APPLICATION OF TAGUCHI METHOD TO OPTIMIZE FUSED DEPOSITION MODELING PROCESS PARAMETERS FOR SURFACE ROUGHNESS

Abstract

Surface quality is one of the limiting aspects of additive manufacturing (AM). This paper presents the findings from a study to optimize Fused Deposition Modeling (FDM) process parameters to improve the surface roughness of the printed test specimen. Taguchi 3⁴ and L9 orthogonal array were used to design the experiment. Samples models of the same size were fabricated with an open source FDM printer using acrylonitrile butadiene styrene (ABS) material and were examined to see the structural differences. Taguchi method S/N ratio and means analysis was used to find the optimum process parameter for surface roughness. The results indicate that flow rate is the most influential process parameter towards better surface roughness, followed by layer height, printing temperature and print speed. The surface roughness of printed test specimen was found to be rougher with the increase in levels of flow rate. The flow rate is responsible for the unevenly aligned section of the deposited filament. It was discovered that the optimal proses parameter levels for surface roughness by the CR-10S Pro FDM machine are 0.1 mm of layer height, 90% of flow rate, 230°C of printing temperature, and 35mm/s of print speed. Thus, Taguchi method has proven to be a useful approach for optimizing parameters to improve the surface roughness of printed parts.