Project description
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. Be part of change You will develop a modular data structure for storing sensor and metadata In doing so, you will create a simple surrogate model for mapping quality-related parameters For validation purposes, you will conduct initial test series and analyse the results Finally, you will check whether the model can reliably predict the parameters of a demonstrator component
Funding and compensation
Compensation not specified. See the original posting for amounts, duration and conditions.
Eligibility and application requirements
Review the qualifications, research interests and required documents in the description above. The employer or university's original posting is the source for complete eligibility requirements.
How to apply
Submit your application through Fraunhofer's official application process. Apply early as a closing date has not been specified.
Source and listing information
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