FDM-3D printing parameter optimization using taguchi approach on surface roughness of thermoplastic polyurethane parts

FDM (Fused Deposition Modelling) 3D Printing requires the special review of process parameters with taguchi optimization for optimal print surface finish. Several previous studies have not yet investigated the parameters of the FDM 3D printing process for the surface roughness of TPU prints. Even though surface roughness is an important point for FDM-3D Printing print quality. The aim of this study is investigate the optimum 3D printing process parameters on the surface roughness of TPU (Thermoplastic Polyurethane). The input variables for printing TPU in this study are flow rate, layer thickness, nozzle temperature, print speed, overlap and fan speed. The output variable of the process parameters is the surface roughness value. The L-27 fractional Taguchi method was used for the optimization analysis. The optimal parameter combination is selected based on the signal-to-noise (S/N) ratio and Analysis of Variance (ANOVA). In addition, linear regression analysis and statistics are used to identify input variables and output variables. The results of our study explain that the surface roughness of the print is affected by the layer thickness. Based on parameter interactions, layer thickness has a significant influence with a contribution of 65.11%. Finally, the confirmation test shows that there is a good agreement between the experimental data and the statistics. The findings of this study suggest that layer thickness is an optimal process parameter for the surface roughness of 3D printing TPU fabrication. Process parameter optimization investigation of TPU printed surface roughness is a novelty study to improve the print quality of FDM 3D printing in the industrial.