TAMPER-EVIDENT PACKAGING: A CASE STUDY

INDUSTRY CHALLENGE

DEEP LEARNING AND MACHINE VISION FOIL INSPECTION SOLUTION

This application shows how a hybrid inspection system may be developed and deployed successfully in the field, utilizing analytical machine vision and deep learning technologies. To achieve high detection accuracy for defect features (clearly or poorly defined), the system’s strengths are effectively combined. One such system for diverse products was effectively deployed to numerous places. The technology maintained a low false failure rate while accurately detecting significant seal flaws. Finding variations in cap torque based on seal integrity and completeness was a crucial area for process optimization. The cap torque was changed to achieve tighter seals and decrease product rejects using the continuing process data. 

Liquid on the cap and bottle, which could cause issues with later operations like labeling, was also discovered using thermal imaging. As a result, the overall quality improved. Additionally, the system effectively recognized even uncommon flaws, like fractured caps that would have gone unnoticed. 

This program skillfully integrates cutting-edge imaging methods and analytical tools to significantly improve a crucial industrial process. The use of tried-and-true industrial thermal imaging techniques and an original combination of deep learning and discrete vision tools are essential. The outcome is a comprehensive solution with broad application in industry. 



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