Senvol recently demonstrated a machine learning approach to material property allowables development that was shown to be more flexible, more cost-effective, more time-effective, and just as accurate as the conventional (in this case, CMH-17) approach to allowables development.
The work was done as part of a contract that Senvol had been awarded by America Makes, the national additive manufacturing institute, and funded by the U.S. Air Force, to apply its machine learning software, Senvol ML, to enable a path to rapid development of material property allowables for additive manufacturing (AM).
