Izenburua
Modeling and analysis of design parameters and interactions in 3D-printed components using response surface methodologyArgitalpen data
2025Beste erakundeak
JSS Academy of Technical Education (Bengaluru, India)Bertsioa
Bertsio argitaratuaDokumentu-mota
ArtikuluaHizkuntza
IngelesaEskubideak
©2006-2025 Asian Research Publishing Network (ARPN). All rights reserved.Sarbidea
Sarbide bahituaBahituraren amaiera data
2145-12-31Argitaratzailearen bertsioa
https://doi.org/10.59018/042557Non argitaratua
ARPN Journal of Engineering and Applied Sciences Vol. 20. N. 8. April 2025Argitaratzailea
ARPNGako-hitzak
Mathematical model3D printing
Surface
UNESCO Sailkapena
Ekoizpenaren antolaketaLaburpena
This study focuses on optimizing key design parameters in the Fused Deposition Modeling (FDM) process, a widely used method in 3D printing. Using response surface methodology (RSM), a regression model ... [+]
This study focuses on optimizing key design parameters in the Fused Deposition Modeling (FDM) process, a widely used method in 3D printing. Using response surface methodology (RSM), a regression model was developed to analyze the effects of six critical variables: temperature, nozzle movement speed, layer thickness, extrusion width, test tube positioning, and internal infill angle. Each variable was investigated at two levels to evaluate its influence on the mechanical properties of 3D-printed materials. A comprehensive set of 64 experimental tests was conducted to examine three key objective functions: Young's modulus, which measures material stiffness; breakage tension, indicative of the material's tensile strength; and breakage deformation, representing its flexibility under stress. The findings revealed that nozzle movement speed, temperature, and positioning were primary contributors to variations in Young’s modulus. For breakage tension, speed, layer thickness, and positioning emerged as significant factors. Similarly, nozzle speed, extrusion width, and positioning were found to strongly influence breakage deformation. Statistical analysis highlighted the significance of the process for optimizing Young’s modulus and breakage tension, with a p-value < 0.05 indicating strong evidence against the null hypothesis. However, the process's impact on breakage deformation was not statistically significant, suggesting the need for further investigation or potential inclusion of additional variables. These insights underline the criticality of parameter optimization in enhancing the structural integrity and mechanical performance of 3D-printed components. The study demonstrates the effectiveness of RSM in systematically identifying and quantifying interactions between variables, providing a pathway for improving FDM outputs. By fine-tuning the process parameters, manufacturers can achieve desired mechanical properties tailored to specific applications, advancing the potential of FDM in diverse industries. [-]


















