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21.03.2024

Pallet classification made easy: How EDEKA is optimizing the receipt of goods with the help of SICK

Optimized processes ensure smoother workflows, increase productivity and have a positive impact on a company’s success. EDEKA knows this all too well. As a representative of the food and beverage industry, the company recognizes significant potential for improvement when it comes to receiving goods, for example: Here, the goods are delivered by truck on pallets from a wide range of manufacturers – including pallets that are subject to the pallet deposit and pooling system. The manual classification of deposit pallets when receiving goods requires a high use of resources and therefore involves a potential for error that should not be ignored. EDEKA entered into an innovative partnership with SICK in order to avoid the resulting costs, save resources, and simultaneously increase process quality and transparency. The Pallet Classification System (PACS) for automatic pallet classification was developed in close cooperation.

Deposit or no deposit – that is the question

As a major player in the German retail sector, EDEKA is pursuing an ambitious goal: By 2025, the Group aims to invest 450 million euros in the automation, innovation and expansion of its warehouses in the regions of northern Bavaria, Saxony and Thuringia. These plans are already taking shape at the Berbersdorf site. Among other things, this applies to receiving goods, especially the classification process for delivered pallets. In addition to deposit and pooling pallets such as EPAL or CHEP, there are also pallets that are not subject to the deposit system. Until now, in order to avoid incorrect deposit payments to suppliers, each incoming pallet has been classified manually according to its deposit relevance, which can be recognized by the color and the label/branding on the pallet block – an error-prone, time-consuming and resource-intensive process.

The optimization potential for EDEKA is obvious: “It is important for us to know whether the pallet has a deposit or not. At the moment, the check is carried out manually by an employee when receiving goods. Our joint project with SICK will change this in future, as the pallet type will be recorded automatically.”

Cooperation from A to Z

In addition to the design and development of the Pallet Classification System, the joint project also involves the corresponding installation in the existing plant: Two color cameras for image acquisition, a light barrier arrangement for triggering the pallet and a controller for processing the data and executing the pre-trained AI-based neural network. An optional third color camera can be mounted above the conveyor system, for example, to document the load on the pallet.

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