Fraunhofer Institute for Mechanics of Materials IWM
Fraunhofer Institute for Mechanics of Materials IWM

Customized material properties in additive manufacturing

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Homogeneous powder bed

The homogeneity and density of the powder bed depends on powder properties and process parameters during doctoring. Issues arise, such as achieving optimum layer thickness for the powder used, knowing which doctor blade speed leads to the best results in terms of uniformity and density of the powder bed and the influence the particle size and particle shape of the powder on the application process. The simulation of the powder application answers these questions. 

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Material selection for polymers

The choice of materials for laser powder bed fusion of polymers (PBF-LB/P) is very limited. One of the main reasons for this is a lack of knowledge about which material properties are important for the process and how these affect product quality. An in-depth understanding of all relevant mechanisms of the PBF-LB/P process does not yet exist. What exactly are the relationships between process parameters, material data and component quality? Detailed process simulations make it possible to derive correlations for the specific application.

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Process regimes for metals

If metal becomes very hot, locally, during powder bed fusion (PBF-LB/M), a gas phase can form. Due to volume expansion and gas pressure during this phase transition, so-called deep penetration welding occurs. If gas transition is avoided and the molten pool is shallow, this is referred to as heat conduction welding. How these process regimes depend on material properties and process parameters as well as the avoidance of an unstable weld pool and splatter needs to be understood.

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Avoiding defects

Melt pool shape depends on laser parameters and thermophysical material properties. It can be elongated along the laser direction movement and deeply protrude. It is important for component strength that the melt pool at least partially covers the previously melted and resolidified powder layer to ensure good bonding. The detailed influences of laser and material parameters on layer bonding and minimizing defects such as pores or cracks needs to be addressed.

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Optimizing the microstructure

Temperature curve has a significant influence on vocational training of metallic microstructures. Fineness and anisotropy of the microstructure in turn determines mechanical component properties. Influence of specific process parameters (e.g. laser power, scanning speed, layer thickness) on the microstructure, controlling grain size and orientation, and reducing anisotropy in mechanical properties caused by the layer structure must be understood.

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Wetting and debinding

During binder jetting, binder droplets hit the powder bed and wet powder particles. Concerns include the influence particle size distribution, binder viscosity, temperature and contact angle have on wetting, which parameters determine resolution and accuracy of the printed part, the effects that particle size and distribution of powder have on print quality and what strategies exist to reduce warping and cracking during debinding and sintering.

Examples of Projects

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Overview of the complete simulation chain: from left to right, shown are the powder application, the melting by the laser, the formation of the microstructure and the determination of mechanical properties.

Accurate simulation of laser powder bed fusion from powder deposition to the microstructure of the component

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.

  • Bierwisch, C.; Butz, A.; Dietemann, B.; Wessel, A.; Najuch, T.; Mohseni-Mofidi, S.:, PBF-LB/M multiphysics process simulation from powder to mechanical properties, Procedia CIRP 111 (2022) 37-40 Link
  • Dietemann, B.; Najuch, T.; Mohseni-Mofidi, S.; Wessel, A.; Butz, A.; Bierwisch, C., Simulation of the laser powder bed fusion process with a holistic workflow, Fraunhofer Direct Digital Manufacturing Conference DDMC 2023; Müller, B. (ed.); Fraunhofer Verlag, Stuttgart (2023) 6 pages Link
  • Bierwisch, C.; Dietemann, B.; Najuch, T., Accurate laser powder bed fusion modeling using ISPH, Proceedings of the 17th SPHERIC International Workshop; Fourtakas, G. (Ed.); University of Manchester, Manchester, UK (2023) 255-26 Link
  • Bierwisch, C.; Butz, A.; Dietemann, B.; Najuch, T., Multiphysics simulation of laser powder bed melting with mesoscopic models, Foundry 9 (2023) 22-27 Link

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Simulation des Pulverbettschmelzens: Ein Laser fährt von links nach rechts über das Pulver und schmilzt es auf. Über die Zeit sieht man von oben nach unten die allmähliche Abkühlung und Verdichtung des Materials.

Prozessfenster für das Pulverbettschmelzen von Polymeren


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.

