[PDF][PDF] Process parameter optimization in fused deposition modeling (FDM) using response surface methodology (RSM)

MS Mustafa, MQ Zafar, MA Muneer, M Arif, FA Siddiqui… - Res. Sq, 2020 - academia.edu
Res. Sq, 2020academia.edu
Abstract Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing
process to produce complex 3D structures and it is typically used in the fabrication of
biodegradable materials eg PLA/PHA for biomedical applications. However, FDM as a
fabrication process for such material needs to be optimized to enhance mechanical
properties. In this study, dogbone and notched samples are printed with the FDM process to
determine optimum values of printing parameters for superior mechanical properties. The …
Abstract
Fused Deposition Modeling (FDM) is a widely adopted additive manufacturing process to produce complex 3D structures and it is typically used in the fabrication of biodegradable materials eg PLA/PHA for biomedical applications. However, FDM as a fabrication process for such material needs to be optimized to enhance mechanical properties. In this study, dogbone and notched samples are printed with the FDM process to determine optimum values of printing parameters for superior mechanical properties. The effect of layer thickness, in ll density, and print bed temperature on mechanical properties is investigated by applying response surface methodology (RSM). Optimum printing parameters are identi ed for tensile and impact strength and an empirical relation has been formulated with response surface methodology (RSM). Furthermore, the analysis of variance (ANOVA) was performed on the experimental results to determine the in uence of the process parameters and their interactions. ANOVA results demonstrate that 44.7% in ll density, 0.44 mm layer thickness, and 20C printing temperatures are the optimum values of printing parameters owing to improved tensile and impact strength respectively. The experimental results were found in strong agreement with the predicted theoretical results.
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