基于累积损伤过程的不完全预防维护决策

基于累积损伤过程研究旧系统的不完全预防维护策略,冲击服从非时齐Poisson过程,并产生随机的损伤量,损伤量是加法累加的.系统在累积损伤量达到k或系统运行年龄达到T时进行计划内预防维护.在两次计划内预防维护之间,当累积损伤量达到预定水平K (k K)时,对系统进行计划外维护,其费用高于计划内预防维护,利用再生过程理论得到单位时间维护成本,讨论在时齐Poisson过程下的时间预防维护策略与水平预防维护策略,同时给出算例.     

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。     

基于多Agent的车间任务招投标粗模糊集建模研究

首先通过相识集、招标集、投标集和任务集的概念 ,描述制造执行系统中的调度 Agent与资源 A-gent间任务招投标过程模型 ;基于任务的属性和资源 Agent完成任务的成本、质量、负荷和时间等属性 ,定义论域上的模糊集 ,将模糊集中的隶属度函数作为粗集的属性 ,在模糊集上作截集 ,从而获得系统的分类知识 ;收集样本数据 ,构造并分析决策表 ,进而获得调度 Agent调度决策知识 ;应用调度知识进行推理 ,从争取获得招标任务的若干个资源 Agent中 ,选出最适合招标任务的中标者 .     

修理设备可修修理延迟的N个部件串联系统的随机性状及可靠性分析北大核心CSCD

考虑N(N≥2)个同型部件串联可修系统的随机性状及修理设备的可靠性.假设修理设备在修理失效部件的过程中可能失效,失效后的修理设备需要立即修理,部件失效后需要一段随机的延迟修理时间.进一步假定系统失效后好的部件可能劣化.利用马尔科夫更新过程工具和Takács的方法,研究系统的随机性状并利用随机性状研究结果得到该系统修理设备在时刻t的失效概率以及修理设备在(O,t)内的故障次数和故障频度以及一些有意义的推论.     

修理设备可修修理延迟的N个部件串联系统的随机性状及可靠性分析

考虑N(N≥2)个同型部件串联可修系统的随机性状及修理设备的可靠性.假设修理设备在修理失效部件的过程中可能失效,失效后的修理设备需要立即修理,部件失效后需要一段随机的延迟修理时间.进一步假定系统失效后好的部件可能劣化.利用马尔科夫更新过程工具和Takács的方法,研究系统的随机性状并利用随机性状研究结果得到该系统修理设备在时刻t的失效概率以及修理设备在(O,t)内的故障次数和故障频度以及一些有意义的推论.     

基于修理设备的冷贮备可修系统的维修策略

本文研究了两同型部件,一个修理设备组成的冷贮备可修系统.在故障部件不能"修复如新"的条件下,分别以系统中部件1故障次数N,工作时间T和(N,T)为维修策略,利用更新过程和几何过程,求出修理设备经长期运行单位时间内平均停工时间表达式.并在部件寿命的分布函数和修理时间的分布函数已知的情况下,以部件1故障次数N为策略证明存在最优N*使修理设备经长期运行单位时间内平均停工时间最长.最后,通过数值例子验证最优策略的存在性.     

面向多阶段任务的武器系统备件优化配置建模

资源优化配置是作战单元维修保障的关键因素.当作战单元执行单阶段任务时,讨论了部件结构为串联系统和k/n系统的任务成功概率建模问题,在此基础上,建立了k/n结构动态变化的多阶段任务系统的任务成功概率模型.在满足系统任务成功概率约束条件下,给出了防空作战单元备件携行量优化模型,并运用边际分析法进行了求解,通过示例表明了模型的正确性.     

“货到人”拣选系统机器人任务分配的鲁棒双层规划模型

在电商“货到人”拣选系统中,如何调度系统中的机器人并对任务进行合理地分配决定着整个系统的运行效率与成本。分析“货到人”拣选系统作业流程,建立机器人数量配置、机器人调度与机器人任务分配的双层规划模型。上层模型以批量订单完成总成本最小为目标函数,以机器人调度为决策变量,构建整数规划模型;下层模型以机器人完成所有任务的平均空闲率最小为目标函数,以任务分配为决策变量,考虑机器人在完成任务过程中由于调度、避障、路径规划等导致的行走距离不确定因素,构建鲁棒优化模型。上层的调度结果制约了下层的最小平均空闲率,下层的任务分配结果影响上层的最小成本,上下层结果共同决定机器人配置决策。利用遗传算法求解模型,通过实例仿真验证了模型的有效性。     

