A logistics hub processes high inbound and outbound volumes across thousands of SKUs daily. Pallet unloading and stacking relied heavily on manual labor, exposing workers to repetitive strain and injury risks. Fluctuating volumes also made night and weekend staffing difficult, reducing labor efficiency and ROI.

To support large-scale logistics operations, CMES Robotics deployed an AI 3D vision–based depalletizing and palletizing solution that recognizes box size, position, and orientation in real time. A CMES Robotics-designed gripper handles diverse box types and packaging conditions. The system adapts automatically to changes in box dimensions and stacking patterns, operating autonomously without re-teaching. For palletizing, it detects available pallet space and optimizes placement with no manual intervention.

The palletizing system processes up to 450 boxes per hour, while depalletizing reaches 600 boxes per hour across multi-SKU operations. Automation reduces injury risk, improves night-shift labor efficiency, and stabilizes operations. The system handles crumpled or irregular stacks and integrates seamlessly with existing equipment. With a payback period of just over one year, the site achieved rapid productivity gains while improving workplace safety.