应对突发状况的装备备件供应网络虚拟库存策略研究

研究突发状况引起装备维修备件需求大增时,供应网络中维修站点备件库存策略问题.基于多维修站点的虚拟库构建应对突发状况的备件库存期望成本模型,考虑突发状况的发生概率和突发状况对维修站点的影响概率,比较分析了突发状况发生引起维修需求大增的情况下,维修站点独立应对和构建虚拟库横向联合应对的库存期望成本,通过算例对这两种库存期望成本模型进行了数值分析,验证了构建虚拟库应对突发状况的有效性.     

基于多种约束条件的维修备件库存优化方法研究

考虑了维修备件需求的随机性,以装备可用度、完好率置信度以及维修备件的保障程度为约束条件,运用概率论与数理统计方法,将维修备件保障费用达到最小值确定为目标函数,在此基础上,制定维修备件库存的最优方案,并通过示例验证了该方法的有效性和科学性.方法可以为其它相关领域解决物资库存与费用问题提供理论依据.     

模糊环境下可控提前期供应链库存优化的Stackelberg模型研究

为了有效地缩短提前期与降低库存成本,研究了模糊环境下可控提前期的供应链库存优化问题.利用三角形模糊数描述需求的不确定性,建立了一类模糊需求条件下可控提前期供应链库存优化的Stackelberg模型.利用三角形模糊数描述成本系数的不确定性,建立了模糊成本系数条件下可控提前期供应链库存优化的Stackelberg模型,并提出利用均值面积度量法来解模糊化.通过数值分析来验证两类模型的优化效果.     

分布式配送系统在运输时间均匀分布条件下的性能分析

本文在运输时间不确定的前提下，对分布式配送系统在两个部件和最终产品早到无限制的情形下建立了随机优化模型。我们在极小化库存费用的同时以满足定时送货要求为目标，讨论了如何确定运输提前期，并给出了敏感性分析结果。     

基于序列运算理论的不可修复件存储决策模型

针对备件需求数量与备件库存数量的随机特性,应用序列运算理论对其供需随机过程进行动态描述.通过概率性序列的期望值理论定义了备件需求满足率,并建立了一定的备件满足率要求条件下的备件存储决策模型.     

三级备件保障系统下的备件库存优化模型

目前我军装备备件保障通常采用三级保障模式,以各级备件期望短缺数量之和最小为目标,研究在不同库存水平条件下,三级备件保障系统的备件库存优化模型.经示例分析,验证了该模型的可行性和有效性,该结果可为多级备件保障提供理论依据.     

预防性维修条件下产品保修策略优化研究

为了降低保修费用,对产品的二维预防性保修策略进行优化.将预防性维修对产品的维修程度进一步细分,并用修复因子来区别不同的维修程度,提出两种程度预防性维修相结合的保修策略.针对提出的保修策略,建立保修费用模型,提出模型求解方法.通过算例,证明该保修策略的有效性,并对结果进行了分析.     

医院医疗器械—麻醉包库存策略

麻醉包对于医院来说是一种重要的医疗物品,具有需求量大,一旦缺货则损失严重等特点,为此研究了黑龙江省某医院麻醉包的库存问题.以存储费用为标准来评价和优选库存策略,共建立了四大库存模型,分别是经济批量EOQ库存模型;需求离散条件下多周期有准备成本库存模型;需求服从正态分布条件下多周期有准备成本库存模型和蒙特卡罗仿真库存控制模型.其中,三个模型得出了结果,通过证明,一个模型不符合医院实际情况.通过比较上述三个模型求得的最优化库存策略与医院实际使用的库存策略,建议采取蒙特卡罗仿真库存控制模型求解得出的结果作为医院方最优库存策略.     

