Surface Texture Characterization and Parameter Optimization of Fused Deposition Modelling Process
Abstract
Fused Deposition Modeling (FDM) is one of the additive manufacturing (AM) methods, widely used for manufacturing prototypes, models and functional thermoplastic parts as final product. Although FDM technology provides opportunity for manufacturing complex geometries, surface quality of the products cannot reach the required value yet. For this reason post processing operations which are time consuming and over costing, are applied to the finished parts. Alternatively, optimization of the FDM process parameters is another solution which is more economical way for improving surface quality of the printed parts. The aim of the study is to optimize the FDM process parameters such as shell number, infill percentage, infill geometry and layer thickness, for improving surface quality of the Polylactic Acid (PLA) parts. L9 (34) standard Taguchi experimental design is applied for manufacturing of the samples. The manufactured surfaces are inspected by mechanical profilometer for obtaining 2D surface profiles and the results were transformed in to signal-to-noise ratio as a quality characteristic to measure the deviation from desired values. Analysis of variance (ANOVA) was used for determining significance of the testing parameters.
Keywords
Fused deposition modeling (FDM), 3D printing, surface roughness, parameter optimization, experimental design
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