Abstract:
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Successful prevention of geometric shape deformation of products manufactured by additive manufacturing depends on building predictive deformation models. However, resource constraints impose severe restrictions on the number of test shapes of a particular type, making the use of meta models inevitable. To build such meta models of deformation with good predictive power, calibration of existing models with data from physical experiments is necessary. We propose a sequential procedure for designing physical experiments and calibrating an ensemble of existing simulation models with data obtained from such experiments.
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