复杂设备最佳维修周期优化决策模型研究

针对现行三级维修机构保障的复杂设备,以规定可用度为约束条件,以单位工作时间内的平均维修费用最低为目标,通过对设备使用、修理流程分析,给出了设备使用与修理状态转移图,建立了设备一个更新周期内,维修周期与维修费用关系模型,并给出了相应应用案例,案例说明了模型的适用性与灵敏性,为维修决策和后续备件保障等提供依据.     

部件有两类故障状态且修理设备可更换的并联可修系统分析

本文考虑由两个同型部件组成的并联可修系统,每个部件有两类故障状态,部件故障后立即修理,且修理设备在修理故障部件的过程中也可能发生故障.假定部件的寿命和修理设备的寿命均服从指数分布,部件发生故障后的修理时间和修理设备故障后的更换时间均服从一般分布,利用马尔可夫更新过程理论,求得系统的有关可靠性指标和修理设备的闲期长度和"广义忙期"长度等一系列结果.     

Selective maintenance for support equipment involving multiple maintenance actions

Selective maintenance is the process of identifying a subset among sets of desirable maintenance actions. Previous works use mathematical programming models for making selective maintenance decisions for production equipment and military vehicles, which perform sequences of missions and are repaired only between missions. In this paper, extensions of these models are proposed. First, system component life is assumed to follow Weibull distributions. Second, the decision-maker is given multiple maintenance options: minimal repair on failed components, replacement of failed components, and replacement of functioning components (preventive maintenance).     

Optimizing maintenance service contracts under imperfect maintenance and a finite time horizon

When a company decides to outsource a service, the most important reasons for doing so usually are to focus on core business, to be able to access high‐quality services at lower costs, or to benefit from risk sharing. However, service contracts typically follow a structure whereby both owner and contractor attempt to maximize expected profits in a noncoordinated way. Previous research has considered supply chain coordination by means of contracts but is based on unrealistic assumptions such as perfect maintenance and infinite time‐span contracts. In this work, these limitations are overcome by defining the supply chain through a preventive maintenance strategy that maximizes the total expected profit for both parties in a finite time‐span contract. This paper presents a model to establish such conditions when maintenance is imperfect, and the contract duration is fixed through a number of preventive maintenance actions along a significant part of the asset life cycle under consideration. This formulation leads to a win–win coordination under a set of restrictions that can be evaluated a priori. The proposed contract conditions motivate stakeholders to continually improve their maintenance services to reach channel coordination in which both parties obtain higher rewards. Copyright © 2012 John Wiley & Sons, Ltd.     

基于综合重要度的动车组多部件系统机会维修策略研究

针对我国动车组列车现行维修方式,提出基于综合重要度序列的动车组多部件系统机会维修策略,对提高系统可靠度贡献大的关键部件进行准时优先维修。建立部件综合重要度指数计算模型,并依据其对部件维修优先级进行排序。以维修总成本最低为目标计算单部件最优维修周期及时刻,以系统维修总成本最低为目标,以关键部件的维修时刻为系统停机时刻建立考虑重要度的多部件系统机会维修模型。算例选取某型动车组四级修时更换的四部件系统为研究对象,讨论机会维修里程窗的大小及其偏移量对维修效果的影响,对比结果表明,考虑综合重要度的机会维修策略能够在维修费用基本持平的条件下,保证对系统可靠性贡献大的关键部件的可靠性,进而保证系统的整体可靠性。     

Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms

Heavy industry maintenance facilities at aircraft service centers or railroad yards must contend with scheduling preventive maintenance tasks to ensure critical equipment remains available. The workforce that performs these tasks are often high-paid, which means the task scheduling should minimize worker idle time. Idle time can always be minimized by reducing the workforce. However, all preventive maintenance tasks should be completed as quickly as possible to make equipment available. This means the completion time should be also minimized. Unfortunately, a small workforce cannot complete many maintenance tasks per hour. Hence, there is a tradeoff: should the workforce be small to reduce idle time or should it be large so more maintenance can be performed each hour? A cost effective schedule should strike some balance between a minimum schedule and a minimum size workforce.     

