Version 1
: Received: 12 August 2024 / Approved: 13 August 2024 / Online: 13 August 2024 (08:49:09 CEST)
How to cite:
Ali, M. A.; Shimoda, M.; Naguib, M. Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability. Preprints2024, 2024080893. https://doi.org/10.20944/preprints202408.0893.v1
Ali, M. A.; Shimoda, M.; Naguib, M. Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability. Preprints 2024, 2024080893. https://doi.org/10.20944/preprints202408.0893.v1
Ali, M. A.; Shimoda, M.; Naguib, M. Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability. Preprints2024, 2024080893. https://doi.org/10.20944/preprints202408.0893.v1
APA Style
Ali, M. A., Shimoda, M., & Naguib, M. (2024). Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability. Preprints. https://doi.org/10.20944/preprints202408.0893.v1
Chicago/Turabian Style
Ali, M. A., Masatoshi Shimoda and Marc Naguib. 2024 "Optimizing Additive Manufacturing with Computer Vision to Enhance Material Efficiency and Structural Stability" Preprints. https://doi.org/10.20944/preprints202408.0893.v1
Abstract
This study presents a novel approach combining computer vision with topology optimization for additive manufacturing. Using specialized photogrammetry software, we capture high-resolution images of the design domain to create precise 3D models through detailed scanning. These models are converted into STL file format and remeshed using an adaptive algorithm within COMSOL 5.3 Multiphysics, managed by a custom MATLAB 2023. This integration allows optimal mesh resolution and accuracy in analyses. We applied this method to design a concrete pillar for 3D printing, aiming for a 75% volume reduction to enhance material efficiency and stability, crucial for extraterrestrial environments. The design, scanned with a 360-degree camera array, informed the MATLAB-based topology optimization process. Combining MATLAB’s optimization algorithms with COMSOL’s meshing and finite element solver solver, we explored material-efficient configurations. The results show significant volume reduction, particularly in the central design area, optimizing material use while maintaining structural stability. The optimization algorithm demonstrated rapid, stable convergence to near-optimal solutions within about 20 iterations, highlighting the method’s efficiency and robustness in complex design optimization.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
