Fraunhofer Institute for Production Systems and Design Technology
Fraunhofer Institute for Production Systems and Design Technology

Repair Technologies

Repair Instead of Replace

© Fraunhofer IPK
Laser powder cladding repair of a turbine blade tip

Replacing expensive and complex parts such as turbine components, molds or tools is often associated with high costs. A cost-effective and material-friendly alternative is to repair such components using laser powder cladding. Equipped with a Trumpf TruLaser Cell 7020 and extensive measuring and production technology, we support our customers in repairing and modifying components made of a wide range of materials. Tailored to your needs, we offer a wide range of services for the repair of your components, including feasibility studies, optimized process design and path planning, as well as the implementation of repair processes into existing production chains.

 

 

What we offer

  • Feasibility, material and parameter studies for laser powder cladding
  • Processing of difficult-to-weld alloys such as titanium or nickel-based materials
  • Development and optimization of laser cladding deposition strategies
  • Path planning for 5- and 7-axis laser cladding processes for repair and additive deposition

Industrial Applications

  • Maintenance, Repair and Overhaul
  • Gentle and cost-effective repair of turbomachinery components, molds and tools
  • Upgrade instead of repair: Improve component properties through functionalization, wear protection and coating

Technical Equipment

  • TRUMPF TruLaser Cell 7020 with 5-axis processing optics and tilt-turn table
  • Trumpf TruDisk 2000, 2kW power
  • Processing head with 3-jet nozzle and ring nozzle
  • Laser cladding process monitoring with pyrometer, infrared camera, laser profile measurement and external Renishaw linear encoder

Selected References

Upgrade instead of repair

As part of the Werner von Siemens Center for Industry and Science, we are researching how additive processes can be used not only to repair components, but also to improve them during the service process.

Certify as you build

We use artificial neural networks to capture key process parameters during additive manufacturing to make predictions about part quality.