The Aircraft Maintenance Base Location Problem

Aviation authorities such as the Federal Aviation Administration (FAA) provide stringent guidelines for aircraft maintenance, with violations leading to significant penalties for airlines. Moreover, poorly maintained aircraft can lead to mass cancellation of flights, causing tremendous inconvenience to passengers and resulting in a significant erosion in brand image for the airline in question. Aircraft maintenance operations of a complex and extended nature can only be performed at designated maintenance bases. Aircraft maintenance planning literature has focused on developing good tail-number routing plans, while assuming that the locations of the maintenance bases themselves are fixed. This paper considers an inverse optimization problem, viz., locating a minimal number of maintenance bases on an Euler tour, while ensuring that all required aircraft maintenance activities can be performed with a stipulated periodicity. The Aircraft Maintenance Base Location Problem (AMBLP) is shown to be NP-complete and a new lower bound is developed for the problem. The performance of four simple “quick and dirty” heuristics for obtaining feasible solutions to AMBLP is analyzed.     

Prioritization of medical equipment for maintenance decisions

Clinical engineering departments in hospitals are responsible for establishing and regulating a Medical Equipment Management Program to ensure that medical devices are safe and reliable. In order to mitigate functional failures, significant and critical devices should be identified and prioritized. In this paper, we present a multi-criteria decision-making model to prioritize medical devices according to their criticality. Devices with lower criticality scores can be assigned a lower priority in a maintenance management program. However, those with higher scores should be investigated in detail to find the reasons for their higher criticality, and appropriate actions, such as ‘preventive maintenance’, ‘user training’, ‘redesigning the device’, etc, should be taken. In this paper,we also describe how individual score values obtained for each criterion can be used to establish guidelines for appropriate maintenance strategies for different classes of devices. The information of 26 different medical devices is extracted from a hospital's maintenance management system to illustrate an application of the proposed model.     

Designing global supply networks for conflict or disaster support: the case of the Canadian Armed Forces

In order to fulfil Canada’s international disaster relief, humanitarian assistance, peacekeeping and peace enforcement roles, the Canadian Forces (CF) rely on a supply network to deploy and sustain its overseas missions. Warehousing, maintenance, transhipment and transportation activities are required to support missions. Currently, the CF supply network does not incorporate any permanent overseas depots. Since international needs and Canada’s roles have significantly evolved during the last decade, and given that supply network efficiency and robustness are critical for missions’ success, reengineering the CF supply network to consider the incorporation of permanent international prepositioning depots has become an important issue. This paper proposes an activity-based stochastic programming model to optimise the CF overseas supply network. It also shows how the model proposed can be used to improve the global reach of the CF.     

Exact and heuristic methods for the selective maintenance problem

We present in this paper, new resolution methods for the selective maintenance problem. This problem consists in finding the best choice of maintenance actions to be performed on a multicomponent system, so as to maximize the system reliability, within a time window of a limited duration. When the number of components of the system is important, this combinatorial problem is not easy to solve, in particular because of the nonlinear objective function modeling the system reliability. This problem did not receive much attention yet. Consequently, rare are the effective resolution methods that are offered to the user. We thus developed heuristics and an exact method based on a branch and bound procedure, which we apply to various system configurations. We compare the obtained results, and we evaluate the best method to be used in various situations.     

On a periodic maintenance problem

In this paper, a machine maintenance problem, in which n machines are to be served on a regular, periodic basis, is studied. In particular, we are interested in how the maintenance cycles of the machines can be initiated so that all service requirements can be fulfilled by k servers.     

Single-machine scheduling problems with both start-time dependent learning and position dependent aging effects under deteriorating maintenance consideration

In this paper we introduce a new model of joint start-time dependent learning and position dependent aging effects into single-machine scheduling problems. The machine may need maintenance to improve its production efficiency. The objectives are to find jointly the optimal maintenance position and the optimal sequence such that the makespan, the total completion time, and the total absolute deviation of completion times (TADC) are minimized. We also aim to determine jointly the optimal maintenance position, the optimal due-window size and location, and the optimal sequence to minimize the sum of earliness, tardiness and due-window related costs function. We show that all the studied problems can be optimally solved by polynomial time algorithms.