基于排队论的专项汽修厂维修台配置数量研究

为了解决因维修台配置不合理而导致的专项汽修厂排队等待的问题,运用排队论等理论和方法,采用先到先修理与维修台带有优先权相结合的排队规则,将维修台配置数量问题转化为两类型服务台排队问题,建立了单队列M/M/s1+s2/K/∞/FCFS+PS排队模型.通过对某专项汽修厂相关的数据采集和分析,得到了模型所需的变量和参数,运用边际效益法进行优化,得到了节假日和非节假日客流高峰期的最优维修台配置数量.通过对系统服务强度、系统资源限制和服务时间段等因素的分析,既能保证排队系统可以在不同时间段内对维修台配置数量进行调整,又能缩小最优值的求解范围.     

飞机退役时限及补充数量的预测研究

飞机的退役是航空装备管理中的重要问题之一.为科学合理地确定飞机退役时限,针对部队飞机使用情况,以某型飞机为例,对飞机的剩余寿命进行详细分析,应用统计学方法,探讨了飞机退役时限和数量的变化规律,在此基础上建立了飞机补充数量预测模型.并结合空军装备发展的实际,对飞机使用过程中的更新换代问题进行了探讨.     

超市收银台最优数量的设置

本文运用排队论理论对超市多个M/M/1/∞/∞的排队系统进行研究,将M/M/s/∞/∞与多个M/M/1/∞/∞进行对比,然后通过对结果进行对比分析、参赛的灵敏度分析,确定出收银台的最佳数量.     

一个基于多类顾客和多阶段排队模型的设备维修案例仿真

通过对一个设备维修案例进行研究,建立了顾客到达、服务时间、服务台故障间隔、故障修复均为负指数分布且相互独立的多类顾客和多阶段排队系统模型.然后,根据时钟推进法构建排队仿真流程,应用MATLAB仿真,结合VSM,对系统进行分析改进.仿真结果表明周期时间由26.06小时减少至4.05小时,增值比由1.82%上升至15.08%,为多类顾客和多阶段排队系统优化提供参考依据.     

一个具有随机丢弃分组机制且分组成批到达的GI~X/M/1/N排队系统

利用排队论中输入流稀疏化的方法,在标准的GIX/M/1/N排队系统中嵌入网络交换设备随机丢弃分组的机制,建立了一个具有随机丢弃分组机制的扩充的GIX/M/1/N排队系统,并讨论了该排队系统的分组丢失率、系统利用率、队列长度的均值/方差、平均等待时间等性能评价指标.     

排队论与标值点过程

现代鞅论的一个重要应用领域是排队论,这方面的文献最早见于 P.Brémaud.尔后,Martins-Netto 与 Wong,用鞅方法讨论了单输入单输出排队过程的最优控制问题.1981年,Brémaud 在[3]中系统地介绍了鞅方法在排队论中的应用.该书主要讨论简单排队问题,在第八章例3中提到用标值点过程描述的排队过程,但没有展开讨论.标值点过程的鞅方法是研究成批到达成批输出排队系统的有用工具,本文打算对此略作     

飞机初始备件品种优化的集对-粗糙集方法

飞机初始备件品种的确定是飞机初始使用和维修工作的必要条件.本文针对初始备件品种影响因素信息不完备的特点,依据集对分析方法在系统中的某一特性上具有同异反定量刻画的优势,结合经典粗糙集理论,提出初始备件品种优化的集对-粗糙集方法,最终得到初始备件品种优化的决策规则.实例计算表明,该方法能够为军方优化初始备件清单提供科学合理的决策.     

某型人工台断话问题建模分析及应用

该文利用排队论建立概率模型,估计出了由于设备软件设计缺陷造成断话的概率,并确定了软件设计缺陷是造成系统断话的主要原因。经采取相应措施后断话率大幅降低(经计算至少减少39.6%),提高了通信网的可靠性和稳定性,是利用概率统计方法分析解决通信网系运行故障的有效尝试。     

