Multi-Objective Optimization for Additive Manufacturing Process using Monarch Butterfly Optimization

Abstract

This study investigates the influence of key Fused Deposition Modeling (FDM) process parameters i.e. nozzle temperature, part orientation, and layer thickness—on the mechanical properties and surface finish of 3D printed components using a Face-Centered Central Composite Design (FCCCD) approach. Experimental results showed that higher nozzle temperatures (250 °C), orientations at 0° or 90°, and thicker layers (0.35 mm) improved tensile and flexural strengths due to enhanced interlayer bonding. Conversely, a finer layer thickness (0.15 mm) yielded lower surface roughness but reduced mechanical strength. To address this trade-off, the Monarch Butterfly Optimization (MBO) algorithm was applied for multi- objective optimization, identifying 250 °C, 90°, and 0.15 mm as the optimal settings. This combination effectively balances strength and surface quality. While optimization results closely matched experimental data, the surface roughness model suggests potential for further refinement. The study demonstrates the effectiveness of integrating experimental design with nature-inspired optimization, offering a foundation for future work involving Pareto-based and non-linear modeling approaches.