Metal Powder Bed Fusion Research Articles

A consistent diffuse-interface model for two-phase flow problems with rapid evaporation

AbstractWe present accurate and mathematically consistent formulations of a diffuse-interface model for two-phase flow problems involving rapid evaporation. The model addresses challenges including discontinuities in the density field by several orders of magnitude, leading to high velocity and pressure jumps across the liquid–vapor interface, along with dynamically changing interface topologies. To this end, we integrate an incompressible Navier–Stokes solver combined with a conservative level-set formulation and a regularized, i.e., diffuse, representation of discontinuities into a matrix-free adaptive finite element framework. The achievements are three-fold: First, we propose mathematically consistent definitions for the level-set transport velocity in the diffuse interface region by extrapolating the velocity from the liquid or gas phase. They exhibit superior prediction accuracy for the evaporated mass and the resulting interface dynamics compared to a local velocity evaluation, especially for strongly curved interfaces.Second, we show that accurate prediction of the evaporation-induced pressure jump requires a consistent, namely a reciprocal, density interpolation across the interface, which satisfies local mass conservation. Third, the combination of diffuse interface models for evaporation with standard Stokes-type constitutive relations for viscous flows leads to significant pressure artifacts in the diffuse interface region. To mitigate these, we propose to introduce a correction term for such constitutive model types. Through selected analytical and numerical examples, the aforementioned properties are validated. The presented model promises new insights in simulation-based prediction of melt–vapor interactions in thermal multiphase flows such as in laser-based powder bed fusion of metals.

A Perspective on Powder Metallurgy and Additive Manufacturing of High‐Nitrogen Alloyed Stainless Steels

Incorporating nitrogen as an alloying element in stainless steels can significantly enhance their mechanical and chemical properties. However, the limited solubility of nitrogen, particularly in the liquid phase, presents challenges. This perspective article explores an innovative powder metallurgical approach to producing high‐nitrogen steels (HNS) by utilizing a mixture of stainless steel and Si3N4. This mixture undergoes hot isostatic pressing (HIP) followed by direct quenching, facilitating diffusion alloying, and solution annealing in a single step. The article also examines adapting this method to powder bed fusion of metals using a laser beam (PBF‐LB/M) to overcome nitrogen solubility limits, which currently constrain the achievable nitrogen content in PBF‐LB/M‐manufactured stainless steels. The approach aims to retain Si3N4 particles within the matrix during PBF‐LB/M to enrich the steel with nitrogen during subsequent HIP. However, laser interaction with Si3N4 can lead to nitrogen loss, prompting an alternative strategy: a shell–core structure based on a gas‐tight shell enclosing loose Si3N4 particles. These particles dissolve during HIP, enriching the matrix with nitrogen and enabling the production of HNS. This article highlights the potential for extending this approach to other stainless steel groups, broadening the possibilities for HNS production through both conventional HIP and PBF‐LB/M manufacturing routes.

Tailored microstructure in laser-based powder bed fusion of IN718 through novel beam shaping technology

Inconel 718, processed by Laser-based Powder Bed Fusion of Metals (PBF-LB/M), exhibits epitaxial dendrite growth, leading to an anisotropic columnar microstructure. While columnar microstructures offer creep resistance, equiaxed microstructures provide more balanced mechanical properties. Understanding how to tailor the as-built microstructure in the PBF-LB/M process remains a persistent challenge. Recent advancements in beam shaping offer solutions for customizing heat flow direction in the PBF-LB/M process and tailoring the as-built microstructure. This research aims to systematically study how the laser beam shape affects anisotropy in the as-built microstructure and tensile mechanical properties. By using an inverse calculated beam shape, called as chair-shaped, the texture strength represented by J-index was reduced from 4.6 (generated by a ring-shaped beam profile with the same beam intensity and laser process parameters) to 1.37. The study prioritizes high productivity, with a building rate of 16 mm3/s (80 μm layer thickness) across chosen process parameters compared to state-of-the-art with a build rate of 4.2 mm3/s (40 μm layer thickness). The findings indicate that rotational asymmetric laser beam profiles with a relative beam diameter of 400 μm significantly enhance productivity by broadening the process window. These profiles also have a profound impact on the microstructure and tensile properties compared to ring-shaped and core-ring laser beam profiles. The new microstructure features a notable reduction in grain size, elongation, and texture index, producing mechanical properties that are comparable to those of an isotropic microstructure.

