The project “Analysis of order picking errors using Eye Tracking technology” investigates how picking errors can be better understood, predicted and reduced. For this purpose, eye-tracking technologies are used to analyse employees’ eye movements and visual search processes during the order-picking process. By using machine learning methods, the project tries to identify relationships between visual attention, cognitive fatigue, and errors in item selection.

Despite increasing automation, picking processes in many warehouses remain primarily manual, since technical systems have so far been able to replace only a small portion of the sensory and motor skills required for item selection. At the same time, rising performance demands and heavy workloads lead to picking errors, which result in additional costs, delays and unnecessary returns.

Based on the findings from the project, approaches are being developed for intelligent assistance systems that can identify critical situations at an early stage and support staff, for example by prompting them to review an item or recommending short breaks. The aim is to reduce picking errors, improve working conditions and increase the efficiency of logistics processes. At the same time, the digital transformation of logistics is being strengthened through data-driven and human-centered solutions for reliable, ergonomic and high-performance warehouse processes.

The project results will be available via the HOLM platform, publications and workshops, and will form the basis for future applications and software solutions in the field of intelligent Software solutions for intelligent assistance systems in logistics.

The research project (HA-Projekt-Nr.: 8004/26-403) runs from June 2026 to October 2027 and is funded by the State of Hesse as well as the HOLM funding as part of the funding program „Innovationen im Bereich Logistik & Mobilität“ of the Hessian Ministry for “Wirtschaft, Energie, Verkehr, Wohnen und ländlichen Raum”. Prof. Dr. Christoph Glock from the Institute of Production and Supply Chain Management at TU Darmstadt leads the project. The companies DB Schenker Europe GmbH, Frankfurt, Ernst Schmitz Logistics, Frankfurt, and MEWA, Frankfurt are also involved in the project.