57533.rar Apr 2026

The researchers compared several algorithms to determine which could best predict the strength of the printed parts: . Artificial Neural Networks (ANN) . Main Findings

The research focuses on predicting the of 3D-printed Polylactic Acid (PLA) components under various conditions. This is critical for industrial applications where the strength of a part can change based on its internal structure and how it is printed. Key Technical Variables 57533.rar

The study utilized Copula-based data augmentation to generate 20,000 synthetic data points to improve the accuracy of their machine learning models. Machine Learning Models Used 57533.rar

Lattice infill patterns were found to underperform compared to other structures in terms of tensile strength. 57533.rar