Subramonian, Sivarao and Kadirgama, Kumaran and Mahdi Al-Obaidi, Abdulkareem Sh. and Mohd Shukor, Mohd Salleh and Vatesh, Umesh Kumar and Pujari, Satish and Rao, Dharsyanth and Ramasamy, Devarajan (2023) Artificial Neural Network Performance Modeling and Evaluation of Additive Manufacturing 3D Printed Parts. Engineering, Technology & Applied Science Research, 13 (5). pp. 11677-11684. ISSN 1792-8036. (Published)
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Abstract
This research article presents a comprehensive study on the performance modeling of 3D printed parts using Artificial Neural Networks (ANNs). The aim of this study is to optimize the mechanical properties of 3D printed components through accurate prediction and analysis. The study focuses on the widely employed Fused Deposition Modeling (FDM) technique. The ANN model is trained and validated using experimental data, incorporating input parameters such as temperature, speed, infill direction, and layer thickness to predict mechanical properties including yield stress, Young's modulus, ultimate tensile strength, flexural strength, and elongation at fracture. The results demonstrate the effectiveness of the ANN model with an average error below 10%. The study also reveals the significant impact of process parameters on the mechanical properties of 3D printed parts and highlights the potential for optimizing these parameters to enhance the performance of printed components. The findings of this research contribute to the field of additive manufacturing by providing valuable insights into the optimization of 3D printing processes and facilitating the development of high-performance 3D printed components.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | 3D printing; Artificial Neural Networks (ANNs); predictive modeling; Fused Deposition Modeling (FDM); mechanical properties |
| Subjects: | T Technology > TJ Mechanical engineering and machinery |
| Faculty/Division: | Faculty of Mechanical and Automotive Engineering Technology |
| Depositing User: | Miss Amelia Binti Hasan |
| Date Deposited: | 22 Mar 2024 03:48 |
| Last Modified: | 22 Mar 2024 03:48 |
| URI: | http://umpir.ump.edu.my/id/eprint/40734 |
| Download Statistic: | View Download Statistics |
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