供应提前期和需求不确定下库存系统的随机比较

本文研究供应提前期和需求不确定下包含最小化成本和最大化利润的一致化报童问题中随机比较实现的充分条件,并通过随机比较定量刻画提前期和需求不确定性对库存系统决策和利润的影响。首先引入报童收益函数,给出其优化前后满足随机占优及拉普拉斯变换序的充分条件。进一步,在周期需求服从指数分布的情形下,定量刻画固定提前期与提前期服从几何分布两种情况的随机单调性。最后,将上述结论应用到报童模型中,得到提前期需求对一致化报童问题的随机单调性。     

提前期可控的模糊需求周期盘点补充订货模型研究

为解决具有模糊需求的可控提前期库存管理问题,建立了提前期和盘点周期作为决策变量的周期性盘点补充订货模型,采用符号距离方法对模型进行反模糊化求解,并设计了一确定其最优存储策略的算法。结合算例分析了需求的模糊性对最优盘点周期和最小成本的影响。     

基于设备状态监控的单级备件库存系统补货策略研究

本文研究一个周期性订货的多设备同备件库存系统,将备件库存策略与设备状态监控相结合,讨论了存在设备状态监控情形下的备件库存策略。针对设备状态自然腐蚀过程和人 为修复过程的复合过程,运用一个新的马尔科夫概率转移矩阵对设备需求概率进行刻画,并在此基础上给出静态订货模型和状态监控下的动态订货模型的最优订货策略。通过对比以上两种订货策略优缺点,本文提出一种新的启发式订货策略: 基于关键状态的订货策略模型。该策略可以有效降低对全部设备实行动态监控的信息成本,且成本节省优于静态订货策略,对于企业的现实问题有着较好的指导意义。     

A stochastic model for joint spare parts inventory and planned maintenance optimisation

Spare parts demands are usually generated by the need of maintenance either preventively or at failures. These demands are difficult to predict based on historical data of past spare parts usages, and therefore, the optimal inventory control policy may be also difficult to obtain. However, it is well known that maintenance costs are related to the availability of spare parts and the penalty cost of unavailable spare parts consists of usually the cost of, for example, extended downtime for waiting the spare parts and the emergency expedition cost for acquiring the spare parts. On the other hand, proper planned maintenance intervention can reduce the number of failures and associated costs but its performance also depends on the availability of spare parts. This paper presents the joint optimisation for both the inventory control of the spare parts and the Preventive Maintenance (PM) inspection interval. The decision variables are the order interval, PM interval and order quantity. Because of the random nature of plant failures, stochastic cost models for spare parts inventory and maintenance are derived and an enumeration algorithm with stochastic dynamic programming is employed for finding the joint optimal solutions over a finite time horizon. The delay-time concept developed for inspection modelling is used to construct the probabilities of the number of failures and the number of the defective items identified at a PM epoch, which has not been used in this type of problems before. The inventory model follows a periodic review policy but with the demand governed by the need for spare parts due to maintenance. We demonstrate the developed model using a numerical example.     

Intermediate buffer analysis for a production system

In this paper, a production system consisting of two serial machines and an intermediate buffer is studied. A shortage cost is incurred when the upstream machine is down and the buffer is exhausted. The practical example for this type of system can be an automated work center or an automobile general assembly.Researches on a similar two-machine system have been done in some articles where maintenance and an intermediate buffer are considered, but the spare parts are not involved. Nevertheless, spare parts are essential for maintenance implementation, and there is interaction between the buffer inventory and the spare parts due to maintenance activity. This paper is aimed to investigate three types of cost related to the intermediate buffer inventory, and obtain their expectations as functions of several decision parameters on maintenance, buffer, and spare parts during a renewal cycle, by using mathematical analysis. The proposed method can be an important basis for further study of system cost calculation and decision making optimization.     

考虑不完美检测的两阶段点检与备件订购策略联合优化

针对设备维修与备件管理相互影响与制约的问题, 在基于延迟时间理论的基础上, 提出了两阶段点检与备件订购策略联合优化。点检是不完美的, 当点检识别设备的缺陷状态时, 进行预防更新; 设备故障时, 进行故障更新。结合设备更新时备件的状态, 采用更新报酬理论建立了以第一阶段点检时间、第二阶段点检周期和备件订购时间为决策变量, 以最小化单位时间期望成本为目标的模型。最后, 通过人工蜂群算法对模型求解, 并在数值分析中将两阶段点检策略与定期点检策略进行比较, 结果表明:两阶段点检策略始终优于定期点检策略, 验证了所建模型的有效性。     

