供应链管理中提前期影响因素分析

提前期是供应链管理中的一个重要参数。它对于基于时间段的供应链的计划开始时间和计划数量、库存控制策略、批量等都有直接的影响，分析了在供应链管理中提前期对采购件、制造件的影响因素，提出了缩短提前期的思路。     

需求和提前期不确定下的两级供应链系统研究

由一个部件提供商和一个装配商组成的两级组装供应链系统,部件提供商提供两种不同的部件给装配商进行装配;分析在单销售周期内,系统上同时存在部件的生产提前期和装配提前期的不确定,以及需求的不确定时,系统的特性.采用博弈论方法,装配商确定装配计划提前期,以及向部件提供商提交的订购量;而部件提供商确定部件生产计划提前期,以及部件批发价格.得出,首先,不确定提前期导致供应链系统订购量减小;其次,在分散控制的组装供应链系统中,系统的总生产、装配计划提前期,要大于集中控制系统中的,并且装配计划提前期与部件生产计划提前期无关;再者,过大的提前期不确定性对组装供应链系统的影响要比需求不确定对组装供应链的影响大.     

汽车行业BTO模式下缩短OTD时间的策略

在比较欧美和我国汽车行业的基础上,提出从缩短OTD提前期、建立客户响应型供应链、加强需求预测与管理、提高信息可视性和关系集成等方面优化OTD时间,并达到推动BTO模式有效实施的目的.     

基于物流能力约束的整车物流计划

基于时间竞争的敏捷供应链环境中,汽车整车物流必须按照客户订单对交货期、交货地点等的要求进行快速响应和准时配送.整车运输能力作为物流要素能力之一,由于其特殊性已成为整车物流的瓶颈,对物流绩效和供应链绩效形成重要影响.从压缩订单响应时间角度出发,在以整车运输能力为约束的条件下,提出了汽车整车物流准时配送计划问题,参照并行多机提前/拖期问题的研究方法,设计了一种制定整车物流配送计划的启发式算法,最后通过算例证明所提算法的可行性.     

允许缺货的可控提前期供应链库存优化与协调

将单个企业的可控提前期库存模型拓展到供应链环境中,并考虑了允许部分缺货后补的情形,分别建立了分散决策和联合决策情形下允许部分缺货后补的可控提前期供应链库存优化模型,并提出价格折扣机制来协调供应链成员的利益.采用数值实验方法,对所建的库存优化模型和协调机制进行了分析,结果表明:随着缺货后补比例的不断减少,供应链必须不断增大订货批量和压缩提前期以提高顾客服务水平;价格折扣机制可以使得允许缺货的可控提前期供应链达到协调的目的.     

大型印刷包装企业ERP与供应链系统集成的研究

阐述了大型印刷包装企业的ERP系统与SCM系统的集成方法;ERP系统与SCM系统集成的信息流接口;ERP系统与SCM系统的集成内容:基础数据、库存状态、客户订单、供应计划及预测.详细论述了大型印刷包装企业ERP中的供应链管理的原则以及关键部分,即供应链战术计划和运作计划、供应链计划的逻辑关系以及供应链计划方法等,并列举了供应链计划的实施范例.基于文中系统集成思想和方法,所构建的ERP系统即能满足企业需求又实用.     

随机需求条件下供应链的补货及折扣策略研究

研究一个供应商和多个零售商围绕单品种商品组成的供应链体系中,以供应商为核心的供应链库存管理,目标是通过直接降低供应商的库存成本,从而降低供应链的总成本.假设每个零售商面对服从随机正态分布的提前期客户需求,在不考虑交货时间的情况下,供应商在固定的时间间隔满足零售商的补货需要,并以价格折扣的方式补偿零售商的成本增加.由此得到较优的补货间隔,并给出了求解方法.最后,通过仿真验证了该解法的可行性并评估了该策略对各方的影响.     

