Food and Beverage

Assorted chocolate box quality inspection

Ensure all pieces in an assortment are present and undamaged

An industrial camera with deep learning inspects boxes of mixed chocolates to ensure the correct chocolates are in the right spots.

相關產品

VisionPro ViDi Product Tile

VisionPro Deep Learning

深度學習工業圖像分析的圖形化程式設計環境

In-Sight D900

In-Sight D900

採用 In-Sight ViDi 深度學習視覺軟體

Confectionary chocolate is a high-cost, high-value product with tight standards for condition and quality. Each piece must be free of signs of physical damage such as dents, punctures, or scratches. Chocolates in a single box can have various shapes, colors, and textures.

Damaged or missing chocolates in quality assortments are a significant defect that can lead to consumer dissatisfaction and brand damage.

Individual chocolates may have a variety of patterned or random surfaces and can range in reflectivity. Possible damage might be located anywhere on any chocolate in the assortment. The range and unpredictability of defects and their locations make it impossible to program conventional machine vision to detect all possible defects.

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Cognex Deep Learning is ideal for detecting small and unpredictable defects. It trains on a set of images of all acceptable types of chocolate, with their range of variation. The defect detection tool then flags as anomalies any pieces of chocolate that deviate outside of the acceptable range, no matter what the type of defect. These can then be removed, maintaining quality standards.

Consumers are guaranteed that an opened box of chocolates will contain the specified contents, complete and undamaged.

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