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This paper considers procurement and allocation policies in a manufacturing environment where common components are assembled into various products that have stochastic demands. The components are allocated to the assembly of a product at a time when product demand is still uncertain (assemble to forecast, ATF). The special case of one component shared by N different products is analyzed, and insights into the general problem are obtained for the situation in which the common component can be reallocated to different products as product demands change. An allocation policy is developed for general distributions and prices in an ATF environment. The policy first addresses anomalies in the state of the system and then, for a feasible state, minimizes the expected excess finished-goods inventory. A procurement level that is nearly optimal is obtained from a Monte Carlo simulation in which the probability of satisfying all of the random product demands simultaneously is considered relative to this allocation policy. Numerical studies indicate that the total component and finished-goods inventory is significantly reduced by an allocation policy that incorporates risk pooling while still fulfilling service-level requirements.
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