基于BERT的短文本分类模型及在铁路CIR设备故障诊断中的应用

在设备故障诊断领域,操作说明、维修记录等文本数据具有极大的应用价值,充分挖掘和利用这类数据能大幅度提升故障诊断的工作效率.现有研究常用语义特征抽取及无监督聚类方法挖掘文本数据,辅助进行故障定位,但这类方法通常无法解释故障原因和给出提供相应维修方案的理由,据此生成的故障维修方案不易于理解.文章基于现有的成熟预训练语言模型BERT (bidirectional encoder representation from transformers),提出了一种基于BERT的短文本分类模型和知识图谱结合的故障定位方法,以充分挖掘和利用铁路CIR设备的文本数据中蕴含的知识和规律.所用方法首先基于CIR设备的功能层次关系确定故障模块,然后借助基于BERT的文本分类技术实现故障的初步定位,最后结合知识图谱进一步确定故障原因等信息辅助进行故障诊断,基于知识图谱积累的故障诊断知识提供故障维修方案易于维修人员理解,有助于知识的管理和工程效率的提升.在文本分类技术方面,文章利用铁路CIR设备故障维修台账记录数据进行实验,实验结果证明,基于BERT的短文本分类模型相较传统分类模型在性能上有较大的提升;在故障诊断方...     

具有风险敏感性顾客的离散时间排队系统策略研究

结合博弈论研究排队系统中顾客的策略行为成为当前排队论研究的一个热点.本文研究了离散时间排队系统中风险敏感性顾客的策略行为.不同于经典排队经济学的是,本文的效用函数是期望-方差二次效用函数.根据纳什均衡和马氏过程理论,该文分别研究了在完全可视和完全不可视两种情况下Geo/Geo/1排队系统中风险敏感性顾客的博弈行为.得到了风险敏感性顾客的个体最优策略、社会最优策略和服务商利润最优策略.研究发现,风险敏感系数越小,顾客越喜欢冒险,加入系统的意愿越强.数值实验探索了风险敏感系数对顾客策略行为的影响.     

A value-adding approach to reliability under preventive maintenance costs and its applications

No equipment (system) can be perfectly reliable in spite of the utmost care and best efforts on the part of the designer, decision-maker and manufacturer. The two sides of maintenance are corrective and preventive maintenance. It is generally assumed that a preventive maintenance action is less costly than a repair maintenance action. We examine this proposition in detail on the basis of a failure-time model that relates conformance quality to reliability. Illustratively, we present reliability in the context of contracts with asymmetric information. The model shows how to overcome information rents through price distortions and quantity rationing. The paper ends with a conclusion and an outlook to future studies.     

A periodic review production and maintenance model with random demand,deteriorating equipment,and binomial yield

In many environments, product yield is heavily influenced by equipment condition. Despite this fact, previous research has either focused on the issue of maintenance, ignoring the effect of equipment condition on yield, or has focused on the issue of production, omitting the possibility of actively changing the machine state. We formulate a Markov decision process model of a single-stage production system in which demand is random. The product yield has a binomial distribution that depends on the equipment condition, which deteriorates over time. The objective is to choose simultaneously the equipment maintenance schedule as well as the quantity to produce in a way that minimizes the sum of expected production, backorder, and holding costs. After proving some results about the structural properties of the optimal policy, numerical problems are used to compare this method to the typical approach of solving the maintenance and production problems sequentially. The results show that the simultaneous solution provides substantial gains over the sequential approach. In the cases studied, the proposed method resulted in an average cost savings of approximately 18%.     

固定通信台站装备保障人员需求预测研究

固定通信台站维修保障人员是装备保障的主体。将固定通信台站保障任务分为通信值勤、预防性维修保障及修复性维修保障任务三类,分析三类保障任务特点,确定保障人员需求预测方法。分析值勤人员动态特点,计算值勤人员需求期望向量;分析预防性维修任务量和维修时间,建立预防性维修人员需求量的周期模型;通过积分法分析修复性保障任务的任务量,估计修复性维修人员的需求量。     

工业互联网环境下预防性维修管理多目标协同优化

工期、成本、质量通常作为传统项目管理过程中三大目标,而工业互联网环境下预防性维修管理除了以上三大目标之外还更多的考虑了安全因素.根据设备机群内不同设备分析了其四大目标不同构成和内涵,四大目标决策权重采用经改进的带置信度的专家确定方法,根据工期约束等因素导出资源使用均衡条件.在此基础上构建了非线性条件下四方关系多属性效用函数模型.采用线性递减收敛因子改进下的多点交叉遗传算法进行优化求解,促使种群快速寻找最优解,算法表现出较好的收敛性和多样性使得寻优过程更加合理.     