Effect of powder properties, process parameters, and recoating speed on powder layer properties measured by in-situ laser profilometry and part properties in laser powder bed fusion

In laser-based powder bed fusion of metals (PBF-LB/M), the powder layer is the link between the powder properties and the resulting part quality. Powder layer quality is a key metric related to powder spreadability and ultimately part quality, yet it is still unclear how it can be quantified. This is due to the difficulty of studying powder layer properties during the process. This study investigates the influence of powder properties, process parameters, and recoating speed on the surface roughness of the powder layer and the part, as well as on the effective thickness of the powder layer and solidified layer, and the resulting relative part density. Utilizing in-situ laser profilometry, high-resolution topographical data of the powder layer and the part surface were acquired, with minimal interference to the PBF-LB/M process. Six AlSi10Mg powders with varying particle size distribution, morphology, and flowability were processed using a wide range of recoating speeds and scan speeds to create powder layers with a wide range of properties. The results reveal a strong correlation between energy input and the effective powder layer thickness where lower scan speed results in an increased effective powder layer thickness due to material losses. Additionally, faster recoating decreases the powder layer density, which is moderated by the median particle size where the effect is strongest for fine powders. The surface roughness of the powder layer and top part surface are influenced by the recoating speed, energy input, and particle size, and they are strongly linked to each other. This highlights the importance of considering realistic substrate surface roughnesses in both powder spreading experiments and simulations. Finally, layer properties affect the process stability, resulting in small differences in relative part density.

Adaptive slicing in powder bed fusion of metals using a laser beam—Investigation on productivity, laser absorption, geometrical accuracy, and thermal conditions

Powder bed fusion of metals using a laser beam (PBF-LB/M acc. to DIN EN ISO/ASTM 52900) has reached market maturity. In addition to developing new materials and enabling new applications, the industry focuses on increasing productivity and reducing costs. In this context, increasing the layer thickness can increase productivity but often leads to a deterioration of surface quality and part density. Using variable layer thicknesses depending on the manufactured geometry is well-known from filament-based material extrusion processes and is called adaptive slicing. This study investigates the manufacturing aspects of adaptive slicing using AlSi10Mg. Laser beam reflectance of the different powder layer thicknesses is quantified using diffuse reflectance infrared Fourier transform spectroscopy. The process window is identified and analyzed, focusing on the achievable productivity and required energy input. Furthermore, the suitability of layer thicknesses and processing parameters is analyzed by measuring the dimensional accuracy and process stability of overhanging structures. Heat input, heat dissipation, and potential heat-up are investigated and compared to conventional processes using part-scale thermal simulations. In this study, parameters are developed for layer thicknesses of 120 μm with an almost threefold increase in productivity in nonoverhanging structures with a part density above 99.7%. Further, adaptive slicing can increase productivity in PBF-LB/M while decreasing the impact on part quality. Future work will focus on automated algorithms to optimize and automize adaptive slicing.

Boosting Coercivity of 3D Printed Hard Magnets through Nano-Modification of the Powder Feedstock.

The demand for strong, compact permanent magnets essential for the energy transition drives innovation in magnet manufacturing. Additive manufacturing, particularly Powder Bed Fusion of metals using a laser beam (PBF-LB/M), offers potential for near-net-shaped Nd-Fe-B permanent magnets but often falls short compared to conventional methods. A less explored strategy to enhance these magnets is feedstock modification with nanoparticles. It is demonstrated that modifying a Nd-Fe-B-based feedstock with 1wt.%Ag nanoparticles boost the coercivity of the magnets to a record value of 935±6kAm-1 without further post-processing or heat treatments. Suitable volumetric energy densities for the PBF-LB/M process are determined using finite element simulations predicting melt pool behavior and part density. Microstructural analyses reveal finer grain sizes and more equiaxed nanocrystalline structures due to the modification. Atom probe tomography identifies three phases in the Ag-modified samples, with Ag forming nanophase regions with rare-earth elements near the amorphous Zr-Ti-B-rich intergranular phase, potentially decoupling the Nd2Fe14B primary phase. The study shows that superior magnetic properties primarily result from microstructure modification rather than part density. These findings highlight inventive material design approaches via feedstock surface modification to achieve superior magnetic performance in additively manufactured Nd-Fe-B magnets.

