Experimental investigation of influence of process parameters on mechanical properties of carbon fibre PLA 3D printed samples

Fused Deposition Modeling (FDM) has become a popularly adopted additive manufacturing technique for fabricating customized polymer and fiber-reinforced polymer parts with minimal wastage of material, inexpensively and rapidly. However, the mechanical behavior displayed by the 3D-printed short carbon fibre-reinforced polymers is highly dependent on process parameters. The aim of this work is to improve tensile strength (TS), flexural strength (FS), and Shore D hardness (SDH), of chopped carbon fibre (CF)-reinforced polylactic acid (PLA). Multi-objective optimization was carried out to enhance the overall performance of the specimens using grey relational analysis (GRA). Taguchi L27 orthogonal array was used to optimize a number of experiments for six input factors: nozzle temperature, layer height, bed temperature, printing speed, raster angle, and raster width, each at three different levels. The percentage significance of each parameter's effect was determined using analysis of variance (ANOVA). The results showed that the optimized parameters obtained for the three output responses differed. Proper combination of the optimized parameters plays a significant role in improving the mechanical properties. Tensile strength was mainly influenced by raster angle, printing speed, layer height, and nozzle temperature. While, the most effective parameters for flexural strength were layer height, nozzle temperature, and bed temperature. Shore D hardness was significantly affected by nozzle temperature, printing speed, and layer height. The following values were identified as the optimum parameters for multi-objective optimization: 225 degrees C nozzle temperature, 0.18 mm layer height, 70 degrees C bed temperature, 55 mm/s printing speed, 0 degrees raster angle, and 0.5 mm raster width.