Multi Objective Optimization of Fused Deposition Modeling Parameters for PC/ABS Blend Material Parts using GRA

Abstract

In this research, multi objective optimization is done on Fused Deposition Modeling (FDM) printing machine for Polycarbonate/Acrylonitrile Butadiene Styrene (PC/ABS) blend material parts. Reductions in part build time and material consumption without compromising its dimensional accuracy and mechanical properties are the major goals of many industries, because there is need to fulfil one part with multiple qualities. So that in this research, part printed without support structure by controlling five FDM process parameters at three levels such as layer thickness, raster width, extrusion temperature, bed temperature and printing speed by using Taguchi’s design of experiments method (L27 Orthogonal Array). This research can saves part build time, post processing time on support removal and damages occurred due to removal of support structure in part. For that, in this research effects of parameters are studied on surface roughness, build time, and flatness error of overhang structure of parts. Then Grey Relational Analysis (GRA) methodology is used for multi-objective optimization of FDM parameters to find best set of parameters for three responses. Analysis of Variance (ANOVA) is also used to find out significant parameters for multi responses and then confirmation test of experimental results also performed to verify the optimal settings of FDM parameters. The experimental result showed, layer thickness, raster width and part printing speed have the more significant effects on multiple performance characteristics.