Senvol says that its Senvol ML machine learning software for additive manufacturing (AM) is currently being used to help with a US Air Force program researching multi-laser AM.
The project, a collaboration between the US Air Force Research Laboratory (AFRL), Air Force Life Cycle Management Center (AFLCMC), and University of Dayton Research Institute (UDRI), uses an EOS M400-4 quad laser powder bed fusion machine. It will focus on ‘developing baseline mechanical properties and design allowables, and ultimately making demonstration builds of heat exchangers and hypersonics-relevant parts,’ a press release said.
‘AM has recently demonstrated the ability to rapidly deliver complex geometries and production quality parts that are able to enhance the capabilities of DoD weapons systems,’ said program manager at UDRI, Jessica Orr. ‘A major challenge facing the use of AM for producing DoD relevant end-use parts is that the number of available large scale printers is likely to be limited for the next 5-10 years. In this collaborative program we are developing and demonstrating methodology to use a new multi-laser AM printer to produce airworthy, end-use parts.’
‘In addition to helping to develop baseline mechanical properties and design allowables, the software will analyze data to evaluate laser-to-laser consistency, optimize bulk scan settings, identify preferred overlap patterns and parameters, and confirm uniformity over the entire build plate,’ added Senvol president Annie Wang.
This story uses material from Senvol, with editorial changes made by Materials Today. The views expressed in this article do not necessarily represent those of Elsevier.
