In laser beam powder bed fusion for metals (PBF-LB/M), a subgroup of additive manufacturing processes, the powder applied layer by layer is locally fused. There are numerous optimization options for increasing the printing speed or printing accuracy. Do you want to predict or optimize the material properties and reduce costs in the process? We can help you with this. Fraunhofer IWM enables the simulation of the powder bed process and has developed a simulation chain along the complete PBF-LB/M process, starting with the powder layer application, laser melting and microstructure formation and ending with the estimation of certain local mechanical properties of the manufactured component. The complexity of the process requires the combination of several simulation methods, but also shows which methods are available for process optimization in the powder bed process. The Discrete Element Method (DEM) is used for simulations of the powder application. Ray tracing is used to model the laser beam including possible reflections. Smoothed particle hydrodynamics (SPH) simulations are then used to investigate the flow in the melt pool, taking into account thermocapillary effects and the recoil pressure of the gas phase. The material properties required for this are obtained from thermodynamic CALPHAD simulations. The temperature field of the melt bath is coupled with cellular automaton, which calculates the growth of dendritic grains and thus provides a prediction for the microstructure formed during solidification. This is used to determine the influence of the output of the laser on the microstructure. This microstructure is then used for crystal plasticity finite element analyses for the qualitative description of texture-dependent mechanical properties. The consideration of the complete chain makes it possible to estimate correlations such as the influence of the alloy composition on the workpiece quality. Of course, we can also provide you with a parameter set for your own simulations.
Um neue Kunststoffe in der additiven Fertigung mittels Pulverbettschmelzen (PBF-LB/P) zu verarbeiten, bedarf es der Kenntnis von materialspezifischen Prozessparametern. Sie suchen die optimalen Prozessparameter für ihr Verfahren? Diese werden häufig in aufwändigen Versuch-und-Irrtum-Zyklen ermittelt. Um den Einfluss von Eingangsmaterial auf die Materialeigenschaften abzuschätzen, wird in einem Verbundprojekt mit unseren Partnern vom Kunststoffzentrum SKZ in Würzburg ein Zusammenhang zwischen Materialdaten, Prozessparametern und Bauteilqualität entwickelt. Das Projekt wird von der Deutschen Forschungsgemeinschaft (DFG) im Rahmen des Schwerpunktprogramms 2122 Werkstoffe für die Additive Fertigung gefördert. Dabei werden die Laserbestrahlung und die thermoviskose Strömung bei PBF-LB/P sowohl theoretisch als auch durch transiente numerische Simulationen, die einzelne Pulverpartikel räumlich auflösen, analysiert (siehe nebenstehende Abbildung). Basierend auf den Ergebnissen wird ein neuartiges Verhältnis von Laserenergieeintrag und Energiebedarf zum Aufschmelzen des Polymers - das Attenuation Melt Ratio (AMR) - eingeführt, dass Materialeigenschaften und Prozessparameter in Beziehung setzt. Auf der Grundlage des AMR werden normalisierte Prozessdiagramme erstellt, die Prozessfenster für optimale Bauteileigenschaften enthalten. Konkret erlauben die Simulationen eine Vorhersage des Einflusses von Laserleistung und Lasergeschwindigkeit sowie Partikelgröße und Partikelform auf die Produktqualität. Sie erfahren die optimale Laserleistung und können mit diesem Wissen den Energiebedarf senken und Ihren Prozess nachhaltiger machen. Die Vorhersagequalität der Prozessfenster wird durch die Bewertung der mechanischen Eigenschaften der hergestellten Teile aus verschiedenen Polymeren bestätigt.
During powder bed fusion, the powder is introduced into the installation space in order to create a new layer that is as homogeneous as possible. A suitable simulation method must be able to map the particle size distribution, accurately capture the flow behavior of the particles and take into account interactions with system components such as the doctor blade or roller. The Discrete Element Method (DEM), in which the simulated particles interact with each other through repulsion, sliding and rolling friction, dissipation and cohesion, is suitable for this. The simulation of the powder application is shown in the figure, where a roller generates a powder layer in the installation space. The homogeneity and density of the resulting powder layer can vary depending on powder properties such as friction and cohesion as well as process parameters such as the translational and rotational speed of the roller. The powder properties required for the simulation are determined experimentally at Fraunhofer IWM.
In additive manufacturing with sinter-based processes, deviations from the desired shape can often occur during firing due to gravitational influences or shrinkage-induced friction effects on the sintering base. This deformation can be predicted. In contrast to conventional shaping processes, in which the compensation of such undesirable deviations is often complex, additive manufacturing processes can in principle easily take such compensation into account during the construction process. Fraunhofer IWM has therefore developed a simulation method that automatically determines the required printing geometry by simulating an "inverse" sintering process.
Fluid rheology dominates the pressure behavior in material extrusion. In these processes, such as fused filament fabrication (FFF), a polymer filament is melted in a hot nozzle during the process and pressed out of the nozzle opening. The filament can also consist of a mixture of high-melting point particles (e.g. a metal powder) and a plastic mixture. Robocasting also involves extruding a paste through a nozzle. The simulation of these processes enables a targeted investigation of process-related issues: How to react if the nozzle clogs, the volume flow does not occur evenly, the build space is not completely filled and if the printed lines are too thin or too thick? In robocasting, for example, a paste was considered that contains ceramic particles of different shapes and sizes in addition to the carrier polymer. The composition of the paste determines the flow properties during the printing process and the material properties of the finished component. Tailor-made paste compositions are therefore required to realize the desired printed object. Identifying an ideal paste is very resource-intensive. Numerical simulations help by correlating formulations and the flow behavior of a paste to reduce the number of trial-and-error cycles to determine an optimal paste composition. In this example project, the influences of the filling level of platelet and spherical components of a paste on the paste viscosity were investigated and experimentally validated.