  • Bierwisch, C.; Mohseni-Mofidi, S.; Dietemann, B.; Grünewald, M.; Rudloff, J.; Lang, M., Universal process diagrams for laser sintering of polymers, Materials & Design 199 (2021) Art. 109432, 15 Seiten Link
  • Grünewald, M.; Popp, K.; Rudloff, J.; Lang, M.; Sommereyns, A.; Schmidt, M.; Mohseni-Mofidi, S.; Bierwisch, C., Experimental, numerical and analytical investigation of the polyamide 12 powder bed fusion with the aim of building dimensionless characteristic numbers, Materials & Design 201 (2021) Art. 109470, 11 Seiten Link
  • Bierwisch, C.; Mohseni-Mofidi, A.; Dietemann, B.; Kraft, T.; Rudloff, J.; Lang, M., Particle-based simulation, dimensional analysis and experimental validation of laser absorption and thermo-viscous flow during sintering of polymers, Procedia CIRP 94 (2020) 74-79 Link
  • Rudloff, J.; Lang, M.; Mohseni-Mofidi, S.; Bierwisch, C., Experimental investigations for improved modelling of the laser sintering process of polymers, Procedia CIRP 94 (2020) 80-84 Link

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Distribution of powder particles (gray) within the installation space with the help of a roller (yellow). The series of images shows the progress of the simulation from top to bottom.

Simulation of powder application



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.

  • Bierwisch, C., Particle-based simulations of melting and solidification dynamics in powder bed processes, in Tagungsband DGM-Fachtagung Werkstoffe und Additive Fertigung; Hoyer, P.; Leyens, C.; Niendorf, T.; Ploshikhin, V.; Schulze, V.; Witt, G. (Eds.); Deutsche Gesellschaft für Materialkunde e.V., Sankt Augustin (2018) 134-139 Link
  • Bierwisch, C., DEM powder spreading and SPH powder melting models for additive manufacturing process simulations, VI International Conference on Particle-Based Methods. Fundamentals and Applications - PARTICLES 2019; Oñate, E.; Wriggers, P.; Zohdi, T.; Bischoff, M.; Owen, D.R.J. (Eds.); Artes Gráficas Torres S.L., Cornellà de Llobregat, Spain (2019) 434-443 Link
  • Bierwisch, C.; Kraft, T.; Riedel, H.; Moseler, M.; Three-dimensional discrete element models for the granular statics and dynamics of powders in cavity filling; Journal or the Mechanics and Physics of Solids 57/1 (2009) 10-31 Link

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Predicted distortion of a component after the sintering process.

Optimization of the design for sinter-based AM processes


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.

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Extrusion of a continuous strand from a controllable nozzle.

Influence of rheology on the printing behavior during material extrusion

 

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. 

  • Dietemann, B.; Bosna, F.; Lorenz, M.; Travitzky, N.; Kruggel-Emden, H.; Kraft, T.; Bierwisch, C., Modeling robocasting with smoothed particle hydrodynamics: Printing gap-spanning filaments, Additive Manufacturing 36 (2020) Art. 101488 1-9 Link
  • Dietemann, B.; Kraft, T.; Kruggel-Emden, H.; Bierwisch, C., A Smoothed Particle Hydrodynamics scheme for arbitrarily shaped rigid bodies within highly viscous fluids, Journal of Computational Physics: X 8 (2020) Art. 100068, 25 pages Link
  • Lorenz, M.; Dietemann, B.; Wahl, L.; Bierwisch, C.; Kraft, T.; Kruggel-Emden, H.; Travitzky, N., Influence of platelet content on the fabrication of colloidal gels for robocasting: Experimental analysis and numerical simulation, Journal of the European Ceramic Society 40 (2020) 811-825 Link
  • Dietemann, B.; Bosna, F.; Lorenz, M.; Travitzky, N.; Kruggel-Emden, H.; Kraft, T.; Bierwisch, C., Numerical study of texture in material extrusion: Orientation in a multicomponent system of spheres and ellipsoids, Journal of Non-Newtonian Fluid Mechanics 291 (2021) Art. 104532 Link
  • Dietemann, B.; Bosna, F.; Kruggel-Emden, H.; Kraft, T.; Bierwisch, C., Assessment of analytical orientation prediction models for suspensions containing fibers and spheres, Journal of Composites Science 5/4 (2021) Art. 107, 18 pages Link
  • Dietemann, B.; Wahl, L.; Travitzky, N.; Kruggel-Emden, H.; Kraft, T.; Bierwisch, C., Reorientation of suspended ceramic particles in robocasted green filaments during drying, Materials 15/6 (2022) Art. 2100, 20 pages Link
  • Dietemann, B.; Bierwisch, C., Predicting particle orientation: Is an accurate flow field more important than the actual orientation model?, Journal of Non-Newtonian Fluid Mechanics 310 (2022) Art. 104927, 12 pages Link

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