Das additive Fertigungsverfahren Laser-Powder Directed Energy Depositon (LP-DED), kombiniert mit automatisierten Reverse-Engineering-Ansätzen, bietet die Möglichkeit, Bauteile effizient zu reparieren. Durch intelligente Algorithmen können im sogenannten Scangineering 3D-Scandaten von Bauteilen vorverarbeitet, ausgerichtet und parametrisiert werden. Die erkannten geometrischen Defekte werden zur Errechnung der Werkzeugwege für den additiven Aufbau verwendet und mittels des LP-DED-Prozesses aufgeschweißt und repariert. Dabei kommen vor allem die Vorteile der flexiblen Prozessführung, ein hoher Automatisierungsgrad und gute Reproduzierbarkeit zum Tragen.

Close-Coupled Gas Atomization (CCGA) is often used to produce spherical metal powders with a wider Particle Size Distribution (PSD) (10 -500 µm) compared to that required by the main Additive Manufacturing processes (10 -105 µm). This work presents an accuracy evaluation of a mathematical model based on the Lubanska equation to predict the d50 for CCGA. Atomization experiments of 316L steel were conducted to evaluate the tip diameter and atomization gas pressure effects on PSD and, the d50 experimental results were used as the reference to the mathematical model evaluation. The mathematical model accuracy could be improved by: (i) considering the backpressure phenomenon for the metal flow rate calculation, since it was an important inaccuracy source; (ii) reviewing the tip diameter effect, which had a lower impact on d50 than that predicted by the Lubanska equation. The atomization gas pressure was the most influential parameter on d50 and d90 and the increase of the gas pressure led to a significant reduction in PSD and, consequently, increased yield.