The US Department of Defense is partnering with industry and academia on an initiative to develop a machine learning prediction tool that can optimize a tool path of Ambient Reactive Extrusion (ARE) material, which will be capable of minimizing deformation, improving dimensional stability, and enhancing overall quality of printed parts.

The overall goal is to solve the discrepancy between idealized paths generated by slicing software and the actual bead formation during printing to eliminate dimensional defects and weaker mechanical properties. The specific approach must encompass real-time data integration, development of an algorithm for dynamic path optimization, and the enablement of iterative learning.

If you feel your organization has the technical capabilities and would like to be considered for this project, please complete the form below and upload your organization’s technical capabilities statement.

Interested Submissions Due by 9-10-24.

We encourage participation of Disadvantaged Business Enterprises (DBEs), including Minority Business Enterprises (MBEs) and Women’s Business Enterprises (WBEs).