含模糊服务水平的可控提前期供应链库存优化

在文献"含服务水平约束的可控提前期供应链Stackelberg模型与协调机制研究"(管理学报,2008)的基础上,进一步将服务水平约束看作一个模糊数,进而探讨具有模糊服务水平约束的可控提前期供应链库存优化问题,并采用模糊非线性规划的方法进行求解。采用数值实验方法,对所建的库存优化模型进行了分析,结果表明:最优订货批量、提前期、供应链各方库存成本和获得该成本的隶属度水平均随对模糊服务水平弹性区间的不同主观估计变化而变化。但当模糊服务水平弹性区间增大到一定程度时,会出现服务水平约束无效的情形,则最优订货决策,库存总成本,及获得该成本的隶属度均不会再发生变化。     

具有时变参数的短生命周期产品供应链协调

技术和需求的快速变化,使得时间竞争成为短生命周期产品最重要的竞争战略.压缩订货提前期在提高销售商需求预测精度的同时却使制造商的生产成本增加,分析了分散决策下提前期压缩对供应链成员利润的影响,提出采用收益共享契约进行供应链协调.研究证明选择恰当的利润分配系数能够使供应链达到Pareto优化,而利润分配系数的取值范围与订货提前期有关,随着提前期的压缩,其取值范围逐渐缩小.最后用一个算例进行了说明.     

客户化供应链中的延迟策略

简单介绍了客户化供应链的概念,描述了延迟策略的内涵。在与客户化供应链整个业务流程结合的基础上,提出了延迟策略可以分为供应延迟、制造延迟、交付延迟和服务延迟,并分别研究了它们的实施目标、实现方式以及运作过程。这四种延迟策略不仅能降低供应链成本．实现产品和服务多样化,而且能够提高供应链的敏捷性,快速响应客户个性化需求。     

面向供应链的大规模定制时间阈值理论研究

针对目前大规模定制管理运作策略中存在的主要问题,以探索提升面向供应链环境下的大规模定制生产过程中的客户服务水平为主线,在对用户订单信息特征分析与合理分类的基础上,通过引入时间阈值概念及相关理论作为协调大规模定制中范围经济同客户定制化服务水平之间矛盾的基本解决思路,并分析了影响时间阈值的各主要因素,同时在时间阈值的前提下,提出了面向供应链的大规模定制管理运作多级优化策略的思想。     

A decision support framework for global supply chain modelling: an assessment of the impact of demand,supply and lead-time uncertainties on performance

We developed a decision support framework for a global manufacturer of specialty chemicals to study the relative impact of demand, supply and lead-time uncertainties on cost and customer service performance. Our approach combines optimisation and simulation methodologies as follows: mathematical models provide optimal plans via a novel approach to the supply chain planning mechanism of the Company. Simulation models execute the supply chain plans so as to allow the examination of the outcomes under the various sources of uncertainty. The iterative use of optimisation and simulation methodologies allows the user the benefit of obtaining optimal solutions while revealing the impact of uncertainties on system performance. Our results indicate that demand uncertainty has the greatest negative impact on performance for the supply chain that we modelled in this study, emphasising the importance of effective forecasting. The relative importance of supply and lead-time uncertainties varies according to the performance measures. While our results are valid for the specific supply chain and the operating environment we modelled, our study emphasises the importance of the ability to model supply chains realistically to obtain valid and useful results.     

基于缩短供应链响应周期的运作模式研究

通过分析总结推动式和拉动式供应链的特点及对用户需求响应时间的变化，阐明基于延迟策略的推-拉结合式供应链的综合优势，提出利用延迟和压缩提前期的方法缩短供应链的响应周期；论述了对于不同生产类型企业为缩短响应时间可以采取不同的供应链运作模式；构建了基于延迟策略的模块化供应链模型，描述了该模型的运作流程以及实施中应注意的问题。     

大规模定制生产的系统协同思想及理论与方法

提出了大规模定制生产有效实施的系统集成和协同思想,强调系统整体规划下的产品设计(包括顾客和市场)、生产过程和供应链管理等多个领域的系统实施;讨论了大规模定制生产核心技术体系为主导的生产协同性,以及大规模定制生产实施技术的集成性.在此基础上,提出了相关的研究问题.     

