WEB Sensitivity investigations on the influence of metal powder properties on Additive Manufacturing processesFriday (25.09.2020) 10:25 - 10:40 P: Processing and Synthesis 2 Part of:
The qualification of feedstock material is a main point of interest in the quality assurance for Additive Manufacturing (AM) processes. The influence of metal powder properties on the process performance of powder-based AM processes like Laser Powder Bed Fusion (L-PBF) or Laser Metal Deposition (LMD) is still not fully understood. Especially the process specific qualification of metal powders regarding their characteristics like rheology, chemistry and morphology depending on their production process and degradation is still not fully interpretable.
For some of the established AM-industries like aerospace this factor limits the range of used powders to high quality powders and reduces the possible life span of powders until their disposal. Target of this contribution is to give insight into a sensitivity investigation of the LMD-process from minor differences between various batches of Ti6Al4V powder. Therefore, several deposition trials based on a statistical experimental design were conducted to investigate the influence of varying powder properties on the deposition and processing quality. Connected with a comprehensive screening of the powder properties and the gathered process and material data a base model for linking the powder properties with the process performance shall be developed.
On this base the derivation of possible counter measures to compensate minor variations in the feedstock properties via dedicated adjustments of the applied process parameters shall be enabled. Furthermore, of the conducted investigations an approach for the key powder quality factors for LMD-processes shall be identified. On base on the applied quality assurance routine in this study also an overview about the process specific quality assurance of metal powders shall be given and an outlook about the processing of low-cost powders and novel qualification approaches like hyper spectral imaging and the added value for AM shall be discussed.
The conducted experimental investigations were conducted in the project GeKowiG funded by the Federal Ministry of Education and Research (BMBF) in the funding program “Line integration of additive Manufacturing processes (LAF)”.