结合备件库存分类后的需求预测

备件的消耗除了日常的定期检修更换以外,还有计划外的设备损坏维修更换,因此备件的需求预测应结合备件库存分类进行。本文通过对随机选取的30种备件库存进行了ABC分类之后,在减少不必要库存的同时,也减少了库存的管理种类,在此基础上探讨了对分类后的备件进行需求预测。     

汽车4S店备件库存的优化研究

汽车备件是汽车4S店经营的一个重要项目,对它的库存进行研究有着巨大的经济效益。本文从供应链管理和汽车4S店备件库存的角度出发,为汽车4S店备件库存的管理提供有用的建议。对汽车4S店的备件库存进行分析,提出汽车4S店备件库存的优化策略。     

不同设备维修模式下的备件库存策略研究

根据不同维修模式对备件储备程度的要求，运用库存管理和可靠性工：程的相关理论，从宏观上给出了事后维修、计划维修和预知维修模式下的备件库存策略，以期达到降低备件库存水平，保障设备正常运转的双重目标。     

基于备件需求优先级的随机库存控制模型研究

根据所安装设备发生故障时对生产过程的影响,备件的需求可划分为关键需求和非关键需求。基于此,研究了需求服从泊松分布、提前期等于常数、基于(S-1,S)订货策略的随机库存模型,提出当库存降低到预定水平,则预留存货以满足关键需求的控制策略,并给出了不同优先级备件服务水平的计算方法。最后结合某核电站库存管理中的一个实例,验证了本文所设计模型的优点和准确性。     

面临零部件过期的产品销售与售后服务供应链合同分析

备件库存管理对产品售后服务至关重要,而零部件过期会影响备件库存的正常补货,进而延长故障修复时间,降低产品可用率.终身购买作为应对零部件过期的重要策略,被广泛运用在实践中.然而,学术论文中关于零件过期对供应链管理影响的研究并不多见.本文建立了同时考虑产品销售和售后服务情况下的供应链动态博弈模型,分析了客户的产品订购批量、供应商的定价决策以及备件终身购买批量之间的相互作用,探讨了保修期和零部件过期采购成本对合同均衡策略和供应链利润的影响.结果表明,当零部件过期采购成本较低时,供应商可以在延长保修期的同时降低备件库存数量,并允许一定程度的备件缺货水平,从而最大化提升产品可用率所带来的收益.同时,应当适当降低对备件数量的技术标准要求.而当零部件过期 采购成本较高时,供应商应当避免提供较长的保修期,并增加备件终身购买批量以减小零部件过期带来的负面影响.此时,备件数量的技术标准则可以适当提高.     

面临零部件过期的产品销售与售后服务供应链合同分析北大核心CSCDCSSCI

备件库存管理对产品售后服务至关重要,而零部件过期会影响备件库存的正常补货,进而延长故障修复时间,降低产品可用率.终身购买作为应对零部件过期的重要策略,被广泛运用在实践中.然而,学术论文中关于零件过期对供应链管理影响的研究并不多见.本文建立了同时考虑产品销售和售后服务情况下的供应链动态博弈模型,分析了客户的产品订购批量、供应商的定价决策以及备件终身购买批量之间的相互作用,探讨了保修期和零部件过期采购成本对合同均衡策略和供应链利润的影响•结果表明,当零部件过期采购成本较低时,供应商可以在延长保修期的同时降低备件库存数量,并允许一定程度的备件缺货水平,从而最大化提升产品可用率所带来的收益.同时,应当适当降低对备件数量的技术标准要求.而当零部件过期采购成本较高时,供应商应当避免提供较长的保修期,并增加备件终身购买批量以减小零部件过期带来的负面影响.此时,备件数量的技术标准则可以适当提高.     

二级供应链系统的三阶段协同订货模型

生产商-销售商联合生产库存系统是供应链的一个重要组成部分。但是目前协同条件下的相关订货策略具有明显的局限性,容易丢失真正的最优策略。本文利用边际分析法,通过改变销售商相邻两次订货量的大小来分析生产商和销售商库存费用的变化,发现销售商的订货量与系统库存费用变化量的确存在一定的规律。并且,进一步可以推导出该类系统的最优订货策略的订货量必须符合“三阶段”规律。根据该特点,只需设置各个阶段的初始订货量和订货次数等6个决策变量就可以构建订货策略的数学模型。该模型与直接求解的数学模型相比,不仅变量减少,而且其求解也相对简单。最后,利用各个文献中常用的两个实例仿真进行对比分析,验证了该策略确实能够找出其他策略丢失的最优解。     

