Optimizing Fused Deposition Modeling Process Parameters for Enhanced Build Time and Mechanical Strength

Abstract

<div class="section abstract"><div class="htmlview paragraph">In this study, we investigate the optimization of additive manufacturing (AM) parameters using a bi-objective optimization approach through the non-dominated sorting genetic algorithm II (NSGA-II). The objectives are to minimize build time and maximize mechanical strength. Experimental evaluations are conducted on various process parameters, including layer thickness, build orientation, and infill density, with a focus on their impact on build time and mechanical properties. Optimal parameter combinations, such as the lowest layer thickness, vertical build orientation, and relatively low fill density, are identified for maximizing tensile strength while minimizing build time. The consistency between experimental results and those obtained through NSGA-II validation validates the reliability of the optimization approach. Overall, this study contributes to the advancement of AM by providing insights into efficient parameter optimization strategies for enhancing both efficiency and performance in extrusion-based processes.</div></div>