Use of Statistical Methods to Model Machine Parameters Affecting 3D Printed Cotton/PLA Fabrics

This research work uses statistical methods to determine the effect of 3D printing machine parameters on the mechanical properties of cotton fabrics combined with polylactic acid (PLA) using the 3D printing technique. PLA was printed on a cotton fabric using an a 3D printer. The effect of extrusion temperature, printing speed, fill density and model height on adhesion force before after washing, adhesion force after washing and tensile strength were investigated using a central composite rotatable design and regression analysis. The experimental data was used to develop regression models to predict the properties of the cotton/PLA structures. The model for adhesion force before washing yielded a coefficient of determination (R²) value of 0.75 and an optimum adhesion force of 50.06 N/cm. The model for adhesion force had an R² value of 0.84, an optimum adhesion force of 42.91 N/cm and showed that adhesion force reduced after washing. Adhesion forces before and after washing, were both positively correlated to extrusion temperature. However, they reduced with an increase in printing speed and model height. Tensile strength yielded an R² value of 0.94 and an optimum tensile strength of 346.22 MPa. From the results of this study it was concluded that 3D printing parameters have an effect on the properties of the structures.