Real-time correction of seam shape at irregular pre-openings

As long as parts fit perfectly together, gas cap and wire searching (Quick-Touch) are sufficient to measure deviations in the position of the weld seam so that the robot can automatically adjust it in the welding program. However, with V-, I- and raised welds, irregular pre-openings and deformations due to shrinkage or heat input, it becomes a lot more difficult and sometimes even impossible to weld these welds with the welding robot. Use of the welding robot in such cases is still no match for the speed and flexibility of an experienced manual welder. The ARC-EYE Adaptive plug-in that Valk Welding developed for its ARC-EYE CSS welding seam tracking system now changes this.

ARC-EYE CSS is a laser sensor system, mounted on the robotic welding torch that registers deviations in the position of the weld seam during welding and corrects them in real time. This eliminates the need for manual program corrections and increases process speed. With the ARC-EYE Adaptive plug-in, the ARC-EYE CSS can now also be used to correct welds with larger tolerances in real time. Therefore, workpieces that could previously only be welded manually can now be welded on the robot thanks to this development.

ARC-EYE Adaptive plug-in recognises the geometry

Due to an irregular pre-opening, a deviant weld seam preparation or distortion caused by the welding process itself, the geometry of the weld seam (seam shape) can deviate. A small geometric deviation can quickly lead to a volume deviation of 40% to 80%. So this means that much more welding material is needed and most likely a different way of welding is needed. With the adaptive plug-in, the ARC-EYE CSS laser sensor also recognises the seam shape and automatically adjusts the welding current, welding voltage, welding speed and weaving movement in the welding program accordingly. Workpieces with larger and irregular tolerances can thus now be welded robotically. In practice, this means that suppliers and OEMs can guarantee higher consistent "robotic quality" to their customers.

Real-Time Adaptive Multi-Layer

For deviations of a few millimetres, the welding volume can easily double.
With such differences in geometry, Real-Time Adaptive Multi-Layer can automatically accommodate this volume difference.

Real-Time Adaptive Seam Mapping.

When during multi-layer welding the volume differs per layer, it is necessary to distribute the welds differently per layer. Therefore, it may be necessary to use a different welding strategy per layer. For this scenario, engineers at Valk Welding are now working on Adaptive Seam Mapping in which each weld, layer by layer, is automatically calculated and generated. During or after the root seam, the ARC-EYE scans the seam shape and uses this data to calculate the best-fitting weld distribution. This calculation then considers the varying weld volume and minimum/maximum allowable heat input per weld.


  • Delivers a correctly positioned weld seam
  • Also on reflective materials such as stainless steel and aluminium
  • No manual program corrections
  • No complex welding jigs
  • Increases process speed
  • Increases process accuracy
  • Prevents unnecessary rejects
  • Greatly enlarges the area of application of welding robots
  • Increases OEE (overall equipment efficiency)

Practical example of welding crane booms

At the German company KSK Vlassenroot, which manufactures, among other things, the crane booms for Liebherr cranes, very strict requirements are placed on the welding due to the high forces on the crane booms. Because the assemblies are made of cast and rolled steel the gaps never close 100%, until recently they were exclusively welded by hand. When KSK Vlassenroot could weld the crane booms robotically, the supplier could guarantee a higher and constant welding quality. Thanks to the deployment of ARC-EYE CSS and the Adaptive plug-in, these crane booms are now successfully welded on Valk Welding welding robots. Meanwhile, more customers require that other parts are also welded in this way.

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