By leveraging data, arti cial intelligence (AI), and analytics tools, it’s possible to collect and analyze data on nearly every aspect of warehouse operations. “By using data to identify patterns, trends, and areas for improvement, we can make more informed decisions,” Thyen says. For instance, it likely makes sense to move fast-moving items where they can be more easily accessed. ROBOT COSTS COME DOWN Deploying robots within a DC has become increasingly economical. “Better camera technology, keyword image recognition, more computing power, and ever-improving AI are increasingly opening elds of application in intralogistics,” says Karoline Kowalik, logistics engineer and PhD researcher with Arvato Supply Chain Solutions. By using an AI camera that snaps images of different parcels, robots can learn to handle thousands of SKUs of varying sizes. How? Once the robots learn how to handle one parcel of a particular size, they can try to handle similar packages the same way. If they don’t receive an error message, the robots can assume their actions were correct. When designing Sager’s new warehouse in Lewisville, Texas, Freise knew it didn’t make sense to install miles of conveyance, as the products’ weight
GXO Logistics builds warehouse and DC automation solutions that o¢er real-time visibility, enhance inventory management, and reduce costs. Collaborative robots, for instance, support workers during picking and packing operations.
processes. Agrawal identi es several strategies his rm employs to achieve this, including batch picking to group similar orders and reduce search and pick time. Pickers are assigned to speci c zones within the warehouse to minimize travel times. Arvato uses a robot-controlled de-palletizer, Stark , along with the warehouse management system, and an automated guided vehicle (AGV) to move cartons of different sizes and shapes from stored pallets. When the AGV brings the pallets, Stark picks the right amount according to the WMS. At the picking positions, AI cameras measure the parcel and pallet dimensions, and calculate an optimal picking sequence and gripping positions. The cameras also detect different labels and orient the box accordingly. Stark ’s self-learning software can determine the shape of the object and how it needs to be picked up. Its exible gripper head moves over the pallet, and suction cups lift the carton onto the conveyor belt. Goods-to-person (GTP) systems regularly prove to be more ef cient than traditional module/pick tower designs, as they reduce walking or travel time, Carter says. A well-designed GTP station can also be used in conjunction with
made them too heavy to use conveyors. Instead, Sager will deploy robots to transport products. As products arrive at the Texas distribution center, robots will transport carts from the receiving dock to vertical lift modules (VLMs) for stocking, and then from the VLMs to packing. “For products that are too large for traditional conveyance, we’re moving the product less,” Freise says. “Instead, we invested in solutions to make it easier for the individual to move to the product.” Accuracy and streamlined operations are just as critical within outbound
As their ecommerce operations grow, many shippers consider splitting inventory across multiple distribution centers so products are closer to more customers. The hitch? If you only have, say, one dozen units per SKU, splitting them often isn’t practical, says Je Wolpov, senior vice president of ecommerce with Ryder Ecommerce by Whiplash. Instead, small parcel delivery is more economically friendly and accomplishes the same goal of moving goods to customers as quickly as possible. When products arrive at a DC that will be used to fill ecommerce orders, it’s no longer enough to simply get them o the truck. “You need to separate and put them away so they’re sellable,” Wolpov says. GETTING OUT QUICK
42 Inbound Logistics • May 2023
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