1、Combining multi-class queueing networks and inventory models for performance analysis of multi-product manufacturing logistics chainsYifan Wu & Ming DongReceived: 15 October 2006 /Accepted: 6 March 2007 /Published online: 31 March 2007# Springer-Verlag London Limited 2007Abstract Manufacturing logis 。

2、tics chains consist of complex interconnections among several suppliers, manufacturing facilities, warehouses, retailers and logistics providers. Performance modeling and analysis become increasingly more important and difficult in the management of such complex manufacturing logistics networks. Man 。

3、y research studies have developed different methods to solve such problems. However, most of the research focuses on logistics systems with either a single stage or single type of product. In the real world, industries always involve multiple stages and produce multiple types of products at one stag 。

4、e. This paper is geared toward developing a new methodology by combining multi-class queueing networks and inventory models for the performance analysis of multi-product manufacturing logistic chains. A network ofmulti-class inventory queue models is presented for the performance analysis of a seria 。

5、l multi-stage manufacturing logistics chain in which multiple types of products are produced at each stage. A job queue decomposition strategy is employed to analyze the major performance measures and an approach for aggregating input streams and separating output streams is proposed to link all the 。

6、 sites or nodes in the logistics chain together. Numerical results show that the proposed method is effective for the application examples.Keywords Multi-class queueing networks .Inventory models .Multi-stage manufacturing logistic chains . Aggregation . Separation1 IntroductionA manufacturing logis 。

7、tic chain can be viewed as a network of suppliers, manufacturing sites, distribution centers, and customer locations, through which components and products flow. A node in a network can be a physical location, a sub-network, or just an operation process, while links represent material (components or 。

8、 products) flow. These networks find significant applications in manufacturing and logistics in many industries, such as the electronic and automobile industries 10. Throughout these networks, there are different sources of uncertainties, including supply (availability and quality), process (machine 。

9、 breakdown, operator variation), and demand (arrival time and volume). Moreover, these variations will propagate from upstream stages to downstream stages. These uncertainties degrade the performances of a network such as longer cycle time and lower fill-rates. Inventories at different stages of a n 。

10、etwork can be used to buffer the uncertainties, but they also have varying costs and different impacts on the end-item service level. Their effective allocation and control becomes a great challenge to the managers of logistics chains. Performance modeling and analysis become increasingly more impor 。

11、tant and difficult in the management of such complex manufacturing logistics chains. Inventory including raw materials, components and finished goods usually represents from 2060% of the total assets of manufacturing firms 2. Therefore, a good inventory management system has always been important in 。

12、 the workings of an effective manufacturing logistic chain. Motivated by this challenge, many researchers have devoted much work to this issue. However, most of the literature is focused on systems with single products only and literature on multi-stage logistics chains with multi-products is limite 。

13、d. The assumption that every stage or node of the network produces a single class of product does not characterize the real world very well since nearly all firms produce more than one kind of product with limited service capacity. In this paper, a model is developed to characterize the dynamics of。

14、complex manufacturing logistics chains with multi-product and finite capacity. An analytical method is proposed to obtain performance measures of such models. Numerical results show that the proposed method works well. Simulation techniques may generally be used to analyze the performance of a syste 。

15、m, but to identify an optimal configuration of a logistics chain, many different system variants have to be evaluated. Simulation-based evaluation is usually very time-consuming. Analytical evaluation methods are therefore needed that can determine the key performance measures quickly, even if these 。

16、 methods only approximate the true performance of the logistics chain.In order to evaluate the performance of a serial manufacturing logistics chain, a parametric decomposition approach is adopted, which has been widely used to analyze multi-stage systems or networks. The basic idea is to approximat 。

17、ely analyze the individual queues separately after approximately characterizing the arrival processes to each queue by a few parameters (usually two, one to represent the rate and another to represent the variability). The goal is to approximately represent the network dependence through these arriv 。

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标题：结合多级排队网络和库存模型用于多产品生产物流链的性能分析|结合多级排队网络和库存模型用于多产品生产物流链的性能分析毕业论文外文翻译