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  • Failure to detect edge cracks, oil stains, insufficient feed, and sunken oxidation on sheet metal strips

  • Failure to detect foreign objects that have fallen into products


  • Data collection and analysis with Dataguess Inspector

  • Labeling the issues that will be captured in the resulting dataset

  • Enrichment of data

  • Artificial intelligence model improvements, tests and integrations

  • Deployment of the trained artificial intelligence model and transition to a live environment


  • Notifying the operator of cases caught as NG (Not Good) via siren, buzzer, or monitor

  • Performing signaling, automation and integration operations for sending the products detected as NG (Not Good) to the reject line

  • Stopping the production line at the moment of incident capture by sending signals to PLCs

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