Application of Image Recognition Technology in 3D Printing Material Selection

• Published in: 2024 International Conference on Electrical Drives, Power Electronics & Engineering (EDPEE) pp. 557 - 560
• Main Author: Xu, Xinkun
• Format: Conference Proceeding
• Language: English
• Published: IEEE 27.02.2024
• Subjects: 3D printing technology; Data analysis; Data visualization; Image recognition; image recognition technology; Manufacturing processes; material selection; printing efficiency; Productivity; real-time optimization; Real-time systems; Three-dimensional printing
• DOI: 10.1109/EDPEE61724.2024.00110

3D printing technology, as a disruptive manufacturing technology, brings new possibilities to manufacturing. Material selection in 3D printing is a key factor in determining the performance and quality of the final product. This study is dedicated to exploring the application of image recognition technology in 3D printing material selection, aiming to improve the printing efficiency and material performance through in-depth study of material recognition, image classification and real-time printing parameter optimization. First, the basic principles and development history of 3D printing technology are outlined, emphasizing the critical role of material selection in the whole manufacturing process. Then, the application of image recognition technology in 3D printing is discussed in detail, including the improvement of material identification accuracy and optimization of printing parameters. The successful cases of image recognition technology in actual production are demonstrated through an example study, and its positive effects are verified through data analysis. The experimental results show that after the introduction of image recognition technology, the material identification accuracy increased from 82% to 99.9%, the scrap rate was reduced from 15% to 0.02%, and the printing efficiency was improved by 62.5%. These data clearly demonstrate the positive impact of image recognition technology on material selection in 3D printing, which not only improves productivity but also optimizes the quality of the final product. By discussing the technical challenges and future directions, it is expected that this study provides useful insights for advancing the application of image recognition technology in 3D printing and provides a useful guide for future research and practice.