Research on size optimization of 3D printed parts using Grey-Taguchi method

Abstract Fused deposition modeling (FDM) is one of the earliest developed 3D printing processes, which has the advantages of a clean processing environment, low overall manufacturing costs, and a variety of optional materials. However, it still has the disadvantages of low dimensional accuracy and poor surface quality of the molded workpiece. Therefore, how to solve this annoying problem has become an important research topic in the current industry-university-research fields. In this study, a square container with a bottom area of 48 mm×48 mm, a height of 30 mm, and a thin wall of 6 mm was used as the design object, and four controllable factors were adopted: layer thickness (A), nozzle temperature (B), printing speed (C), and forming path (D), combined with Grey- Taguchi’s experiments and calculations are carried out in order to achieve the purpose of optimizing the inner volume (IV) and inner diagonal length (IDL) of the square container (dual-objective quality characteristics). The experimental results show that within the selected printing parameter range, the optimized process parameter combination is layer thickness of 0.25 mm (A 3 ), nozzle temperature of 190 °C (B 1 ), printing speed of 50 mm/s (C 3 ) and the molding direction of the annular surface (D 2 ). Finally, use the GOM Inspect software (ATOS Q 3D scanner) and vernier caliper (VC) to compare the physical errors. According to the verification results, the errors of IV and IDL of the square container obtained by optimizing process parameters are 0.49% and 1.53%, and 3.76% and 6.33% respectively in GOM Inspect software and vernier caliper measurement. The results of this optimization process not only prove that the GOM Inspect software has a considerable degree of accuracy, but also can be used as a means to improve FDM multi-quality printing process optimization when combined with the Grey-Taguchi method.