Accelerating Process Development for 3D Printing of New Metal Alloys
This addresses the need for efficient process development in 3D printing of new metal alloys, which is incremental but practical for manufacturing industries.
The paper tackles the problem of uncertainty and variability in 3D printed metal quality by developing a method using video vision transformers and high-speed imaging to create in situ process maps, enabling efficient defect quantification and demonstrating generalizability across different alloys.
Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently produce acceptable printing quality. Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts. On the other hand, in situ approaches are limited because their observable features are limited and they require complex high-cost setups to obtain temperature measurements to boost accuracy. Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging. Our approach can be used in existing commercial machines and can provide in situ process maps for efficient defect and variability quantification. The generalizability of the approach is demonstrated by performing cross-dataset evaluations on alloys with different compositions and intrinsic thermofluid properties.