基于绩效的产品维修服务合同最优设计与比较分析——考虑零部件过期的影响

基于绩效的合同 (Performance-based Contracts-PBC) 是近年来在产品售后维修服务领域出现的全新商业模式。PBC 改变了传统上供应商通过提供维修活动和销售零件获取收益的方式，将供应商最终实现的产品可用率作为客户付款的标准。在 PBC 模式下，供应商以提高产品可用率为目标，其运营管理决策需要重新审视。备件库存对维修服务十分重要，直接影响故障修复时间。而零部件过期会影响备件库存的正常补货，降低产品可用率。本文基于 Stackelberg 博弈框架，建立了两种不同惩罚机制PBC合同的供应链动态博弈模型，得出了供应商的最优合同设计方案和用户的最优产品订购批量，分析了博弈均衡策略之间的相互作用，探讨了备件过期应对策略对供应链成员最优利润的影响。结果表明，不同的惩罚机制会对供应链成员的决策产生不同的影响。相对于基于备件缺货数量的惩罚机制，基于用户停机损失的惩罚机制对供应商提高产品可用率具有更加强烈的激励效应。然而，这种惩罚机制会导致供应商对备件库存过度投资，并减少用户的产品购买数量，进而会降低供应链成员的最优利润。同时，一个有意思的结果是在基于备件缺货数量的惩罚机制下，供应链均衡状态中惩罚金额与批发价格有联动特征，使得罚金的大小不会对产品订单数量和备件库存数量产生单独的影响。     

基于神经网络的备件库存风险级别预测

本文提出了一种基于神经网络的备件库存风险级别分类方法,在对备件的供货来源、重要性、易损程度、标准化程度、供货周期等指标进行模糊评价的基础上,建立了多层前向神经网络模型,利用BP训练算法,确定神经网络模型的连接权系数。将某测井服务公司100种备件的历史数据作为样本,进行了BP训练仿真,并利用模型预测了该公司60种备件的库存风险级别,预测结果与实际结果的符合率为84%。     

供应链管理视角下的煤炭企业库存策略探讨

本文主要阐述了供应链视角下的VMI和JIM两种库存模式,库存分类管理策略,联合库存管理策略和供应商管理库存策略等问题。     

Inventory Models with Continuous and Poisson Demands and Discounted and Average Costs

We develop a new, unified approach to treating continuous‐time stochastic inventory problems with both the average and discounted cost criteria. The approach involves the development of an adjusted discounted cycle cost formula, which has an appealing intuitive interpretation. We show for the first time that an (s, S) policy is optimal in the case of demand having a compound Poisson component as well as a constant rate component. Our demand structure simultaneously generalizes the classical EOQ model and the inventory models with Poisson demand, and we indicate the reasons why this task has been a difficult one. We do not require the surplus cost function to be convex or quasi‐convex as has been assumed in the literature. Finally, we show that the optimal s is unique, but we do not know if optimal S is unique.     

Optimal Ordering Policies for Inventory Problems With Dynamic Information Delays

Information delays exist when the most recent inventory information available to the Inventory Manager (IM) is dated. In other words, the IM observes only the inventory level that belongs to an earlier period. Such situations are not uncommon, and they arise when it takes a while to process the demand data and pass the results to the IM. We introduce dynamic information delays as a Markov process into the standard multiperiod stochastic inventory problem with backorders. We develop the concept of a reference inventory position. We show that this position along with the magnitude of the latest observed delay and the age of this observation are sufficient statistics for finding the optimal order quantities. Furthermore, we establish that the optimal ordering policy is of state‐dependent base‐stock type with respect to the reference inventory position (or state‐dependent (s, S) type if there is a fixed ordering cost). The optimal base stock and (s, S) levels depend on the magnitude of the latest observed delay and the age of this observation. Finally, we study the sensitivity of the optimal base stock and the optimal cost with respect to the sufficient statistics.     

考虑碳税对备件联合订购决策影响的研究

针对价格适中、消耗量高、对装备运行起重要作用的不可修备件的库存管理问题,构建了碳税政策下由多个基层站点和一个基地站点组成的两级保障链联合库存决策模型。模型以基层站点再申请点r_i、申请量Q_i和基地站点补给次数m_i为决策变量、以备件满足率为约束、以成本为目标。最后通过策略迭代方法对模型求解,并在数值分析中研究碳税对保障链决策的影响,结果表明：碳税政策虽然增加了保障链成本,但减少了碳排放,并且在合理的税费下能够实现显著的减排效果,有助于环境成本的降低。     

The benefit of receding horizon control: Near-optimal policies for stochastic inventory control

In this paper we address the single-item, single-stocking point, non-stationary stochastic lot-sizing problem under backorder costs. It is well known that the (s, S) policy provides the optimal control for such inventory systems. However the computational difficulties and the nervousness inherent in (s, S) paved the way for the development of various near-optimal inventory control policies. We provide a systematic comparison of these policies and present their expected cost performances. We further show that when these policies are used in a receding horizon framework the cost performances improve considerably and differences among policies become insignificant.     

Computing globally optimal (s,S,T) inventory policies

We consider a single-echelon inventory installation under the (s,S,T) periodic review ordering policy. Demand is stationary random and, when unsatisfied, is backordered. Under a standard cost structure, we seek to minimize total average cost in all three policy variables; namely, the reorder level s, the order-up-to level S and the review interval T. Considering time to be continuous, we first model average total cost per unit time in terms of the decision variables. We then show that the problem can be decomposed into two simpler sub-problems; namely, the determination of locally optimal solutions in s and S (for any T) and the determination of the optimal T. We establish simple bounds and properties that allow solving both these sub-problems and propose a procedure that guarantees global optimum determination in all policy variables via finite search. Computational results reveal that the usual practice of not treating the review interval as a decision variable may carry severe cost penalties. Moreover, cost differences between (s,S,T) and other standard periodic review policies, including the simple base stock policy, are rather marginal (or even zero), when all policies are globally optimized. We provide a physical interpretation of this behavior and discuss its practical implications.     

