Sustainable multi-objective optimization of fused deposition modelling parameters using response surface methodology and grey relational analysis

Abstract Fused Deposition Modeling FDM is one of the most widely used additive manufacturing techniques due to its simplicity, cost effectiveness, and design flexibility. However, the quality and energy efficiency of FDM process remain challenges that affect the sustainability of this technology. This research aims to optimize FDM process parameters by analyzing the combined influence of four input parameters (extrusion temperature, infill overlap percentage, layer height, and printing speed) on three performance measures: surface roughness, energy consumption, and printing time. A Response Surface Methodology RSM approach based on Box-Benham design was adopted to design the experiments. Furthermore, desirability analysis and Grey Relational Analysis GRA were used to perform multi-objective optimization. Based on desirability analysis, the optimum values of surface roughness, energy consumption, and printing time were 4.5626 μm, 0.0223 kWh, and 13.8929 min respectively, at an extrusion temperature of 216.1616 °C, an infill overlap percentage of 0.20, a layer height of 0.1422 mm, and a printing speed of 180 mm s −1 . The optimum Grey relational Grade value derived from GRA was 0.7343 at an extrusion temperature of 210 °C, an infill overlap percentage of 0.20, a layer height of 0.12 mm, and a printing speed of 240 mm s −1 . A comparison between the RSM desirability results and the GRA results indicated that GRA achieved superior performance with lower predictive error of 3.7% compared to the overall average error of 17.29% for RSM