Understanding the Influence of Process Parameters for Minimizing Defects in 3D Printed Parts Through Remote Monitoring

Abstract

Although fused deposition modeling (FDM) can fabricate complex functional components with desired structures, various defects emerge due to the diverse process parameters used in the process, which have a substantial impact on the quality and mechanical properties of the manufactured FDM parts. Therefore, the selection of suitable process parameters is an important design consideration for improving component quality. In the proposed work, the Taguchi optimization approach was used to optimize FDM process parameters to eliminate warpage defects in 3D printed parts. Infill pattern, infill density, raster angle, printing speed, layer height, build plate temperature, and extruder temperature were selected as the process parameters. Polylactic acid (PLA) was used to make the specimens using the Creality Ender-3 3D printer. The entire fabrication process was remotely monitored by interfacing the Raspberry Pi controller and camera with the OctoPrint platform. The influence of selected factors on warpage defect was evaluated and optimized using Analysis of Variance (ANOVA), the signal-to-noise ratio (S/N ratio), and a linear regression model. The results were later experimentally validated. The applicability of the optimized 3D printed part was verified by subjecting them to tensile tests.