This paper uses an experimental design and regression metamodels to evaluate the relationships between the throughput of an automated flowline and other system parameters such as the number of machines in the flowline, machine processing times, capacity of the buffer, mean time between failure, and the mean time to repair. The Taguchi approach is used in the experimental design. Sixteen simulation runs are generated to test the significance of the main effects and the two-factor interactions. Consequently, Kleijnen's regression metamodel approach is used to develop predictor models for the automated flowline throughput. Finally, a decision model is formulated to determine the optimum design level of each factor.
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