This solution employs real-time imaging and algorithms to identify the optimal pick points and guide the robot’s movements.
High-resolution sensors – 2D cameras or 3D laser scanners – are strategically mounted to a robot’s gripper to capture product dimensions and orientation. These technologies achieve accuracy within 0.5-1mm, ensuring precise positioning of the specific gripper and enabling the system to manage varying pallet configurations and partially consumed pallets with minimal manual intervention.
It’s possible to design a system that optimises the de-palletisation of partially consumed pallets. Robots can be programmed with their onboard inspection system — using a gripper mounted with 2D vision or a 3D laser — to perform a pre-process inspection of the pallet, accurately determine what is in front of it, and execute system logic to begin picking the partially consumed layers for de-palletisation.
CSR Cemintel manufactures fibre cement sheeting products that are stacked and shipped on gluts or custom pallets. Varying glut layouts and pallet sizes are used to prevent damage during transport. We developed a flexible solution for various pallet configurations, directing them onto two fibre cement sheeting outfeeds. Mounted on a trolley, the cell can be easily moved to the second outfeed, significantly reducing capital expenditure by eliminating the need for a duplicate cell.
Unilever supplies its dosing lines with bottles from external suppliers, but manual de-palletisation — picking, decanting, and collapsing cartons over three shifts — hindered output due to staffing challenges. We developed a custom gripper and optimised robot cycle that efficiently de-palletises by gripping carton corners, decanting contents and flat-packing them using controlled pivoting hinge technology. This compact, flexible solution handles varying product sizes while ensuring smooth unloading without bottle displacement.
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