Investigation on dimensional accuracy optimization of FDM printed UCFL bearing using response surface methodology

Abstract

Additive manufacturing (AM) is a fabrication technology that enables flexibility in design and the manufacture of parts consisting of multiple materials. In this study, we focus on the dimensional accuracy optimization of the UCFL series roller bearing fabricated using the Fused Deposition Modeling (FDM). Printing parameters (layer thickness, infill density, and wall thickness) and their interactions were examined. The fabrication process was carried out by determining three levels for each parameter. Box-Behnken Design (BBD), which has three independent printing parameters at three levels, was used and fifteen pieces were produced using Akrilonitril Bütadien Stiren (ABS) material with a 3D printer. It has been determined that printing parameters affect the dimensional accuracy of the bearing, extrusion time and the amount of material consumed during the fabrication phase. ANOVA was performed to observe the effect of printing parameters on dimensional accuracy and extrusion time. Response Surface Methodology (RSM) analysis was used to optimize AM fabrication processes. Additionally, regression analysis was applied to mathematically model the dimensional accuracy values obtained as a result of experimental measurements. When the experimental results were examined, the best dimensional accuracy was determined as 35.9981mm using the combination of 150μm layer thickness, 50% infill density, and 1mm wall thickness.