Application of Markov renewal theory and semi-Markov decision processes in maintenance modeling and optimization of multi-unit systems

In this paper, a condition-based maintenance model for a multi-unit production system is proposed and analyzed using Markov renewal theory. The units of the system are subject to gradual deterioration, and the gradual deterioration process of each unit is described by a three-state continuous time homogeneous Markov chain with two working states and a failure state. The production rate of the system is influenced by the deterioration process and the demand is constant. The states of the units are observable through regular inspections and the decision to perform maintenance depends on the number of units in each state. The objective is to obtain the steady-state characteristics and the formula for the long-run average cost for the controlled system. The optimal policy is obtained using a dynamic programming algorithm. The result is validated using a semi-Markov decision process formulation and the policy iteration algorithm. Moreover, an analytical expression is obtained for the calculation of the mean time to initiate maintenance using the first passage time theory.     

提高建筑消防设施完好率探讨

分析了建筑消防设施现状及完好率低的原因,提出改变消防管理模式,建立塔式管理的建议,并从严把消防产品质量关、加强施工队伍管理、发挥消防中介机构作用、强化消防设施维护保养、提高技防水平等方面给出了提高建筑消防设施完好率的措施。     

舰船维修器材保障点选址决策模型及算法

传统的最大覆盖选址模型没有考虑对服务半径外的需求点的满足和服务时间的响应,而在舰船维修器材保障中,不论需求点到保障点的距离是否大于服务半径,都应对其进行保障服务,且在保障过程中要满足保障时间控制在不影响舰船正常维修任务时间内。针对此问题,运用广义最大覆盖选址模型和时间满意度函数,构建基于时间满意的广义最大覆盖选址模型,并运用一种混合算法———基于遗传模拟退火算法的BP算法对模型进行求解。最后,运用该算法对实例进行了分析计算,计算结果验证了该算法的有效性。     

Nonperiodic preventive maintenance for repairable systems

As a complex system with multiple components usually deteriorates with age, preventive maintenance (PM) is often performed to keep the system functioning in a good state to prolong its effective age. In this study, a nonhomogeneous Poisson process with a power law failure intensity is used to describe the deterioration of a repairable system, and the optimal nonperiodic PM schedule can be determined to minimize the expected total cost per unit time. However, since the determination of such optimal PM policies may involve numerous uncertainties, which typically make the analyses difficult to perform because of the scarcity of data, a Bayesian decision model, which utilizes all available information effectively, is also proposed for determining the optimal PM strategies. A numerical example with a real failure data set is used to illustrate the effectiveness of the proposed approach. The results show that the optimal schedules derived by Bayesian approach are relatively more conservative than that for non‐Bayesian approach because of the uncertainty of the intensity function, and if the intensity function are updated using the collected data set, which indicates more severe deterioration than the prior belief, replacing the entire system instead of frequent PM activities before serious deterioration is suggested. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010     

随舰备件需求分析中维修策略问题

分析了面向任务保障性工程理论指导下的舰船随舰备件配置问题,就最大、最小两种维修策略下随舰备件配置问题进行了研究,给出了面向任务的随舰备件需求分析仿真模型框架,结合算倒,研究了最大维修策略与最小维修策略的适用时机:在任务确定且任务结构函数明确条件下,应采用最小维修策略;否则采用最大维修策略.     

装备维修社会化研究

新型装备的科技含量不断提升，战场透明度不断增大，装备的损坏率也在不断提高，如何快速抢修损坏装备，恢复其保障能力，是事关战争胜负的一个关键环节。针对装备维修力量如何满足未来信息化战争装备保障需求，分析了装备维修社会化的必要性与可行性，提出了装备维修社会化的模式构想。     

一种基于辅助交互的手抓握动作生成方法

针对沉浸式、非沉浸式和混合式虚拟维修系统中,维修动作交互过程繁琐、实现效果不佳的问题,提出一种高效的辅助交互方法,首先基于现有的维修动作规则和用户对维修任务的理解,建立了用户辅助信息接口和系统反馈辅助信息接口,前者由用户提供抓取目标、抓取手形和抓握点等辅助信息加速交互过程,系统通过后者反馈辅助信息帮助用户进一步决策,然后应用增广矩阵方法对经典逆向运动学算法进行扩展并生成具体的维修动作,最后应用该方法实现了装备车辆轮胎更换任务中维修动作的生成,维修动作交互过程的鲁棒性和效率得到显著提高。     

本体驱动的多分辨率联邦一致性维护方法

传统的聚合解聚方法仅能解决语法层的数据聚合解聚的参数静态匹配问题,却不能解决联邦一致性的其他两个重要的方面:数据的语义匹配合理性及联邦运行中的动态一致性。为了解决以上两个问题,提出了一种本体驱动的多分辨率联邦一致性维护框架——OCM框架。该框架基于本体创建与融合技术构建联邦本体,通过邦员本体与联邦本体间的映射,解决了联邦数据匹配的合理性问题;基于聚合解聚方法,引入管理与协调联邦实体状态的邦员,通过合理设计联邦的实时对象更新及交互机制,实现了联邦实体状态的实时一致性。实验结果表明:OCM框架能有效保持联邦中多分辨率实体的状态一致,并且由于联邦本体的可重用性,对邦员的增加与退出不敏感,因此联邦的重组合也具有一定的借鉴价值。     

基于预防性维修工作组合的维修等级优化研究

针对单部件的维修间隔期无法反映系统的维修最佳间隔期这一问题,对装备各部件在各修理级别上的预防性维修任务组合情况进行了探索。通过建立费用模型作为决策模型,用以组合某一修理级别各部件的维修工作,得出系统预防性维修间隔期,并结合部队实际从系统的角度优化等级维修中的维修工作间隔期,为确定大、中、小修工作提供科学、合理的理论指导。该算法在区分各修理级别的维修能力的基础上,能较好地对各修理级别的维修工作组合情况进行了优化。实例验证了模型的实用性和有效性。     

Optimal maintenance policies for a safety‐critical system and its deteriorating sensor

We consider the integrated problem of optimally maintaining an imperfect, deteriorating sensor and the safety‐critical system it monitors. The sensor's costless observations of the binary state of the system become less informative over time. A costly full inspection may be conducted to perfectly discern the state of the system, after which the system is replaced if it is in the out‐of‐control state. In addition, a full inspection provides the opportunity to replace the sensor. We formulate the problem of adaptively scheduling full inspections and sensor replacements using a partially observable Markov decision process (POMDP) model. The objective is to minimize the total expected discounted costs associated with system operation, full inspection, system replacement, and sensor replacement. We show that the optimal policy has a threshold structure and demonstrate the value of coordinating system and sensor maintenance via numerical examples. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 399–417, 2017