Investigating the Machining Quality of Additively Manufactured Composite: Multi-Response Modeling and Evolutionary Optimization

model. To further evaluate process performance, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) was employed to determine the Pareto-optimal solutions that simultaneously minimize the dimensional error and the surface roughness. It was found that the optimal solutions are generated with a cutting speed between 120 m/min and 180 m/min, depth of cut below 0.52 mm and feed ranging from 0.05 mm/rev to 0.10 mm/rev. Finally, additional validation experiments confirmed the reliability of the proposed models, yielding mean absolute prediction errors between the measured and estimated values equal to 3% for the dimensional error and 4.8% for the surface roughness.