Additive manufacturing of component based on polyethylene terephthalate glycol: multi-response optimization using grey relational analysis

Abstract This work details the experimental investigations of additive manufacturing (AM) of components based on Polyethylene Terephthalate Glycol (PETG) and subsequent multi-response optimization through grey relational analysis (GRA). The effect of layer thickness (LT), infill density (ID), and raster angle (RA) on the hardness and compressive strength of the PETG component was assessed. The GRA revealed that the optimal values of the input parameters for the best combination of hardness and compressive strength are LT—0.1 mm, ID—1, and RA—90°. The values of compressive strength and hardness at the optimal condition were 34.89 MPa and 84.97, respectively. The high F-value for ID (379.18) obtained from the variance analysis indicates that the ID has the most significant influence on the responses. The R-sq value for grey relational grade (GRG) being 97.51% signifies the fitness of the regression model. The delamination and crushing of layers were observed in the optical micrographs of the tested specimens.