Metal Additive Manufacturing (AM) has the potential to reduce DoD sustainment costs and delays through on demand part production. However, at present metal AM build times are too long, often require post-processing treatments, and produce parts of inconsistent quality or with defects. There are multiple factors inherent to LPBF that contribute to the variability of the build and cause defects. This is particularly true in the dynamic environment of a Laser Powder Bed Fusion (LPBF) system. The DoD requires a modular intelligent multi-laser LPBF solution that can monitor and control the process to 1) Mitigate the static variability of the physical properties (e.g. thermal conductivity) from point to point in the powder bed; 2) Reduce the dynamic variability of the powder bed created by the process itself (e.g. spatter); 3) Alleviate the thermal gradients created when metal is rapidly heated then cools as is the case in single laser LPBF systems; and 4) Scale to produce more and bigger parts in less time. To meet these requirements, R3 Digital Sciences (R3-DS) working with the University of Dayton Research Institute (UDRI) will extend the Open Intelligent Additive Manufacturing (Open-IAM) system that we are currently developing from a two-laser system to a modular three-laser system.
