This project was funded through an ARM Institute Directed Project Call with the AF Mantech and Air Force Rapid Sustainment Office. Directed Projects provide another method for the ARM Institute to fund projects, enable ARM Institute Members to build relationships with the Department of Defense (DoD), and facilitate collaboration between the DoD and non-traditional collaborators. These projects also outline use cases for industry, creating dual impact.
Objective & Technical Approach
Defastening is a complex point process that has strict accuracy requirements while required flexibility. Current systems for defastening are too slow and process failures are too high on valuable assets. The DoD sustainment community requires better and faster detection and classification of point like objects, as demonstrated on fasteners.
This project aims to configure artificial intelligence (AI) for fastener detection and classification to reduce the fastener removal time cycle.
This project seeks to reduce the time needed for fastener removal cycles, applicable both to DoD and industry. The outputs of this project also have the potential to be transferrable to other markets and processes for detection and classification of point like objects: FOD detection, defect classification, and similar tasks. This particularly impactful to markets where skilled labor is scarce, high mix throughput requires operator vigilance, manual adjustments, and/or engineering support