Supply Chain Design and Analysys: Models and Methods

7451 Words Apr 14th, 2012 30 Pages
Supply Chain Design and Analysis:
Models and Methods

Abstract
For years, researchers and practitioners have primarily investigated the various processes within manufacturing supply chains individually.
Recently, however, there has been increasing attention placed on the performance, design, and analysis of the supply chain as a whole. This attention is largely a result of the rising costs of manufacturing, the shrinking resources of manufacturing bases, shortened product life cycles, the leveling of the playing field within manufacturing, and the globalization of market economies. The objectives of this paper are to: (1) provide a focused review of literature in multi-stage supply chain modeling and (2) define a research
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Inventory control describes the design and management of the storage policies and procedures for raw materials, work-in-process inventories, and usually, final products.
The Distribution and Logistics Process determines how products are retrieved and transported from the warehouse to retailers. These products may be transported to retailers directly, or may first be moved to distribution facilities, which, in turn, transport products to retailers. This process includes the management of inventory retrieval, transportation, and final product delivery.
These processes interact with one another to produce an integrated supply chain. The design and management of these processes determine the extent to which the supply chain works as a unit to meet required performance objectives.
3 Literature Review
The supply chain in Figure 1 consists of five stages. Generally, multi-stage models for supply chain design and analysis can be divided into four categories, by modelling approach. In the cases included here, the modelling approach is driven by the nature of the inputs and the objective of the study. The four categories are: (1) deterministic analytical models, in which the variables are known and specified (2) stochastic analytical models, where at least one of the variables is unknown, and is assumed to follow a particular probability distribution, (3) economic models, and (4) simulation models. 4
3.1 Deterministic Analytical Models
Williams (1981)