Investigation of the mechanical properties, surface quality, and energy efficiency of a fused filament fabrication for PA6

Practitioners in the industry are developing predictive methods for assessing key parameters and responses of engineering materials. The aim of this research is to optimize the average surface roughness (R a), flexural strength (FS), tensile strength (TS), print time (T), and print energy consumption (E) of 3D printed Nylon 6 (PA6). Quantitative parameters for infill density (ID), layer thickness (LT), and print speed (PS) were selected. Employing the central component design (CCD)-response surface methodology (RSM) for investigational design, statistical analysis, and multi-objective optimization, a total of 20 samples were produced and analyzed to develop prediction models. The implication of the selected parameters was confirmed through variance analysis (ANOVA), and the models were validated using confirmatory trial tests. It was found that LT was essential in achieving appropriate R a and T values, while ID was a crucial factor in obtaining the necessary mechanical properties. RSM optimization led to an FS of 70.8 MPa, TS of 40.8 MPa, lowest T of 53 min, lowest possible R a of 8.30 μm, and 0.203 kW·h "E"at ID = 84%, LT = 0.21 mm, and PS = 75 mm·s-1. The study also revealed weak bond strength between layers and layers debonding after bending tests, as shown in SEM micrographs. The PA6 material exhibited flexibility during tensile testing, going into plasticity before breaking. The created numerically optimized model is anticipated to benefit manufacturers and practitioners in predicting the required surface quality for various factors before conducting experiments, ultimately improving 3D printing (3DP) processes and outcomes. Despite limitations such as limited parameter selection, small sample size, and material-specific focus, this research presents valuable insights for the 3DP industry.