利用故障数据和估计的检查数据建立维修优化模型

利用时间延迟概念,根据故障记录数据和估计的检查数据建立了预防维修模型.通过对故障记录数据统计分析,提出了模型的假定条件.采用最大似然估计法,估计参数,包括缺陷发生率、不完全检查概率和时间延迟分布.建立了有关预防维修间隔期和总停机时间之间关系的检查模型,并根据估计参数和检查模型,计算最佳维修间隔期.     

带有机器维修和两车辆派送的单机排序问题

研究了带有机器维修和工件派送的单机排序问题,该问题可以被视为一个集成生产和出站配送的排序模型。不同体积的工件需要在带有一个维修区间的机器上加工,且加工不可中断,然后由固定容量的两辆同类车批次交付给单客户,目标函数是极小化最大完工时间,本文提出了2-近似算法,并证明了2是紧界。     

一个机器服务模型的可靠性分析

本文讨论了由Ｎ个同型部件和一个服务设备组成的机器服务模型，在服务设备绝对可靠，或服务设备具有指数寿命，修理工对其修理的时间为ＰＨ分布，这两种情况下求得了系统的平稳概率分布，从而求得机器系统和服务设备的稳态可靠性指标，并证明了它们的首次失效时间均服从ＰＨ分布，服务设备和修理工的忙期亦服从ＰＨ分布．     

工期窗口安排与具有退化效应和维修活动的单机排序

考虑具有工件相关的退化效应和维修活动的单机排序模型,讨论了工期窗口安排问题.在这一模型中,机器在加工过程中产生退化使效率降低,工件的实际加工时间不仅与其所在排序中的位置有关并且与其本身的退化率有关;然而,维修活动能使机器的加工效率得到恢复.工期窗口的开始时间是已给定的常量,而工期窗口的结束时间是需要确定的变量.目标是得到安排维修活动的最佳时间、最佳工期窗口的大小和最优排序以便最小化流时间、提早、延误和工期窗口大小的总处罚函数.对这一问题,给出了一多项式算法.     

机器维修的排序问题

研究了机器维修的排序问题,假设第i台机器的维修起始日期为第αi天(i=1,2,…,n)．n台机器的维修起始日期简记为(α1,α2,…,αn),得到一系列(α1,α2,…,αn)存在的充分或必要条件。     

维修设备可失效的两部件冷贮备系统的可靠性分析

本文讨论了两相同部件构成的冷贮备可修系统。假设维修设备可能失效,它的修理时间分布为一般分布,部件的寿命分布、失效修复时间分布及维修设备工作寿命分布都为指数分布。利用马尔可夫更新过程理论,求出了系统首次失效前时间分布、系统的可用度、(0,t)时间内系统的平均故障次数、维修设备忙的概率、维修设备首次失效前时间分布及时刻t维修设备失效的概率。     

目标是最小化最大完工时间带柔性维修时间限制的两台机器排序问题的一个近似算法

本文研究了两台机器带柔性维修时间限制的排序问题,其中第一台机器在固定的时间内必须进行维修,而第二台机器一直可用,目标是最小化所有工件的最大完工时间。工件在加工过程中不允许中断。对于该问题,我们给出了一个性能比为的近似算法,并证明了该性能比是紧的。     

独立维修两部件并联系统可靠性的进一步分析

本文考虑了具有独立维修规则的两个不同型部件并联系统的可靠性问题，在一个部件的寿命为指数分布，维修分布为Ｅｒｌａｕｇ分布，另一个部件的寿命和维修分布均为一般连续型分布的条件下，我们得到了并系统的主要可靠性指标。     

机修工人这样分工为好

某车间维修班有 6名机修工人 ,该车间有 1 2 0台同型机器 ,经长期使用观察发现 ,每台机器发生故障的概率为 0 .0 1。发生故障时 ,一名机修工人只能同时修一台。那么 ,应如何进行机保修分工 ,才能既保证不误生产 ,又能最大限度地发挥工人的潜能 ?让我们先来算一算。如果分工每人负责维修 2 0台机器 ,那么 ,当机器发生故障时 ,不能得到及时维修的概率是多少 ?由已知条件 ,同一时间发生故障机器台数 ξ是一随机变量 ,它服从二项分布 ,参数 n=2 0 ,P=0 .0 1 ,用泊松分布近似计算 ,λ=np=0 .2。当同时发生故障机器台数在 2台以上时就不能及时维…     

