Missing item inspection
Detect presence or absence of products during final assembly
Food and beverage manufacturers must detect missing items and verify the completeness of final packages before they are distributed in order to avoid costly chargebacks and returns, as well as damage to their brand. During secondary packaging, items are wrapped and packaged in their final form. Quality inspections confirm the presence or absence of products inside the packaging before they leave the facility.
Cognex 2D vision systems with edge learning perform pass/fail inspections and trigger a rejection when a faulty item or package is detected. The embedded edge learning tools are trained using only a few images to classify packages into good (all items present) and NG (one or more items missing). They verify that all bottles or products are present even under shrink-wrapped packaging, helping food and beverage manufacturers error-proof their operations and maintain customer satisfaction.
The edge learning tools find complex features and objects by learning from annotated images. Self-learning algorithms locate different types of items on very noisy backgrounds or other complex objects in bulk. To train the tool, the user provides images where the targeted features are marked.