基于GDSS的大规模动态定制供应链协调系统的研究

在指出目前普遍采用的大规模定制系统的局限性的基础上，提出了更具有普遍适用性的大规模定制系统——大规模动态定制系统(MDCS)，并在对其特性详细分析的基础上，对MDCS构建展开了分析，提出了基于GDSS的供应链协调与管理系统。     

Bullwhip and inventory variance in a closed loop supply chain

A simple dynamic model of a hybrid manufacturing/remanufacturing system is investigated. In particular we study an infinite horizon, continuous time, APIOBPCS (Automatic Pipeline Inventory and Order Based Production Control System) model. We use Åström’s method to quantify variance ratios in the closed loop supply chain. Specifically we highlight the effect of a combined “in-use” and remanufacturing lead-time and the return rate on the inventory variance and bullwhip produced by the ordering policy. Our results clearly show that a larger return rate leads to less bullwhip and less inventory variance in the plant producing new components. Thus returns can be used to absorb demand fluctuations to some extent. Longer remanufacturing and “in-use” lead-times have less impact at reducing inventory variance and bullwhip than shorter lead-times. We find that, within our specified system, that inventory variance and bullwhip is always less in supply chains with returns than supply chains without returns. We conclude by separating out the remanufacturing lead-time from the “in-use” lead-time and investigating its impact on our findings. We find that short remanufacturing lead-times do not qualitatively change our results.     

Impact analysis of customized demand information sharing on supply chain performance

In today's dynamic market environment, rapidly changing customer preferences increase the customization of products and the diversification of demand mix. Companies should understand how the demand mix influences supply chain performance and react properly to fulfil customer satisfaction as to what the customers want. This paper investigated the impact of information sharing of the demand mix on the supply chain performance, under increasing product customization, by changing customer demand pattern and production capacity. The results of simulation analysis demonstrated that a demand mix can be determined that produces the best supply chain performance. A real multi-echelon automotive supply chain was analysed for each of six performance measures and the demand mix information significantly influenced five of them. Demand variation and production capacity also resulted in significant impact on the performance measures.     

A control engineering approach to the assessment of supply chain resilience

There is no consensus on the supply chain management definition of resilience. To aid in evaluating the dynamic behaviour of such systems we need to establish clearly elucidated performance criteria that encapsulate the attributes of resilience. A literature review establishes the latter as readiness, responsiveness and recovery. We also identify robustness as a necessary condition that would complement resilience. We find that the Integral of the Time Absolute Error (ITAE) is an appropriate control engineering measure of resilience when it is applied to inventory levels and shipment rates. We use the ITAE to evaluate an often used benchmark model of make-to-stock supply chains consisting of three decision parameters. We use both linear and nonlinear forms of the model in our evaluation. Our findings suggest that optimum solutions for resilience do not yield a system that is robust to uncertainties in lead-time. Hence supply chains will experience drastic changes in their resilience performance when lead-time changes.     

The bullwhip effect on inventory under different information sharing settings based on price-sensitive demand

Information sharing (IS) is proved to be a valid method to counter demand variability amplification along the supply chain, or bullwhip effect (BWE). Different from the traditional way of measuring the BWE based on order quantity, we measure the BWE on inventory in different IS settings and try to find the best IS approach. In this paper, the retailer will face the market demand which is price-sensitive, and the price follows a first-order autoregressive process. This demand model includes some indexes that can provide more useful managerial insights than previously studied parameters. Our study identifies the best IS setting under any conditions, and clarifies that the benefits of IS will be evident when the overall market product pricing process is highly correlated over time, the demand shocks to the retailer are high, the price sensitivity coefficient is small, the overall market shocks are low, the retailer’s lead-time is long and the manufacturer’s lead-time is short.