As SKU requirements are unique to each individual distributor or store’s needs, mixed case palletizing — building multi-SKU (Stock Keeping Unit) pallets, is key to B2B distribution, especially in retail. However, the labor shortage and physical risks of handling heavy boxes make the manual approach an imperfect choice.

Some companies have already implemented automation solutions, but the investment required is substantial and the return on investment (ROI) may take years. Moreover, changing SKU requirements demand high automation flexibility, thus bringing more challenges to mixed case palletizing.

In response to these dynamics, XYZ Robotics collaborated with Chinoh.Ai, an innovative logistic integrator, to help Trancom, a leading Japanese 3PL server, reinvent its logistics center in Saitama.

How to automate B2B order fulfillment process?

The automation solution consists of AS/RS (Automated Storage and Retrieval System) and mixed case palletizing robots. It covers the inbound, storage, and outbound processes.

The goods flow starts with the goods receiving. The operator uses forklifts to transport single-SKU pallets to the entry of AS/RS. The lifts and RGVs (Rail Guided Vehicle) receive and store these unit loads on high-density racks in the Storage Area.

When duty calls, AGVs (Automated Guided Vehicle), also called AMRs (Autonomous Mobile Robot) will transport SKU pallets from the exit of AS/RS to the Order Picking Area. Our mixed case palletizing robots pick the required amount of cases from single-SKU pallets and palletize them on multi-SKU pallets to fulfill orders — a process called Mixed Case Order Picking.

When finishing depalletizing, single-SKU pallets with remaining cases will be transported back to the Buffer Area by AGVs and wait for the next assignment. Following mixed case palletizing, the order pallets will be dispatched for outbound delivery.

How to address the mixed case order picking?

The solution combines vision-guided depalletizing and mixed case palletizing. Our robot first picks the required amount of SKUs during depalletizing and strategically places them on mixed case pallets. The mixed loads are supposed to be stable and volume-efficient to make the most of the pallet space.

The robot workstation incorporates two 3D cameras above each depalletizing position. As AGVs deliver single-SKU pallets, the cameras capture them, allowing the vision system to identify each case's location on the pallet and guide the robot for accurate picking. Powered by deep learning algorithm, the robot adapts to new case types without pre-registration or any input.

The mixed case palletizing process is also supported by our advanced pallet planning technology. Confronted with various cases coming in a random sequence, our system can autonomously calculate the optimal placement of each case to build a stable and dense pallet immediately and in the foreseeable future.

Autonomous picking robot upgrades warehouse automation

Case picking, involving repetitive movements of heavy boxes weighing up to 30 kg, poses safety risks and fatigue for manual operators. Tired forces may also lead to increased picking errors. Adopting fully autonomous picking robots significantly enhances the working environment and warehouse ergonomics, ensuring accurate and efficient operations.

Previous outbound solutions often involve complex and costly equipment like miniloads, conveyor lines, and mixed case palletizing workstations. These methods rely on meticulous pallet planning that requires prior knowledge of SKU and order information, with cases arriving in specified sequences.

In contrast, our solution for Trancom is more streamlined, space-efficient, and cost-effective. The combination of agile AGVs and efficient picking robots eliminates the need for bulky and expensive equipment. With modularized designs, our solution offers a more flexible and easily scalable alternative, which is much easier to integrate in the warehouse.