典型串并联系统的备件库存优化模型

选取典型串并联系统的备件库存优化为研究对象,以系统供应可用度最大为目标,备件总购置费为约束条件构建备件库存优化模型,给出基于边际分析法的优化算法.经示例分析,验证了该模型的可行性和有效性,结果可为备件保障经费的合理配置提供理论依据.     

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.     

基于需求分布规律的石化企业备件库存优化研究

石化类企业备件管理的难度较大,主要原因在于其备件需求往往是间断、离散、随机产生.针对石化类企业备件的间断需求特点,提出Markov过程的bootstrap方法取得备件需求的分布规律,在此基础上构建了备件库存优化模型,利用某大型石化企业实际管理运行数据进行了算例及仿真计算,结果验证了备件需求规律统计方法和库存优化模型的优越性,对于该类企业的备件库存管理实践提供了一定的借鉴意义.     

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.     

基于战役的多机种战伤备件需求模型

为了合理储备战时航材备件,通过分析战时故障备件的需求特点,改进了传统的单机故障备件需求模型.根据多机种协同作战任务的不同,引入备件工作运行比的概念,建立了基于作战任务的多机种故障备件需求模型.为解决多机种协同作战时的保障资源配置问题提供了思路和方法.     

改进的加权不等时距灰色IMUGM(1,m,ω)模型及其应用

针对传统的灰色预测模型的缺陷,提出了改进的多因素不等时距加权灰色预测模型.首先,以引入加权因子ω的方式建立多因素不等时距加权灰色模型,再通过初始值改进、残差修正以及新陈代谢思想相结合的方式对模型进行改进;然后结合实际消耗数据,依据欧氏距离、隶属度权值等模型,实现备件消耗预测,实例仿真及分析验证了方法的有效性.     

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.     

凸概率密度分布簇下的多损失鲁棒优化等价模型及在直营连锁企业中的应用

首先,证明了凸概率密度分布簇的单周期期望均值下单损失鲁棒优化等价模型定理,以及凸概率密度分布簇的单周期期望均值下多损失鲁棒优化等价模型。然后,提出了直营连锁企业的产品在凸概率密度分布簇下的期望均值的单周期生产分配供应问题,建立了直营连锁企业的单周期生产分配供应期望均值鲁棒模型,在获得近似周期概率分布簇情形下给出了单周期生产分配供应鲁棒模型,这种近似鲁棒模型等价于一个线性规划问题。最后,通过已知一个产品的4个周期构成的混合分布簇进行了数值实验,数值结果表明了期望均值准则下的生产分配供应鲁棒模型的生产分配供应策略更加稳健。     

基于多目标粒子群算法的电梯备件采购配置

电梯备件采购配置问题是典型.的多目标、多约束、非线性规划问题.针对该问题,根据维修BOM配置出所需采购的备件清单,并得到备件的损坏率及消耗率.最后,提出了一种多目标粒子群算法,并运用算法对某一待采购备件的配置问题进行了优化求解.实例的结果表明,对该类问题,算法能快速准确地得到最优的解.     

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.     

An improved stochastic programming model for supply chain planning of MRO spare parts

The maintenance, repair and operation (MRO) spare parts that are vital to machine operations are playing an increasingly important role in manufacturing enterprises. MRO spare parts supply chain management planning must be coordinated to ensure spare part availability while keeping the total cost to a minimum. Due to the specificity of MRO spare parts, randomness and uncertainties in production and storage should be quantified to formulate the problem in a mathematical model. Given these considerations, this paper proposes an improved stochastic programming model for the supply chain planning of MRO spare parts. In our stochastic programming model, the following improvements are made: First, we quantify the uncertain production time capacity as a random variable with a probability distribution. Second, the upper bound of the storage cost is modeled as a multi-choice variable in the constraint. To derive the equivalent deterministic model, the Lagrange interpolating polynomial approach is used. The results of the numerical examples validate the feasibility and efficiency of the proposed model. Finally, the model is tested in the supply chain planning of continuous caster (CC) bearings.     

Determining the optimal place and capacity of spare parts warehouses in the construction industry

In the construction industry, places, capacities and levels of demand in basic spare parts are changing in relatively short periods of time. This creates an optimization problem of the following form.We are given the following:o

1. (i)The location and the level of demand for each basic spare part in each work site for a specific time period.
2. (ii)The places and the levels of demand can be altered.
3. (iii)There are more than one supplier of each part geografically distributed.
4. (iv)The number of basic equipment spare parts.
5. (v)The transportation cost per load of spare parts.
6. (vi)The purchasing and functioning cost of the various air houses used as warehouses of spare parts.

In this paper we present an algorithm which determines the place, capacity and number of supply points to minimize the total cost of the supply system under the constraints (i) to (vi) above.     

基于期权的树形供应链应急模型与仿真

在多级树形供应链网络环境下,基于实物期权策略并引入中断风险成本,建立了树形供应链应对中断风险的保护与应急模型,通过求解模型得到最优策略并进行了数值仿真分析.仿真结果表明该模型能够显著降低树形供应链系统的中断风险成本与系统中断时间,从而提高供应网络的鲁棒性.     