Replenishment Policies for Multi‐Product Stochastic Inventory Systems with Correlated Demand and Joint‐Replenishment Costs

This study analyzes optimal replenishment policies that minimize expected discounted cost of multi‐product stochastic inventory systems. The distinguishing feature of the multi‐product inventory system that we analyze is the existence of correlated demand and joint‐replenishment costs across multiple products. Our objective is to understand the structure of the optimal policy and use this structure to construct a heuristic method that can solve problems set in real‐world sizes/dimensions. Using an MDP formulation we first compute the optimal policy. The optimal policy can only be computed for problems with a small number of product types due to the curse of dimensionality. Hence, using the insight gained from the optimal policy, we propose a class of policies that captures the impact of demand correlation on the structure of the optimal policy. We call this class (s, c, d, S)‐policies, and also develop an algorithm to compute good policies in this class, for large multi‐product problems. Finally using an exhaustive set of computational examples we show that policies in this class very closely approximate the optimal policy and can outperform policies analyzed in prior literature which assume independent demand. We have also included examples that illustrate performance under the average cost objective.     

The Effects of Sharing Upstream Information on Product Rollover

The process of introducing new and phasing out old products is called product rollover. This paper considers a periodic‐review inventory system consisting of a manufacturer and a retailer, where the manufacturer introduces new and improved products over an infinite planning horizon using the solo‐roll strategy. We consider two scenarios: (1) the manufacturer does not share the upstream information about new‐product introduction with the retailer and (2) the manufacturer shares the information. For each scenario, we first derive the decentralized ordering policy and the system‐optimal ordering policy with given cost parameters. We then devise an optimal supply chain contract that coordinates the inventory system. We demonstrate that when the inventory system is coordinated, information sharing improves the performance of both supply chain entities. However, this may not be true if the inventory system is not coordinated. We also show that under the optimal contract, the manufacturer has no incentive to mislead the retailer about new‐product information in the information‐sharing model. When demand variability increases, information sharing adds more benefits to the coordinated supply chain. Our research provides insights about coordinating product, financial, and information flows in supply chains with product rollover.     

Unsold Versus Unbought Commitment: Minimum Total Commitment Contracts with Nonzero Setup Costs

We study a minimum total commitment (MTC) contract embedded in a finite‐horizon periodic‐review inventory system. Under this contract, the buyer commits to purchase a minimum quantity of a single product from the supplier over the entire planning horizon. We consider nonstationary demand and per‐unit cost, discount factor, and nonzero setup cost. Because the formulations used in existing literature are unable to handle our setting, we develop a new formulation based on a state transformation technique using unsold commitment instead of unbought commitment as state variable. We first revisit the zero setup cost case and show that the optimal ordering policy is an unsold‐commitment‐dependent base‐stock policy. We also provide a simpler proof of the optimality of the dual base‐stock policy. We then study the nonzero setup cost case and prove a new result, that the optimal solution is an unsold‐commitment‐dependent (s, S) policy. We further propose two heuristic policies, which numerical tests show to perform very well. We also discuss two extensions to show the generality of our method's effectiveness. Finally, we use our results to examine the effect of different contract terms such as duration, lead time, and commitment on buyer's cost. We also compare total supply chain profits under periodic commitment, MTC, and no commitment.     

Analysis and Management of Periodic Review,Order‐Up‐To Level Inventory Systems with Order Crossover

In this article, we investigate the (R, S) periodic review, order‐up‐to level inventory control system with stochastic demand and variable leadtimes. Variable leadtimes can lead to order crossover, in which some orders arrive out of sequence. Most theoretical studies of order‐up‐to inventory systems under variable leadtimes assume that crossovers do not occur and, in so doing, overestimate the standard deviation of the realized leadtime distribution and prescribe policies that can inflate inventory costs. We develop a new analytic model of the expected costs associated with this system, making use of a novel approximation of the realized (reduced) leadtime standard deviation resulting from order crossovers. Extensive experimentation through simulation shows that our model closely approximates the true expected cost and can be used to find values of R and S that provide an expected cost close to the minimum cost. Taking account of, as opposed to ignoring, crossovers leads, on average, to substantial improvements in accuracy and significant cost reductions. Our results are particularly useful for managers seeking to reduce inventory costs in supply chains with variable leadtimes.     

A method of spare parts inventory planning

A mathematical and simulation technique is discussed to obtain integer (s1, S) solutions for a group of part numbers at spares stocking locations. The technique utilizes cost function based on stochastic integer (s, S) inventory model formulation. The results are successfully implemented to plan several million dollars of spares inventory and to plan multi-echelon initial spares provisioning in the field.