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The introduction of Deep Learning within the Machine Vision Industry has allowed significantly more vision applications to be successfully deployed than in the past. Its real strength comes from its ability to handle more variability from part to part that is common in manufacturing but has been an issue for traditional machine vision. Its ability to not only identify defects much more reliably but just as important, the ability to reduce false rejects caused by slight part variation. This presentation will show a real-world application that were considered extremely challenging, if not impossible with traditional vision applications