Thesis: AI-based local quality prediction for laser powder bed fusion
AachenPosted Sep 7, 2026
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In cooperation with the Chair of Optical Systems Technology (TOS), the Fraunhofer Institute for Laser Technology ILT—Europe’s leading center for contract research and development in the field of laser technology—is offering the opportunity to write a thesis on the topic: »AI-based local quality prediction for laser powder bed fusion«.
We are currently developing machine learning-based approaches to make the laser powder bed fusion (LPBF) process more efficient and improve its quality. To this end, a scalable database of sensor and process data is being created, which serves as the basis for ML models for component segmentation, strategic path planning and process optimisation. The aim is to enable data-driven solutions for the automated analysis of melt pools, porosity and other quality-relevant parameters in 3D printing.
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Original posting: jobs.fraunhofer.de
RISC-V ecosystem
Fraunhofer Gesellschaft in the RISC-V ecosystem
RISC-V International: Strategic
Attn: Norbert Schuhmann, Erlangen, Germany c/o Fraunhofer IIS Alexander Noack, Dresden, Germany c/o Fraunhofer IPMS The Fraunhofer Society is a German research organization with 72 institutes…
- Develops RISC-V processor cores, incl. a RISC-V core for functional safety (whitepaper; Lauterbach added tool support)
- Fraunhofer IMS works on Edge AI on low-footprint RISC-V (the AIRISC core family)
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