Service differentiation in spare parts inventory management

The contemporary after-sales market is of increasing importance. One of the features required by the market is to provide differentiated service levels to different groups of customers. We use critical levels as a means to offer differentiation. Critical level policies aim to exploit the differences in target service levels by inventory rationing. In our multi-item single-location spare parts inventory model, we aim to minimize the spare parts provisioning cost, that is inventory holding and transportation cost, under the condition that aggregate mean waiting time constraints for all customer groups are met. In a computational experiment and a case study with data from a company in the semiconductor supplier industry, we show that significant cost reductions can be obtained when critical level policies are used instead of base stock policies (ie policies without critical levels).     

智能电表最优更换及备件库存联合决策

智能电表是智能电网运行的关键部件,提高其可靠性和可用度对保证电力的持续不间断供应和准确电能测量至关重要。充足的智能电表库存是其换装与维修的基本保障。本文基于智能电表的故障特性和换装需求分析,建立了智能电表的最优更换与备件库存联合决策模型,并给出了优化方法,以求得可以使系统长期平均运营成本最小的最优更换与备件库存策略。     

Consolidating Maintenance Spares

The inventory of spare parts that a firm holds depends on the number of working parts and age of the equipment to be serviced, the expected failure rate associated with each working part, and the acceptable level of service. We model the problem of consolidation of spare parts to reduce overall inventory as an integer program with a nonlinear objective function. A linear reformulation of this model is obtained that helps solve some practical instances. A more compact implicit formulation is developed and solved using a specialized branch-and-price technique. We also demonstrate how this specialized branch-and-price technique is modified to devise a very effective heuristic procedure with a prespecifiable guarantee of quality of solution produced. This provides a practical and efficient methodology for maintenance spare consolidation.     

Optimal provisioning strategies for slow moving spare parts with small lead times

When an expensive piece of equipment is bought, spare parts can often be bought at a reduced price. A decision must be made about the initial provisioning of spare parts. Furthermore, if at a certain time the stock drops to zero, because a number of failures have occurred, a decision must be made about the number of parts to be ordered. We focus on one specific expensive slow-moving part that is essential for the functioning of the equipment. The lead time of that part is small compared to its lifetime. We seek an ordering strategy for this part that covers the entire lifetime. Such a strategy should also be applicable to cases where there is uncertainty about the lifetime of the machine, the reliability of the components and the cost of failure. The main result is the development of a simple strategy that performs well in almost all cases. Furthermore, this strategy can easily deal with uncertainty and changes in the parameters.     

Planning performance based contracts considering reliability and uncertain system usage

This paper investigates a novel quantitative approach for planning and contracting performance-based logistics in the presence of uncertain system usage. Our efforts focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose an analytical model to characterize system operational availability by comprehending five performance drivers: inherent failure rate, usage rate, spare parts inventory, repair time, and the fleet size. This analytical insight into the system performance allows the service supplier to minimize the total cost across system design, production, maintenance, and repair. Two contracting schemes are investigated under cost minimization and profit maximization schemes. For the first time in literature, reliability design and service parts logistics are seamlessly integrated into one decision support model for improving operational availability while lowering the lifecycle cost. Numerical examples are provided to demonstrate the applicability and the effectiveness of the proposed decision support tool.     

Joint optimization of spare parts ordering and maintenance policies for multiple identical items subject to silent failures

In this paper the joint maintenance and spare parts ordering problem for more than one identical operating items is studied. The operating items may suffer two types of silent failures: a minor failure, which results in item malfunctioning, and a major failure, which renders the item completely out-of-function. Inspections are periodically held to detect any failures and the inspected items are preventively maintained, repaired or replaced according to their condition. Two ordering policies are investigated to supply the necessary spare parts: a periodic review and a continuous review policy. The expected total maintenance and inventory cost per time unit is derived and the proposed models are optimized for real case data. In addition, the sensitivity of the proposed models is studied through numerical examples and the effect of some key problem characteristics on the optimal decisions is discussed.