<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>