Optimization of 3D printed polylactic acid structures with different infill patterns using Taguchi-grey relational analysis

Abstract

In several engineering applications, the demand for robust yet lightweight materials have exponentially increased. Additive Manufacturing and 3D printing technology have the scope to make this possible at a fraction of the cost compared to traditional manufacturing techniques. Majority of the previous studies are focused mainly towards the printing parameters namely build orientation, infill density, and layer height etc. Also, most studies considered strength as an output response. However, when it comes to the cellular geometry and nozzle diameter, these parameters were found limited in the literature. Similarly, the combination of output responses such as stiffness, strength, toughness and resilience are found rarely in the previous studies. The current study is designed to capture the said gap in the literature with focus on cell geometry, nozzle diameter and strain rate by using the Taguchi design of experimentation and Grey Relational Analysis. Tensile test results performed on six different patterned samples under ASTM D638 standard suggest that square patterned samples perform the best under tension and retain more mechanical strength than the other five patterns. The grey relational analysis indicates that highest grey relational grade (GRG) was achieved for the larger nozzle diameter of 0.8 mm, strain rate of 5 mm per minute and square cellular geometry. It has been observed that highest contributing factor was nozzle diameter (48.99%), whereas cellular geometry was ranked second with (40.78%) as obtained from analysis of variance (ANOVA). The grey relational analysis simplified the complex 3D printing process optimization.