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This paper presents an application of probabilistic graphical models to the problem of predicting parts demand in the automotive industry. When the production of vehicles is induced by individual orders of customers and distributed on a large number of factories located in different regions of the world, production and capacity management becomes a very challenging problem to solve. The calculation of parts demand is a complex field with high-dimensional dependency relations, which requires efficient solutions. Based on a Markov network model, a system for item planning and demand estimation is described, which was in the phase of final development and implementation.

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Pages:8

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