智能制造环境下的备件生产与运输协同调度问题研究

智能制造和即时配送环境下的备件生产与运输协同调度问题是目前国内研究的一大热点,这是因为备件供应链响应速度已成为当前备件制造企业赢得客户的关键因素。为了提高客户满意度,尽可能缩短从客户下达定制化生产订单到订单配送完成的时间,本文建立了以所有客户总等待时间最短为目标的混合整数规划模型和集合覆盖模型,推导了最优解性质,并设计改进的分支定价算法求得最优解。通过将小规模算例结果与CPLEX进行对比,验证了模型和算法的有效性。多组算例测试结果表明,所提出的模型和算法可以有效提升智能制造环境下的备件供应链运作效率。     

修如新模型中备件量的计算及其置信上限的Fiducial推断

本文研究了在修如新模型下, 对预定贮存期为$T$同时开始贮存的$N$个系统, 给出在$P_0$可修复率下所需备件数的计算公式; 针对贮存寿命服从威布尔分布的系统, 利用枢轴量, 在$P_0$可修复率和预定贮存期为$T$的条件下, 给出$N$个系统所需备件数的置信上限的定义; 并基于系统寿命试验的完全样本, 利用Fiducial方法得出备件数置信上限的计算方法.     

基于双层规划的集群式供应链供应商激励机制研究

对存在多级供应商的集群式供应链中稀缺资源供应的激励问题进行了研究。在假设市场某种零部件稀缺,制造商的产量直接与零部件供应量链相关,而零部件供应量直接与一级供应商努力程度相关的情况下,建立了相应的单多双层规划模型,分别研究了制造商针对供应商结盟与不结盟的情况下的最优激励机制。最后进行了仿真,结果表明本文的激励机制能较好激励供应商并能有效防范其结盟。     

需求中断下具有提前期的双渠道供应链的风险规避决策

讨论了由一个制造商和一个零售商所组成的双渠道供应链在需求中断下具有提前期的双渠道供应链的风险规避问题.给出了在需求中断前后的最优价格、最优提前期和最优生产决策.研究表明决策变化量是需求中断量的线性函数,在集中式下最优的决策和销售量与供应链的市场份额和需求中断有关,模型的最优生产体现了一定的稳健性.对于提前期来说,当市场份额较大时,最优提前期关于风险规避系数呈正比例,当市场份额较小时,最优提前期关于风险规避系数呈反比例.     

On sourcing and stocking policies in a two-echelon,multiple location,repairable parts supply chain

This research develops policies to minimize spare part purchases and repair costs for maintaining a fleet of mission-critical systems that operate from multiple forward (base) locations within a two-echelon repairable supply chain with a central depot. We take a tactical planning perspective to support periodic decisions for spare part purchases and repair sourcing, where the repair capabilities of the various locations are overlapping. We consider three policy classes: a central policy, where all repairs are sourced to a central depot; a local policy, whereby failures are repaired at forward locations; and a mixed policy, where a fraction of the parts is repaired at the bases and the remainder is repaired at the depot. Parts are classified based on their repair cost and lead time. For each part class, we suggest a solution that is based on threshold policies or on the use of a heuristic solution algorithm that extends the industry standard of marginal analysis to determine spare parts positioning by including repair fraction sourcing. A validation study shows that the suggested heuristic performs well compared to an exhaustive search (an average 0.2% difference in cost). An extensive numerical study demonstrates that the algorithm achieves costs which are lower by about 7–12% on average, compared to common, rule-based sourcing policies.     

The final order problem for repairable spare parts under condemnation

We consider a manufacturer of complex machines that offers service contracts to her customers, committing herself to repair failed spare parts throughout a fixed service period. The suppliers of spare parts often discontinue the production of some parts as technology advances and ask the manufacturer to place a final order. We address the problem of determining final orders for such spare parts. The parts that we consider are repairable, but they are subject to the risk of condemnation. We build a transient Markovian model to represent the problem for a repairable spare part with a certain repair probability and repair lead time and we present some approximations that allow for further real-life characteristics to be included. Furthermore, an approximate model that can be computed more efficiently is presented, and the sensitivity of the results obtained with respect to the problem parameters is discussed, helping us develop several managerial insights.     

Optimization of component reliability in the design phase of capital goods

We introduce a quantitative model to support the decision on the reliability level of a critical component during its design. We consider an OEM who is responsible for the availability of its systems in the field through service contracts. Upon a failure of a critical part in a system during the exploitation phase, the failed part is replaced by a ready-for-use part from a spare parts inventory. In an out-of-stock situation, a costly emergency procedure is applied. The reliability levels and spare parts inventory levels of the critical components are the two main factors that determine the downtime and corresponding costs of the systems. These two levels are decision variables in our model. We formulate the portions of Life Cycle Costs (LCC) which are affected by a component’s reliability and its spare parts inventory level. These costs consist of design costs, production costs, and maintenance and downtime costs in the exploitation phase. We conduct exact analysis and provide an efficient optimization algorithm. We provide managerial insights through a numerical experiment which is based on real-life data.