Empirical estimation of metal powder bed fusion technological improvement rate

AbstractThis study empirically estimates the technological improvement rate (TIR) of metal powder bed fusion (PBF) technology, widely used in aerospace, automotive, and medical industries. PBF's continuous long-term adoption growth is driven by its ability to enhance manufacturing efficiency in terms of time and raw material use, as well as its capability to produce high-quality, high-strength, complex-shaped parts. Measuring the technological development of PBF is crucial as itis enlarging its application domain and is increasingly considered a viable alternative to traditional manufacturing technologies across a broader range of applications. We resorted to the literature to collect information and assess which technical parameters are most relevant to measure the capabilities of PBF. With those, we established an ideal functional performance metric (FPM) capable of comprehensively assessing PBF's technological performance improvement. Considering all available data sources and PBF machines ever made commercially available, a data set of technical parameters was constructed. This was followed by a data curation process focusing on data availability and reliability. The resultant practical FPM was used to estimate the TIR of PBF technology. By employing regression analysis, we estimate a yearly improvement of 26.8%. This empirical rate comes as a more accurate and reliable substitute to the previously indirectly estimated patent-derived rate of 33.3%. Our findings underscore PBF's capability of keeping pace with its growing significance and wider industrial applications. The results of this study provide a key metric for those in the industry and research, confirming the rapid performance growth and establishing a standard for future industrial uses.

Temperature measurement in laser–metal processing using optical sensing: Radiometric calibration and validation of a multispectral camera

In laser–metal processing such as Laser-based Powder Bed Fusion of Metals (PBF-LB/M), the quality of the final product is significantly influenced by the thermal behaviour of the melt pool. Accurate temperature measurements are challenging due to high temperature gradients and rapid cooling. This study introduces Multispectral Imaging (MSI) as a highly effective thermometry technique to address these demanding conditions. MSI captures multiple bands of radiation, enabling the simultaneous determination of absolute temperature and surface emissivity. This capability is crucial for ensuring high-quality outcomes in laser–metal processing such as PBF-LB/M, contingent upon robust radiometric calibration.To enhance reliability, two radiometric calibration models were developed: an empirical model based on linear sensor data correlations and an analytical model leveraging sensor behaviour. An efficient calibration was found for both models across a range of signal-to-noise ratios in the black body calibrator, where the analytical model even performs robust under a high noise level.Additionally, the temperature accuracy in the solid-state case was tested with a thermo-mechanical simulator. Results showed that the empirical and analytical models achieved mean relative errors of 2.0% and 1.6%, respectively, outperforming the state-of-the-art. Further, laser irradiation experiments highlighted the analytical model’s ability to accurately determine the emissivity decrease during the solid-to-liquid transition, allowing for accurate melt pool temperature estimations. Conversely, the empirical model struggled to estimate temperature effectively in the liquid phase.This study not only proposed a robust methodology of MSI in temperature measurement but also confirmed the accuracy and reliability of the system, broadening the scope for further investigation into the intricate thermal dynamics involved in laser–metal interactions.

Simulation-assisted prediction of residual stress-induced failure during powder bed fusion of metals using a laser beam

Simulation-assisted prediction of residual stress-induced failure during powder bed fusion of metals using a laser beam

Enhancing the efficiency of laser-based powder bed fusion of metals through the use of localized and vertically directed shielding gas flow

Enhancing the efficiency of laser-based powder bed fusion of metals through the use of localized and vertically directed shielding gas flow

The Dispersion-Strengthening Effect of TiN Nanoparticles Evoked by Ex Situ Nitridation of Gas-Atomized, NiCu-Based Alloy 400 in Fluidized Bed Reactor for Laser Powder Bed Fusion

Throughout recent years, the implementation of nanoparticles into the microstructure of additively manufactured (AM) parts has gained great attention in the material science community. The dispersion strengthening (DS) effect achieved leads to a substantial improvement in the mechanical properties of the alloy used. In this work, an ex situ approach of powder conditioning prior to the AM process as per a newly developed fluidized bed reactor (FBR) was applied to a titanium-enriched variant of the NiCu-based Alloy 400. Powders were investigated before and after FBR exposure, and it was found that the conditioning led to a significant increase in the TiN formation along grain boundaries. Manufactured to parts via laser-based powder bed fusion of metals (PBF-LB/M), the ex situ FBR approach not only revealed a superior microstructure compared to unconditioned parts but also with respect to a recently introduced in situ approach based on a gas atomization reaction synthesis (GARS). A substantially higher number of nanoparticles formed along cell walls and enabled an effective suppression of dislocation movement, resulting in excellent tensile, creep, and fatigue properties, even at elevated temperatures up to 750 °C. Such outstanding properties have never been documented for AM-processed Alloy 400, which is why the demonstrated FBR ex situ conditioning marks a promising modification route for future alloy systems.

