Achieving Optimal Injection Molding Parameters to Minimize Both Shrinkage and Surface Roughness Through a Multi-Objective Optimization Approach

This study developed a multi-objective optimization procedure aimed at minimizing surface roughness and volumetric shrinkage in injection-molded products. Surrogate models for both outputs were constructed using the Kriging technique, based on experimental data and seven input parameters: packing pressure, mold temperature, cooling time, injection speed, injection pressure, melt temperature, and packing time. A multi-objective optimization problem was formulated and solved using the pattern search algorithm, generating a Pareto front that highlights the trade-off between the two objectives. This Pareto front was further analyzed to determine three optimal parameter sets. The first point minimizes volumetric shrinkage at 1.9314 mm3 but results in the highest surface roughness of 0.55956 µm. In contrast, the second point yields the lowest surface roughness of 0.20557 µm but the highest volumetric shrinkage of 3.9286 mm3. The third point offers the best compromise between the two objectives, with a volumetric shrinkage of 2.2348 mm3 and surface roughness of 0.28246 µm. The proposed approach provides an experimentally validated tool for plastic engineers, enabling informed parameter adjustments to achieve optimal trade-offs in surface quality and dimensional stability within practical manufacturing constraints.