Optimization of printing parameters in fused deposition modeling for improving part quality and process sustainability

Additive manufacturing (AM) technology is capable of efficiently building complex shapes when compared with traditional manufacturing methods. Fused deposition modeling (FDM) is one of the AM processes, and it produces a great variety of polymeric parts. Therefore, it is essential to determine the relationship that exists among its process parameters, productivity and sustainability, quality of the final piece, and its structural performance. This paper presents an experimental study centered on optimizing five responses associated with FDM: energy consumption of the 3D printer, processing time, part's dimensional accuracy, the quantity of material used to print the pieces, and mechanical strength of the specimens. The model material employed was acrylonitrile styrene acrylate. The effects of five key process parameters on the responses were studied using the Taguchi methodology and analysis of variance (ANOVA). These parameters were layer thickness, filling pattern, orientation angle, printing plane, and position of the piece on the build platform. A desirability analysis was employed to determine the set of process parameters that provided the best trade-off among all the considered variables. The results showed that the approach presented in this work allowed for simultaneous optimization of all the observed variables for the 3D printing process.