How do we best use digital tools (AI, cloud computing, and physical/digital automation) to augment technicians/designers/planners in a world of ever growing complexity in manufacturing?  The Digital Manufacturing Research Team within AFRL applies the mantra of “Teaching tools to be teammates” across a range of DAF-relevant processes including additive manufacturing and robotics.  Areas of interest include capture of human expertise in digital systems, autonomous development of artificial expertise, accessible software for accelerating data-centric manufacturing, and best practices for robust application of AI to manufacturing.  Consequently, we build novel AI models on data collected with in-house automation and seek to make the models part of closed-loops manufacturing systems to “prove” their usefulness.

This work is highly multidisciplinary.  Our team works together on focused, small-scale projects to highlight key challenges in digital manufacturing technology.  We are not the only researchers working on related technologies.  Collaboration with industry, other national labs, and academia is highly encouraged.  Additionally, digital technologies are advancing at a pace where “learning as you go” is expected.

Relevant Reference:

Johnson, M.V., Garanger, K., Hardin, J.O., Berrigan, J.D., Feron, E. and Kalidindi, S.R., 2021. A generalizable artificial intelligence tool for identification and correction of self-supporting structures in additive manufacturing processes. Additive Manufacturing, 46, p.102191.

key words

artificial intelligence; machine learning; automation; control; explainable AI; additive manufacturing; 3D printing

Citizenship:  Open to U.S. citizens

Level:  Open to Postdoctoral and Senior applicants