飞机维修短期计划模型及其算法研究

目前对于飞机维修计划的研究,大都通过精确算法一次性完成周期内所有飞机的排班优化。本文在分析传统数学规划模型的基础上,以最大化利用两次维修之间的可用飞行时间为目标,构造了飞机维修计划优化模型。然后提出了求解此模型的启发式两阶段分解算法,第一阶段优先完成需维修飞机的任务指派,第二阶段再完成余下飞机的任务指派。利用航空公司真实数据进行的数值试验表明,两阶段分解算法能够显著提高模型的求解效率和质量,可以有效求解大规模飞机维修计划制定问题。     

Marginal queue length approximations for a two-layered network with correlated queues

We consider an extension of the classical machine-repair model, where we assume that the machines, apart from receiving service from the repairman, also serve queues of products. The extended model can be viewed as a layered queueing network, where the first layer consists of the queues of products and the second layer is the ordinary machine-repair model. As the repair time of one machine may affect the time the other machine is not able to process products, the downtimes of the machines are correlated. This correlation leads to dependence between the queues of products in the first layer. Analysis of these queue length distributions is hard, as the exact dependence structure for the downtimes, or the queue lengths, is not known. Therefore, we obtain an approximation for the complete marginal queue length distribution of any queue in the first layer, by viewing such a queue as a single server queue with correlated server downtimes. Under an explicit assumption on the form of the downtime dependence, we obtain exact results for the queue length distribution for that single server queue. We use these exact results to approximate the machine-repair model. We do so by computing the downtime correlation for the latter model and by subsequently using this information to fine-tune the parameters we introduced to the single server queue. As a result, we immediately obtain an approximation for the queue length distributions of products in the machine-repair model, which we show to be highly accurate by extensive numerical experiments.     

Profit Analysis of the <Emphasis Type="Italic">M/M/R</Emphasis> Machine Repair Problem with Spares and Server Breakdowns

This paper studies the machine-repair problem consisting of M operating machines with S spares, and R servers which themselves are subject to breakdown under steady-state conditions. Spares are considered to be either cold-standby, or warm-standby or hot-standby. Failure and service times of the machines, and breakdown and repair times of the servers, are assumed to follow a negative exponential distribution. Each server is subject to breakdown even if no failed machines are in the system. A profit model is developed in order to determine the optimal values of the number of servers and spares. Numerical results are provided in which several system characteristics are evaluated for all cases under the optimal operating conditions.     

A generic approach to measuring the machine flexibility of manufacturing systems

Despite extensive studies on the flexibility of manufacturing systems over the last two decades, a unified measurement approach has not been developed. To this end, we integrate two domains of machine flexibility models from the literature: operational capability-based machine flexibility and time and cost-based machine flexibility, and propose a generic model to measure machine flexibility with consideration of uncertainties in the system. Furthermore, in our approach we include part characteristics such as processing time and processing cost, the number of operations that a machine can perform, and uncertainties in demand and machine-part assignment. The resulting framework to measure machine flexibility is a two-stage model: a super efficiency Data Envelopment Analysis Model and a flexibility model. The results show that the marginal system machine flexibility does not always increase as the number of operations that a machine can perform increases, and the system machine flexibility depends on the demand uncertainty.     

一类可靠性模型的适定性

研究由一个可靠机器，一个不可靠机器和一个缓冲库构成的生产线．首先对应于此系统的数学模型化为抽象Cauchy问题，然后运用C0-半群理论证明此模型存在唯一的非负解。     

A kernel-free quadratic surface support vector machine for semi-supervised learning

In this paper, we propose a kernel-free semi-supervised quadratic surface support vector machine model for binary classification. The model is formulated as a mixed-integer programming problem, which is equivalent to a non-convex optimization problem with absolute-value constraints. Using the relaxation techniques, we derive a semi-definite programming problem for semi-supervised learning. By solving this problem, the proposed model is tested on some artificial and public benchmark data sets. Preliminary computational results indicate that the proposed method outperforms some existing well-known methods for solving semi-supervised support vector machine with a Gaussian kernel in terms of classification accuracy.     

