Multi objective optimization of FDM Parameters Using Taguchi grey relation analysis for PLA specimen

Abstract

Polylactic acid (PLA), is a thermoplastic polyester that has many uses in both consumer goods and industrial settings. The mechanical characteristics of PLA specimens created using Fused deposition modeling (FDM), a cost-effective 3D printing process, including tensile strength, shore hardness, and dimensional precision, have been studied for use in specialised engineering applications. Layer height, infill density, and printing speed are the choices made for the specimen’s 3D printing. Design of experiments use Taguchi’s L9 orthogonal array. Using analysis of variance (ANOVA), designers can determine the relative importance and percentage contribution of each process parameter to each answer. Using Taguchi method while conducting test for individual responses result shows that for tensile strength printing speed is 70 mm/s, layer height 0.2mm and 40% infill density as optimum parameters while for the hardness it is 60 mm/s,0.3mm and 40%, and for the dimensional deviation found 60 mm,0.2 mm, 40% respectively. Proposed TGRA method found optimum parameter for all the responses in single test as printing speed is 70 mm/s, layer height 0.3 mm and 40% infill density also validated by conducting confirmation test. Finally, a superior specimen with all-around mechanical characteristics is fabricated using Taguchi based grey relational analysis (TGRA) as a multi-objective optimization technique