Visualizing Supply Chains: A Design Study

Suppy chains describe the process by which materials are turned into products, and occur in a wide variety of contexts. As an example, consider the manufacture of desktop computers. Each computer is comprised of a variety of subcomponents, each of which is typically manufactured from a further set of components (and using various “capacities,” for example, fabrication machinery). Each part has a cost and possibly limited availability; similarly each capacity has a cost and a maximum throughput. Sometimes one component may be allowed to be substituted by another, perhaps at a greater cost or with some lead time. The computers to be manufactured have projected demands as well as expected revenue when sold.

In the Mathematics department at IBM Research our particular focus is on optimizing supply chains, making recommendations on the best parts and capacities to use to produce a particular final product, and to predict shortages with enough lead time to do something to fix it. We can also recommend, based on limited available supply, which end products to manufacture, and when to manufacture them. As part of our asset base for solving such problems, we have the Watson Implosion Technology library, which allows one to model the supply chain, setting the relevant priorities, costs, constraints, etc. As one can imagine, real-life supply chains can be enormously complex, and there is a need for the optimization modelers to be able to visualize the model, as it is being constructed, to verify its accuracy and check for anomalies.

We have created a visualization application, which we call WitViz, which directly reads a supply chain model and presents an interactive, simple to understand graphical view of the supply chain, based on the Draw2D/GEF framework, after experimenting with alternative representation methods based on spanning trees. It allows the modeler to traverse the chain interactively, probe attributes, and see relationships quickly. The graphical representation closely matches the mental model that users hold about the relationships between objects in the supply chain. We also provide linked statistical views that allow users to see the range of node or link attributes, to look for outliers, or highlight particular values of interest. These highlights can also be fed back to the graphical representation.

By: Donna L. Gresh

Published in: RC23584 in 2005


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