This paper proposes a digital model to generate the profile of additively manufactured (AM) surfaces, specifically for vat polymerization (VP) parts, and based on laser stereolithography (SLA) physics to consider the fabrication-media interaction, which impacts surface roughness. Two SLA resins with different photocuring properties were tested on both convex and concave surfaces, with a radius ranging from 6 mm to 10 mm, and layer thickness ( \(\:t\) ) of 50 μm; measuring roughness, waviness, and profile averages ( \(\:{R}_{a}\) , \(\:{W}_{a}\) , and \(\:{P}_{a}\) respectively). A Gaussian filter was implemented in the model, replicating the experimental setup conditions and following standard guidelines. The results prove the influence of photocuring properties and deliver a fair accuracy on all three average estimations, with discrepancies related to the inherent variability of profile roughness measurements because of manufacturing defects or equipment limitations, achieving 66.66% of the \(\:{R}_{a}\) and \(\:{W}_{a}\) inferences under 20% error or below, and a higher amount of 78.33% for \(\:{P}_{a}\) estimates. Gaussian filter implementation contributes especially to \(\:{R}_{a}\) predictions on different curvature types. Expected advantages include using the model to tailor surface roughness in applications where a smoother texture is preferred. The objective is to offer a novel approach integrating fabrication physics into a predictive surface model for curved SLA parts, which has the potential to become a design stage tool with enough fidelity to help with AM surface improvement.
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