Narrow, precise gaps in doors, hoods, and tailgates are considered a hallmark of modern vehicles. Ensuring accurate gap dimensions serves not only purely aesthetic needs but also functional importance - such as achieving a uniform closing force and optimum tightness.
DFKI's industrial demonstrator from the AIQUAMA (AI-based Quality Management for Smart Factories) project shows how integrative sensor technology interacts with the digital twin and AI to enhance quality assurance in car body construction. The aim is to minimize the effort involved in door adjustment. A bodyshell will be utilized to demonstrate how a combination of intrinsic sensor data and external sensor technology can create a comprehensive representation of the production environment and the individuals involved, including their current status.
The system recognizes, for example, whether a car door is open or closed, whether a worker is working on a door or is on the way there. All recorded raw data is processed in the administration shell to compare the actual status with the target status. If the gap dimension requires correction, the worker receives clear instructions from the Industrial Metaverse through mixed reality glasses or as a projection directly onto the vehicle door. This allows for a targeted readjustment of the screw connection on the door.
The AIQUAMA demonstrator, which includes a robotic production cell for modular battery retrofitting and a control algorithm for the humanoid Unitree H1 robot, represents a part of DFKI's Twinned AI innovation field.
The AIQUAMA project is funded by the Federal Ministry of Education and Research. In addition to DFKI, the Czech Technical University in Prague, the University of Brno, and the Technical University of Ostrava, the project also involves application partners Volkswagen AG and Skoda Auto.
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