基于Epsilon约束法的短纤维生产调度的双目标优化研究

针对短纤维生产行业实际,本文综合考虑客户的需求差异、客户的重要程度、纤维生产设备的准备时间以及交货期差异等因素,研究连续需求下的短纤维生产排序优化问题。首先,本文建立双目标整数规划模型,即最小化客户订单总延迟和最小化机器总准备时间;其次,设计Epsilon约束算法并调用CPLEX精确求解调度方案,即帕累托前沿;最后设计非支配排序的遗传算法(NSGA-II)求解大规模生产下的调度优化方案。通过实验,证明该整数规划模型和算法对解决多客户连续需求问题具有实际价值,进而可以为短纤维生产企业提供参考。     

Joint determination of optimal safety stocks and production policy for an imperfect production system

In this article, we develop an imperfect economic manufacturing quantity (EMQ) model for an unreliable production system subject to process deterioration, machine breakdown and repair and buffer stock. The basic model is developed under general process shift, machine breakdown and repair time distributions. We suggest a computational algorithm for determination of the optimal safety stock and production run time which minimize the expected cost per unit time in the steady state. For a numerical example, we illustrate the outcome of the proposed model and perform a sensitivity analysis with respect to the model-parameters which have direct influence on the optimal decisions.     

Single-machine time-dependent scheduling problems with fixed rate-modifying activities and resumable jobs

In this paper, we deal with single machine scheduling problems subject to time dependent effects. The main point in our models is that we do not assume a constant processing rate during job processing time. Rather, processing rate changes according to a fixed schedule of activities, such as replacing a human operator by a less skilled operator. The contribution of this paper is threefold. First, we devise a time-dependent piecewise constant processing rate model and show how to compute processing time for a resumable job. Second, we prove that any time-dependent continuous piecewise linear processing time model can be generated by the proposed rate model. Finally, we propose polynomial-time algorithms for some single machine problems with job independent rate function. In these procedures the job-independent rate effect does not imply any restriction on the number of breakpoints for the corresponding continuous piecewise linear processing time model. This is a clear element of novelty with respect to the polynomial-time algorithms proposed in previous contributions for time-dependent scheduling problems.     

Modeling and analysis of machine sharing in manufacturing systems

The issue of machine sharing arises quite frequently in the design and operation of automated manufacturing systems. It is often championed as a mechanism for enhancing the flexibility and versatility of these systems. However despite its importance, our understanding of machine sharing and of its effect on system performance has remained inadequate, relying mainly on anecdotal data or limited empirical evidence. In this paper, we present an analytical model that captures the various dimensions of machine sharing and use this model to study the effect of machine sharing on performance of manufacturing systems. In particular, we examine the relationship between machine sharing and several performance measures, such as production rate, machine utilization, flow time and work-in-process inventory, for varying assumptions of system utilization, setup times, batch sizes and demand and processing variability. These relationships are then used to identify conditions under which machine sharing is of value and to determine the corresponding optimal sharing levels.     

Joint effect of stock threshold level and production policy on an unreliable production environment

In this article we develop an economic manufacturing quantity (EMQ) model subject to stochastic machine breakdown, repair and stock threshold level (STL). Instead of constant production rate, in this model production rate is considered as a decision variable. Since, the stress of the machine depends on the production rate, failure rate of the machine will be a function of the production rate. Again, in this article consideration of safety stock in all existing literature is replaced by the concept of stock threshold level (STL). Further, extra capacity of the machine is considered to buffer against the possible uncertainties of the production process where machine capacity is predetermined. The basic model is developed under general failure and general repair time distributions. Since, the assumption of variable production rate makes the objective function quite complex, so main emphasis is given on computational methodology to solve the present problem. We suggest two computational algorithms for the determination of production rate and stock threshold level which minimize the expected cost rate in the steady state. Finally, through numerical examples we illustrate the key insights of our model from managerial point of view.