Establishing a robust processing window is critical for laser powder bed fusion (LPBF) of advanced materials such as intermetallic alloys. This study presents a unified and efficient framework for rapid optimization of LPBF parameters, integrating single-track melt pool characterization, response surface methodology (RSM), and analysis of variance (ANOVA). The developed regression model accurately correlates laser power, scanning speed, and hatch spacing with relative density, enabling the prediction and validation of optimal parameters. Using this framework, five distinct processing schemes were developed, all producing Ti-22Al-25Nb specimens with near-full density (≥99.8%). These schemes delivered a range of mechanical properties: while some achieved high ultimate tensile strengths up to 1054 ± 5.33 MPa with moderate ductility (12.5 ± 1.07%), one scheme (LD25-t10) attained an exceptional balance of strength and ductility (UTS: 975 ± 12.08 MPa, YS: 899 ± 18.08 MPa, elongation: 25.4 ± 1.80%). Microstructural analysis revealed that a smaller laser spot size (at constant layer thickness) refines cellular structure and nano-precipitates via higher cooling rates, enhancing strength but compromising plasticity. Conversely, a larger spot coarsens microstructure, improving plasticity. At a constant spot size, increasing layer thickness strengthens the alloy through grain refinement but drastically reduces ductility due to process-induced defects, leading to a high-strength butbrittle result. These results highlight the complex parameter coupling in LPBF. The proposed framework provides an effective methodology for qualifying and optimizing the LPBF process for high-integrity component manufacturing.
Li et al. (Mon,) studied this question.