SolMotionCase Study
Body Panel Sealing Using Vision Guided Robotics + AI
Case
Automating the Vehicle Body Panel Sealing Process
Achieving consistent quality in automobile manufacturing requires precise synchronization of complex processes. A critical step in this process is sealing the car body panels, where accuracy in positioning and sealing quality plays a decisive role in the vehicle’s durability and performance. While traditional vision systems often fail to meet these demands, vision-guided robots combined with AI enable more precise control, improving sealing quality, optimizing operational processes, and maintaining production standards in high-demand environments.
Challenge
Limitations of the Laser Triangulation Method in the Sealing Process
Sealing the car body requires close coordination between robotic systems and scanning technology. Traditional laser triangulation methods often face challenges in meeting these demands due to limited scanning range and positioning constraints. These limitations can result in alignment errors, missed sealing points, and slowed production processes, posing significant risks to quality control and operational efficiency in high-speed automotive manufacturing environments.
Solution
Sealing the Vehicle Body Accurately with VGR + AI
SolMotion, Solomon’s vision guided robotics software, integrates AI and 3D vision technology to provide precise sealing solutions for automotive manufacturers. By analyzing 3D point cloud data, SolMotion accurately identifies different car models on the production line and dynamically adjusts the sealing path in real time to accommodate variations in alignment or orientation. This flexibility ensures consistent sealing quality even when component positions change.
The system’s adaptability enables multiple robots to work in sync, maintaining uniform sealing quality across the entire production line. SolMotion not only enhances sealing precision but also improves production efficiency by reducing alignment errors, missed sealing points, and delays that could impact manufacturing schedules.