Abstract
In this paper, an analytical parametric model is presented for the swift prediction of small features producible in the X-Y plane through the Metal AM Laser Powder Bed Fusion (LPBF) process. This model can be employed to design and create surface textures on Additive Manufactured parts without the need for costly post-processing steps. The Rosenthal equation is the basis for the model, which considers both the build parameters of the LPBF process and the thermo-physical properties of the materials. The initial model was constructed and assessed using one LPBF machine followed by the implementation of a tuning method utilizing the Limited Memory Algorithm for Bound Constrained Optimization to enhance the model’s accuracy. Overall, the findings suggest that with a simple optimization step based on a single printed tuning sample, precise analytical models can be established for specific LPBF machines and materials combinations.
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