[March 15, 2024, Hannover, Germany] Global industrial automation giant ABB and Siemens Digital Industry jointly released the AdaptiveWeld AI 2.0 system, which for the first time realizes the millisecond welding seam error self-correction capability of cross-brand industrial robots (compatible with controllers such as the KUKA KR C4 and the FANUC R-30iB), and may reshape the automotive and aerospace fields It may reshape the high-precision welding standard in the automotive and aerospace fields.

Industrial Robotics

Technology breakthrough highlights

✅ “Vision - Force Control” dual closed-loop AI algorithm

Integrated 3D line laser and tactile sensors, real-time capture of 0.05mm welding seam deviation.

Dynamic path planning based on digital twin, 200% faster response than traditional PLC.

✅ Multi-brand senseless adaptation technology

Seamlessly connects to mainstream control systems such as ABB IRC5, KUKA KSS, etc. through virtualized middleware.

Reduces integrator commissioning time by 70%, cracking the compatibility bottleneck of multi-brand mixed-line production.

✅ Zero sample migration learning

Achieve ±0.1mm accuracy when welding unknown materials for the first time without massive data training.

TÜV Rheinland's “Industrial AI Safety Certification” reduces fault tolerance by 98% compared to traditional solutions.

Industry Validation Cases

The battery tray production line of a German automobile company has been tested:

Increased efficiency: single-station welding cycle time compressed from 82 seconds to 48 seconds.

Cost reduction: manual rework rate reduced from 12% to 0.3%, saving €260,000 in annual QC costs.

Flexible expansion: synchronized control of ABB IRB 6700 and KUKA KR 500 on the same system, with a changeover time of less than 15 minutes.

Industrial Robotics

Expert Opinion

“This is the first intelligent welding solution that truly breaks down brand barriers,” said Dr. Susanne Bieller, Technical Director of the International Federation of Robotics (IFR). ”With the global welding robot market set to reach $6.3 billion by 2025, whoever solves the pain points of multi-machine synergies will control the key to smart upgrading.”

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