Enhancing Mechanical Properties of 3D-Printed PLAs via Optimization Process and Statistical Modeling

This paper investigates the optimization of 3D printing by 1.75 mm filaments of poly-lactic acid (PLA) materials. The samples are printed separately and glued together to join the tensile device for the failure load and checking the surface roughness. The printing method in this research is Fused Deposition Modeling (FDM), in which the parameters of Infill Percentage (IP), Extruder Temperature (ET), and Layer Thickness (LT) are considered variable parameters for the 3D printer, and according to the Design of Experiments (DOE), a total of 20 experiments are designed. The parametric range is considered to be 15-55% for IP, 190-250 degrees C for ET, and 0.15-0.35 mm for LT. The optimization model is conducted according to the Response Surface Method (RSM), in which the ANOVA and plot tables are examined. Moreover, the samples' maximum failure load, weight, fabrication time, and surface roughness are considered output responses. Statistical modeling shows that by increasing the IP and setting the ET at 220 degrees C, the failure load of the samples increases, and the maximum failure load reaches 1218 N. The weight and fabrication time of the specimen are optimized at the same time to achieve maximum failure load with less surface roughness. By comparing the predicted and actual output for the optimum samples, the percentage error for all results is less than 5%. The developed optimization method is revealed to be accurate and reliable for FDM 3D printing of PLAs.