Multi-Objective Optimization of Process Parameters for Part Quality with Laser Powder Bed Fusion: A Heat Exchanger Application

The widespread adoption of additive manufacturing (AM) is hindered by the challenges in achieving consistent part quality across AM processes and equipment. Typical quality metrics such as geometric accuracy and porosity are affected by the microstructure of the fabricated parts, which are controlled by the AM's process parameters. This study presents an approach for optimizing the AM process parameters to achieve the desired part quality. The approach integrates design of experiments, AM process simulation, surrogate modeling, and multi-objective optimization. The applicability of the proposed approach is demonstrated through a laser powder bed fusion (LPBF) process. An application example for an air-to-water heat exchanger (HX) is used to demonstrate the effectiveness of the proposed approach. For this example, it is shown that with the optimized process parameters, the HX has about 19% better geometric accuracy and 0.2% porosity reduction when compared to baseline process parameters. This Technical Brief addresses a gap in the existing AM literature in which part quality, such as geometric accuracy and porosity, is multi-objectively optimized and demonstrated using a complex heat exchanger example.