Next-Gen Robot-Based 3D Inspection System Finds Defects Right on the Production Line

senswork Inc.'s state-of-the-art robot-assisted 3D inspection and metrology system is designed for real-time quality control in manufacturing. The fully automated inspection cell leverages collaborative robotics and advanced 3D vision to detect defects and perform precise 3D measurements directly on the production line.

senswork's robot vision system, powered by Photoneo's 3D sensing technology, enables:

• Real-time defect detection -- Identifies imperfections, dents, and deformations with high precision.
• GD&T-compliant 3D metrology -- Performs accurate inline measurements for tight tolerance manufacturing.
• Seamless integration into production -- Supports continuous, automated quality control.
• Quality control directly on the production line.

"The combination of state-of-the-art 3D machine vision and collaborative robotics opens up new possibilities in industrial quality inspection," said Roman Rieger, CEO of senswork. "Our technology enables companies to perform 3D measurements directly at the production line and simultaneously detect surface defects."

Thanks to their ability to detect defects regardless of texture or material, they offer a particularly robust and reliable solution for automated quality control.

"By combining our 3D Vision with senswork's expertise in robotics, we are tackling some of the toughest challenges in inspection. This collaboration enables manufacturers to achieve unparalleled accuracy, detect defects in real time, and streamline quality control processes with greater efficiency than ever before," says Frentišek Takác, Global Strategic Partnerships Manager -- Robotic Vision at Photoneo.

Why 3D Over 2D?

Traditional 2D inspection systems often struggle with variable surface textures and materials. In contrast, senswork's 3D inspection technology provides:

• Material-independent accuracy -- Works on reflective, textured, or multi-colored surfaces.
• Consistent defect detection -- No reliance on contrast-based image processing.
• Reliable pass/fail decisions -- Eliminates false positives caused by lighting variations.

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