Replacing expensive and complex parts such as turbine components, molds or tools often involves high costs. A cost-efficient and material-saving alternative is the repair of such components using laser powder cladding. Equipped with a Trumpf TruLaser Cell 7020 as well as extensive measuring and production technology, we support our customers in the repair and modification of components made of a wide variety of materials. Adapted to their needs, we offer them an extensive range of services for the repair of their components with feasibility studies, optimized process design and path planning, and the implementation of repair processes in existing production chains.
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 LPA build-up strategies
Path planning for 5- and 7-axis LPA processes for repair and additive build-up
Maintenance, repair and overhaul
Material-saving and cost-efficient repair of components, molds or tools for turbomachinery
Upgrade instead of repair: improvement of component properties through functionalization, wear protection and coating
TRUMPF TruLaser Cell 7020 with 5-axis machining optics and turn-tilt table
Trumpf TruDisk 2000, 2kW power
Processing head with 3-jet nozzle and ring jet nozzle
LPA process monitoring by pyrometer, infrared camera, laser profile measurement and external linear Renishaw path measurement system
Upgrade instead of repair
At the Werner-von-Siemens-Centre for Industry and Science we are researching how components can not only be repaired but also improved during the service process using additive methods.
Sensor technology in additive components
We develop solutions for the embedding of sensor technology in safety-critical aerospace structural components and highly stressed functional elements in power engineering.
Certify as you build
With the aid of artificial neural networks, we detect important process parameters during additive manufacturing and can make predictions about component quality on this basis.