Improve traceability and decrease product loss during the induction process
Ecommerce fulfillment and retail distribution facilities need to accurately induct and sort orders and inventory to final shipment locations. Sorting process must be highly efficient and able to detect and prevent errors that could cause lost product or sorter downtime. Sorters wear down, and accumulate dust, dirt, and labels. Under these conditions, traditional solutions often fail and are expensive to maintain. Some warehouses employ specific staff just to manually tweak, clean, and monitor the sorter. Additionally, existing solutions require custom programming or only work for specific sorter types.
Processing issues, such as products hanging over a tray, can result in products falling off the sorter. In these cases, customers will not receive the product and the warehouse will have an inaccurate count of their inventory. Without reliable tray occupation data, induct automation can provide wrong or double counts leading to low order accuracy.
Ecommerce and retail distribution facilities can more efficiently run their induction processes using the item detection capability of the Cognex 3D-A1000 item detection system. This system utilizes 3D and 2D optics to detect objects and identify errors, while ignoring common hygiene issues, such as dirt, dust, and spots on the belt or tray. The 3D-A1000 is factory-calibrated and adapts to various sorter types without custom programming or complicated calibration. The system uses both 3D and 2D data to overcome problematic environmental and item conditions that singularly would otherwise result in an incorrect output.
The 3D-A1000 item detection system is ready to use right out of the box, is set up in less than 15 minutes, and works on all conveyance types. Using advanced 3D image processing technology, the 3D-A1000 delivers high detection rates for inventory accuracy and very low false detections for sorter efficiency. Error state detection provides protection against lost product and sorter downtime. Granular data such as item location or carrier feedback enables further automation of induction processes.