Identifying flaws in manufacturing of composites
Description
Inspection for manufacturing flaws makes up 40% of fabrication time so if that time could be reduced it would have a significant impact on overall manufacturing time. That doesn’t even take into account the benefits of finding flaws that were previously undetectable by the current technique of visual inspection.
Detailed example
A U-Net was trained to ID flaws in those images.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Inspection for manufacturing flaws makes up 40% of fabrication time so if that time could be reduced it would have a significant impact on overall manufacturing time. That doesn’t even take into account the benefits of finding flaws that were previously undetectable by the current technique of visual inspection.
Controls / human review
ATO: Not reported; PIA: Not published