Fraunhofer ILT & Etxetar advance EHLA and LMD

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In These Fields, Laser-Based Processes Can Excel

Among the new fields of application, aviation stands out as particularly promising. High-value components such as blisks, turbine blades, and other geometrically complex parts embody precisely the requirements that make laser-based repair using LMD so attractive. These include high material value, extreme operating conditions, and a strong interest in extending the lifespan of components rather than replacing them prematurely. Aviation sets the benchmark for what laser-based repair must achieve: precision, repeatability, and complete process control for components where failure is not an option, comments Alejandro Bárcena, CEO of Etxetar. However, aviation is not the only field where the partnership can create advantages. Etxetar has already documented use cases in the repair of gears, worm wheels, and certified railway axles–applications where wear, localized damage, or complex geometries make replacement costly. Components related to space exploration are also "on the radar," particularly when innovative manufacturing and repair strategies can support new propulsion concepts or other highly specialized applications.

Tool and mold making can also benefit from laser cladding, as seen here. Damaged tool areas can be repaired efficiently and precisely by welding material and reshaping them to contour. The expensive component can then be reused.(Image: Etxetar) — Tool and mold making can also benefit from laser cladding, as seen here. Damaged tool areas can be repaired efficiently and precisely by welding material and reshaping them to contour. The expensive component can then be reused.
(Image: Etxetar)

Artificial Intelligence is Making Its Way into Laser Processes

Artificial intelligence is also playing an increasingly practical role in making these laser-based processes more robust and productive. The "AI-SLAM" project of the Fraunhofer ILT demonstrates how this works in laser metal deposition. The system captures component geometries during the coating process, detects deviations from the target contour, and adjusts process parameters such as feed rate in real-time, the researchers explain. Based on larger data sets, the software also learns to improve the process iteratively. For industrial users, this is relevant because coating and repair tasks are often characterized by uneven wear, varying layer thicknesses, and repeated manual corrections. Within the partnership with Etxetar, this type of digital process intelligence creates additional value and supports the transition from good individual results to reliable performance in demanding industrial environments on a large scale, it is believed.

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Date: 08.12.2025

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