Exclusive insights into AI-optimized inbound and logistics processes at the AI Vision Day

Every day, up to 180 pallets arrive at the incoming goods department at Rutronik's logistics center in Eisingen, Germany. Even today, around 20 percent of the delivery notes are still handed over in paper form or scanned. It used to take the logistics staff around an hour to manually read and digitally record the key data documented on the delivery notes. The main objective of the automation was therefore to reduce the workload of the employees and to avoid errors.

The automated capture application developed by COMI uses AI models to recognize and read the information on the bills of lading. As there are around 1,000 different delivery note formats, the layout of which frequently changes or is subject to ongoing adjustments, making it time-consuming and error-prone even for trained staff, the processing of delivery notes can be significantly accelerated. However, the Document Reader is also suitable for capturing other documents, regardless of whether they are physically available or have already been stored digitally, e.g. as PDFs, image files, etc. The content can be recorded in a structured way and saved accordingly.

In the incoming goods department, the pallets and packages are opened, distributed to item-only load units and transported to the warehouse. Currently, the item number is either transmitted by hand scanner or manually entered, and the total quantity and codes such as trace code and date code are manually determined and entered. These processes are error-prone and slo

The Label Reader developed by COMI enables the capture of article information such as date code and trace code by means of a camera. The camera reads all code and font information on the labels and provides it in a structured way. The data is stored and can be compared with the master data in the logistics system. This makes the Label Reader a key component in the complete traceability of all products.