基于排队论的内场维修设备数量确定方法

在内场车间维修设备配置研究中,为了科学合理地确定维修设备数量需求,运用排队论的基本方法,结合飞机内场维修工作特点,提出了基于排队论的内场维修设备数量确定方法,构建了相应的数量确定模型,结合实例验证了该方法可行有效.结果表明方法可以提高飞机基层级内场车间维修设备数量确定的准确性.     

A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems

When complex systems are monitored, multi-observations from several sensors or sources may be available. These observations can be fused through Bayesian theory to give a posterior probabilistic estimate of the underlying state which is often not directly observable. This forms the basis of a Bayesian control chart where the estimated posterior probability of the state can be compared with a preset threshold level to assess whether a full inspection is needed or not. Maintenance can then be carried out if indicated as necessary by the inspection. This paper considers the design of such multivariate Bayesian control chart where both the transition between states and the relationship between observed information and the state are not Markovian. Since analytical or numerical solutions are difficult for the case considered in this paper, Monte Carlo simulation is used to obtain the optimal control chart parameters, which are the monitoring interval and the upper control limit. A two-stage failure process characterised by the delay time concept is used to describe the underlying state transition process and Bayesian theory is used to compute the posterior probability of the underlying state, which is embedded in the simulation algorithm. Extensive examples are shown to demonstrate the modelling idea.     

基于不确定性信息的多目标评估模型研究

针对航空维修质量多目标评估中存在的不确定性信息,采用区间数的相离度来确定属性的权重,再通过WAA算子得到方案的综合属性值;并根据可能度矩阵求得排序向量,从而得到评估方案.最后的算例证明了模型的可行性和可靠性.     

Optimizing Preventive Maintenance Models

We deal with the problem of scheduling preventive maintenance (PM) for a system so that, over its operating life, we minimize a performance function which reflects repair and replacement costs as well as the costs of the PM itself. It is assumed that a hazard rate model is known which predicts the frequency of system failure as a function of age. It is also assumed that each PM produces a step reduction in the effective age of the system. We consider some variations and extensions of a PM scheduling approach proposed by Lin et al. [6]. In particular we consider numerical algorithms which may be more appropriate for hazard rate models which are less simple than those used in [6] and we introduce some constraints into the problem in order to avoid the possibility of spurious solutions. We also discuss the use of automatic differentiation (AD) as a convenient tool for computing the gradients and Hessians that are needed by numerical optimization methods. The main contribution of the paper is a new problem formulation which allows the optimal number of occurrences of PM to be determined along with their optimal timings. This formulation involves the global minimization of a non-smooth performance function. In our numerical tests this is done via the algorithm DIRECT proposed by Jones et al. [19]. We show results for a number of examples, involving different hazard rate models, to give an indication of how PM schedules can vary in response to changes in relative costs of maintenance, repair and replacement. Part of this work was carried out while the first author was a Visiting Professor in the Department of Mechanical Engineering at the University of Alberta in December 2003.     

Optimizing a General Optimal Replacement Model by Fractional Programming Techniques

In this paper we adapt the well-known parametric approachfrom fractional programming to solvea class of fractional programs with a noncompact feasible region.Such fractional problems belong to an important class ofsingle component preventive maintenance models.Moreover, for a special but important subclass we showthat the subproblems occurring in this parametric approachare easy solvable.To solve the problem directly we also propose for a relatedsubclass a specialized version of the bisection method.Finally, we present some computational results for these twomethods applied to an inspection model and a minimal repair modelhaving both a unimodal failure rate.     

基于蒙特卡洛算法的航空兵场站装备广义维修过程研究

研究了适用于航空兵场站可修装备在多级备件、(s-1,s)库存下的广义维修过程解析模型。基于Monte Carlo算法,迭代产生大量样本数据,经过拟合发现该维修过程依分布收敛于一对数正态分布;再针对该样本分别以OLS(最小二乘),ML(极大似然)估计进行参数推断,得到了其稳态分布函数,通过了拟合优度检验。最后解出了该情况下装备的稳态维修度,稳态可用度等参数。对比simlox模型对该装备的评估结果,数据吻合程度较为理想。     

选择性维护决策的研究进展与挑战

在工业生产和军事领域中,生产设备或技术装备往往要求连续执行多个任务,并且在任务间隔期内需要对系统中老化或失效的部件进行维护以确保完成后续任务.然而,由于受有限的成本、时间、设备及人员等维护资源的限制,在任务间隔期内难以修复系统中的所有组成部件,决策者只能有策略地选择部分部件进行维护,从而最大程度地确保完成后续任务,这类维护决策问题被称为选择性维护.现主要介绍选择性维护决策的基本模型和特点,并从系统建模、维护程度、资源约束与资源消耗、任务特性与应用环境、优化算法五个方面综述国内外关于选择性维护决策的研究进展和发展动态,并讨论其发展趋势和挑战.     

A bivariate optimal replacement policy for a system subject to a generalized failure and repair process

Traditionally, in the studies of the optimal maintenance policies for repairable systems, the nonhomogeneous Poisson process model, which corresponds to the minimal repair process, has been intensively applied. However, in many practical situations, the repair type is not necessarily minimal. In this article, a new repair process based on a new counting process model (so‐called the generalized Polya process) is introduced. Then, the issue of the optimal replacement problem is discussed. A bivariate preventive replacement policy is developed and the properties of the optimal policy are studied. Illustrative examples are also presented. In addition, a comparison with a conventional replacement policy is performed.     

WebLogic服务器运行状态监测系统的研究和应用

WebLogic服务器作为B/S构架信息系统重要组成部分,其运行状态在信息系统状态评价中起到了十分重要的作用,是开展信息系统状态检修的重要支撑。针对电网企业信息管理系统,通过模拟真实环境进行测试分析,定义了WebLogic服务器的关键性能指标,并开发了监控程序实现对其状态的监视。通过实验验证了该状态监测系统的有效性。     

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.