology which was used at an aluminum plant in order to select critical machines and to develop an optimal maintenance policy based on reliability data of each machine, safety consequences of system failure, lead time and repair time, and components criticality.     

基于优先使用权的温贮备可修重试系统可靠性与期望成本模型

针对具有两种不同类型部件的温贮备可修系统,基于优先使用权规则,将部件的重试特性和不可靠修理设备引入系统,建立一种新的系统可靠性和成本模型.失效部件由一个不可靠修理设备维修,当正常的修理设备维修失效部件时会发生不完全故障,此时,它或以一定的概率立即被维修,或以一定的概率继续低效维修失效部件.在不完全故障下,修理设备有可能发生完全性故障,完全性故障后会立即被维修.鉴于维修环境的随机波动性,利用PH分布对修理设备的修理时间进行建模,这在一定程度上拓展了模型的适用性.通过概率讨论得到稳态下系统的一些主要性能指标,构建单位时间的总期望成本函数,并就总期望成本关于各参数的敏感性进行分析.通过数值实例展示系统参数对系统稳态性能指标和系统成本的影响,为系统可靠性设计者和决策者提供理论支撑和参考.     

Remote,condition-based maintenance for web-enabled robotic system

The current trends in industry include an integration of information and knowledge-base network with a manufacturing system, which coined a new term, e-manufacturing. From the perspective of e-manufacturing any production equipment and its control functions do not exist alone, instead becoming a part of the holistic operation system with distant monitoring, remote quality control, and fault diagnostic capabilities. The key to this new paradigm is the accessibility to a remotely located system and having the means of responding to a changing environment, which is better suited for today's rapidly changing environment. Within the framework of the web-enabled robotic system, this paper focuses on the remote maintenance schemes with an emphasis on condition-based maintenance strategies. Real-time monitoring of robot harmonic drive systems and operational status have been attained over the Web. A mathematical modeling of system availability has been derived in order to account for other failures that might occur in the subsystems of the robot. Compared to the schedule-based maintenance strategies, the proposed approach shows great potential for improving overall production efficiency, while reducing the cost of maintenance.     

Optimal non-periodic inspection scheme for a multi-component repairable system using A search algorithm

This paper proposes an approach for finding an optimal non-periodic inspection scheme on a finite time horizon for a multi-component repairable system. The system consists of several components, each of which is subjected to soft failure. Soft failures of each component do not cause the system to stop functioning, but increase the system operating costs and are detected only if inspection is performed. Thus, the system is inspected at the scheduled inspection instances and if any of its components is found to have failed, the failed component is minimally repaired. The system’s expected total cost associated with a given inspection scheme includes inspection costs, repair costs, and the penalty costs that are incurred due to the time delay between the actual occurrence of a soft failure of the components and its detection at an inspection. The objective is to determine the optimal inspection scheme which minimizes system’s expected total cost.