FASER
KI generiertes Bild über Metall-3D-Druck
WG Microsystems Technology/System Integration

FASER

The project develops measures for more energy- and resource-efficient production of 3D-printed metal components in SMEs.

German version

Error-free additive manufacturing through adaptive sensor technology for optimizing energy and resource efficiency

The overarching goal of the FASER project is to enable small and medium-sized enterprises (SMEs) to significantly enhance the manufacturing quality of 3D-printed metal components by achieving energy and resource efficiency through targeted analytical and technological developments. This will be accomplished using a zero-defect strategy. Given the current substantial increase in energy costs, the FASER collaborative project aims to determine the energy and resource efficiency for the entire production process chain of additive manufacturing methods for 3D printing metal, compared to existing conventional manufacturing processes. The two research institutions will comprehensively investigate and ensure process reliability for both the powder bed fusion (SLM) and wire-based GMA-DED methods.

The project is funded for a duration of four years and receives co-financing from the European Social Fund Plus (ESF+).

 

For the period from Q2 2024 to Q1 2028, the following objectives are defined:

  • Research suitable solutions for process analytics, including thermography, acoustics, and spectroscopy.
  • Specify requirements for energy and resource monitoring in compliance with energy efficiency standards.
  • Plan a comprehensive software environment and conduct an interface analysis for controlling system components and processing data.
  • Create reference prints and a demonstrator.
  • Install and calibrate process analytics in SLM/DED systems.
  • Develop methods for continuous monitoring of printing processes and energy/resource consumption.
  • Conduct comprehensive quality analyses of the physical-mechanical properties of printed components

 

grant number: 86000670