Spatter-based in situ monitoring of process variability in PBF-LB/M with application to NiTi shape memory alloy

Abstract In situ monitoring in metal laser powder bed fusion (PBF-LB/M) is increasingly used not only for anomaly detection but also for material development and process optimization. Among available process signatures, spatter ejections have been widely studied, though mainly in relation to process parameters and energy density. This work investigates how spatter dynamics can capture additional and often overlooked sources of variability, including spatial variations within layers and geometry-induced changes across layers. Detecting such multi-scale variations is essential to ensure consistent part quality, particularly for materials with narrow process windows. The proposed approach is applied to the PBF-LB/M of NiTi, a crack-prone alloy with pseudo-elastic and shape memory properties and high sensitivity to process instabilities. A case study on structural NiTi dampers shows that spatter descriptors effectively capture process variations induced by powder spreading irregularities and evolving geometry along the build direction. The results highlight the potential of spatter-based monitoring to support the early identification of process deviations and defect-prone conditions in process-sensitive materials.