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Tracking the course of the manufacturing process in selective laser melting

: Thombansen, U.; Gatej, A.; Pereira, M.

Preprint urn:nbn:de:0011-n-2906396 (881 KByte PDF)
MD5 Fingerprint: 71d076ed9a851ac4a4fb579ccc8527e8
Erstellt am: 23.5.2014

Dorsch, F. ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
High-Power Laser Materials Processing: Lasers, Beam Delivery, Diagnostics, and Applications III : 4–6 February 2014, San Francisco, California, United States
Bellingham, WA: SPIE, 2014 (Proceedings of SPIE 8963)
ISBN: 978-0-8194-9876-2
Paper 89630O
Conference "High-Power Laser Materials Processing - Lasers, Beam Delivery, Diagnostics, and Applications" <3, 2014, San Francisco/Calif.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ILT ()

An innovative optical train for a selective laser melting based manufacturing system (SLM) has been designed under the objective to track the course of the SLM process. In this, the thermal emission from the melt pool and the geometric properties of the interaction zone are addressed by applying a pyrometer and a camera system respectively. The optical system is designed such that all three radiations from processing laser, thermal emission and camera image are coupled coaxially and that they propagate on the same optical axis. As standard f-theta lenses for high power applications inevitably lead to aberrations and divergent optical axes for increasing deflection angles in combination with multiple wavelengths, a pre-focus system is used to implement a focusing unit which shapes the beam prior to passing the scanner. The sensor system records synchronously the current position of the laser beam, the current emission from the melt pool and an image of the interaction zone. Acquired data of the thermal emission is being visualized after processing which allows an instant evaluation of the course of the process at any position of each layer. As such, it provides a fully detailed history of the product This basic work realizes a first step towards self-optimization of the manufacturing process by providing information about quality relevant events during manufacture. The deviation from the planned course of the manufacturing process to the actual course of the manufacturing process can be used to adapt the manufacturing strategy from one layer to the next. In the current state, the system can be used to facilitate the setup of the manufacturing system as it allows identification of false machine settings without having to analyze the work piece.