多元Lanchester方程在装备战损量预计中的应用

在战时装备保障中,装备战损量预计是一难点问题.本文从分析影响装备战损的因素出发,采用多元Lanchester方程寻求解决方案.提出了基于指数多元Lanchester方程的装备战损量预计模型和模型中毁伤系数的确定方法.据此,建立了一种新的装备战损量预计方法,并举例验证.该方法较好的满足了未来信息化条件下作战装备保障的需要,具有重要的参考价值.     

基于遗传算法的多目标柔性工作车间调度问题求解

本文针对柔性工作车间调度问题给出了一个有意义的综合目标尽可能缩短制造周期的同时尽可能的减少机器负荷。由于传统遗传算法在多目标柔性工作车间调度问题上的局限性，我们提出了一种改进遗传算法：首先，我们给出了针对综合目标的工序调度算法获得初始集合；接着，针对柔性工作车间调度问题的特点，我们在常用的基于工序顺序的编码方法上融入了基于机器分配的编码方法，并据此设计了相应的交叉变异操作；最后借鉴了物种进化现象中的环境迁移思想设计了解决多目标优化问题的迁移操作。实验结果表明，改进的遗传算法在多目标柔性工作车间调度问题的解决上要优于传统遗传算法。     

提前期不确定条件下的预防性维修备件存储模型研究

在考虑预防性维修周期和提前期不确定的条件下,分别研究备件存储与其相关的维修费用、缺货费用、库存费用以及订购费用等四种费用之间的关系,明确了备件存储量对各项费用的影响.以各项费用总和最小化为目标,构建了提前期不确定条件下的预防性维修备件存储模型.通过备件存储模型的构建,对备件存储过程中的各项成本进行分析,以期对备件库存策略的确定给出一种解决方案.     

Unit Load Size Determination Based on Economic Move Quantity

Material handling in job shop environments is accomplished through the transfer of parts between work centres. Parts that are grouped together prior to transfer form a unit load. A new method is proposed for determining the unit load size, called the economic move quantity (EMQ), based on cost considerations during the design phase of the production system. EMQ takes into account system performance through the use of a queueing network model.     

Multi-objective open shop scheduling by considering human error and preventive maintenance

This study presents an open shop scheduling model by considering human error and preventive maintenance. The proposed mathematical model takes into account conflicting objective functions including makespan, human error and machine availability. In order to find the optimum scheduling, human error, maintenance and production factors are considered, simultaneously. Human error is measured by Human Error Assessment and Reduction Technique (HEART). Three metaheuristic methods including non-dominated sorting genetic algorithm-II (NSGA-II), multi-objective particle swarm optimization (MOPSO) and strength Pareto evolutionary algorithm II (SPEA-II) are developed to find near-optimal solution. The Taguchi method is applied by adjusting parameters of metaheuristic algorithms. Several illustrative examples and a real case study (auto spare parts manufacturer) are applied to show the applicability of the multi-objective mixed integer nonlinear programming model. The proposed approach of this study may be used for similar open shop problems with minor modifications.     

Workforce-constrained maintenance scheduling for military aircraft fleet: a case study

The problem is related to a fleet of military aircraft with a certain flying program in which the availability of the aircraft sufficient to meet the flying program is a challenging issue. During the pre- or after-flight inspections, some component failures of the aircraft may be found. In such cases, the aircraft are sent to the repair shop to be scheduled for maintenance jobs, consisting of failure repairs or preventive maintenance tasks. The objective is to schedule the jobs in such a way that sufficient number of aircrafts is available for the next flight programs. The main resource, as well as the main constraint, in the shop is skilled-workforce. The problem is formulated as a mixed-integer mathematical programming model in which the network flow structure is used to simulate the flow of aircraft between missions, hanger and repair shop. The proposed model is solved using the classical Branch-and-Bound method and its performance is verified and analyzed in terms of a number of test problems adopted from the real data. The results empirically supported practical utility of the proposed model.