Scientists have proposed a technology based on deep machine learning that greatly facilitates the detection of defects in 3D printed products. To create their model, the researchers used computer simulations to create tens of thousands of artificial defects.
Each such defect had a different size, shape, and location; This allowed the deep learning model to “learn” a wide range of possible damage and learn to separate defective parts from good ones.
The algorithm was then tested on real parts, some of which contained defects. The algorithm successfully detected hundreds of defects it had never seen before in real products.
Source: Ferra
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