Mostafa A. Abdullah; Tahseen F. Abbas
Abstract
Complex geometry components can be produced using FDM-based additive manufacturing (AM). In this study, the compressive and tensile strength were investigated, considering variations ...
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Complex geometry components can be produced using FDM-based additive manufacturing (AM). In this study, the compressive and tensile strength were investigated, considering variations in layer thickness (0.2, 0.25, and 0.3 mm), density (40%, 60%, and 80%), and infill pattern (tri-hexagon, zig-zag, and gyroid). The experiment was designed using the Taguchi technique and carried out on a commercial FDM 3D printer, involving nine specimens with different processing settings. The compression standard ASTM D695 and tension standard ASTM D638-02a were used for evaluation. The results indicated that infill density significantly impacted compressive and tensile strength, contributing to 65% and 60% of the variations. Based on the S/N ratio analysis, the optimal parameters for achieving high compressive and tensile strength were 80% infill density, a Gyroid infill pattern, and a layer thickness of 0.3 mm. With these settings, the maximum compression strength reached 45.23 MPa, and the maximum tensile strength was 44.03 MPa. Regression prediction modeling proved to be a powerful tool for predicting the compression and tensile strengths of PLA samples and optimizing the 3D printing process. Accurate and reliable predictions can be achieved by carefully selecting relevant features, preprocessing the data, training, and evaluating the model. These predictions can greatly assist in process design and manufacturing, with a percentage error of approximately 2.79% for compression strength and 3.35% for tensile strength.