Efficient sensitivity analysis of the thermal profile in powder bed fusion of metals using hypercomplex automatic differentiation finite element method

Rapid cyclic temperature fluctuation occurring in powder bed fusion of metals using a laser beam (PBF-LB/M) influences the formation of flaws in printed parts. Consequently, there is a pressing need to enhance the quality of printed parts by developing innovative methodologies that can predict thermal histories and help uncover the intricate relationships between process parameters and thermal profiles. Sensitivity Analysis (SA) emerges as an essential tool for this, offering the potential for process optimization and enhanced quality control. Nonetheless, conventional SA methodologies often incur in excessive computational costs and potential numerical approximation errors. To address this technical challenge, we present a novel method for SA that integrates the HYPercomplex-based Automatic Differentiation (HYPAD) technique with transient thermal simulations conducted via the finite element method (FEM). Leveraging this methodology, we efficiently and accurately perform SA for PBF-LB/M processes in a post-processing step. Compared to traditional methods like Finite Differences (FD), HYPAD-FEM required 96 % less computational time for obtaining sensitivities for 22 process parameters, under a comparative study conducted within the context of the 2018–02 AM benchmark of the National Institute of Standards and Technology. In summary, HYPAD-FEM offers superior efficiency and accuracy in SA over conventional methods, delivering the best sensitivity of a model without the need for step-size selection and problem or parameter-based implementations.

Prediction of spatter-related defects in metal laser powder bed fusion by analytical and machine learning modelling applied to off-axis long-exposure monitoring

Laser powder bed fusion of metals is increasingly used for fabricating complex parts requiring good mechanical properties. Simultaneously, researchers in the field are intensifying the efforts to reduce defects, such as internal porosities, which hinder a wider industrial adoption of this technology, urging process monitoring to a pivotal role in defect identification and mitigation. Therefore, understanding the correlation between in-process monitoring signals and post-process actual defects is fundamental to taking informed decisions and potential corrective actions during the process.This work focuses on developing models to predict spatter-related defects from specific process signatures detected through off-axis long-exposure imaging. Layer-wise images were properly aligned with corresponding cross-sections from tomographic reconstructions to investigate the relationship between spatter-related signatures and actual defects measured by X-ray computed tomography. This relationship was used as a knowledge basis to develop an analytical image-processing approach and a machine learning-based methodology, which were then compared in terms of their correlation performances. The advantages and limitations of both methods are discussed in the paper.Both approaches led to promising results in the prediction of lack-of-fusion defects caused by spatters, with the machine learning approach showing a prediction accuracy in the order of 90% for defects with equivalent diameter above 90µm, while the analytical model needed equivalent diameters larger than 130µm to reach a prediction accuracy in the order of 80%. Furthermore, the machine learning method led to strong results regarding early defect detection, with most of the investigated defects properly predicted by analysing two consecutive layers after the signature detection.

Towards bespoke gas permeability by functionally graded structures in laser-based powder bed fusion of metals

Permeable, media transporting, components are an integral part in numerous technical applications. In gas turbines combustors, for example, gaseous oxidizer and fuel are transported separately into the burner, where they are injected and mixed, and subsequently combusted. The mixture homogeneity strongly affects the combustion performance and emissions formation and is, amongst other, determined by the spatial distribution of fuel injection ports. In this context, porous media provide the limiting case for a spatial distribution of media-injecting pores, yet is typically associated with a high pressure drop that yields a loss in efficiency. In this study, possibilities of achieving gas permeability in additively manufactured porous structures are investigated. The objective is to selectively functionalize the permeable layers for gaseous media supply with low pressure loss and, when needed, enable a targeted mixing of different gas streams. For this purpose, a laser-based powder bed fusion process (PBF-LB/M) was used in this study. It offers the opportunity to manufacture varying porosities inside complex monolithic metal parts. To produce the porous structures and to achieve gas permeability, the effect of scan rotation angle, hatch distance, build-up direction and length of the porous specimen is investigated. Due to the high temperatures present in combustion systems, the present work utilizes Inconel 718 material. The AM gas permeable specimen are experimentally characterized by means of surface topography, micro X-ray computed tomography (µXRCT) as well as flow and pressure loss test. The results show, that the AM process parameter provide effective control parameters to adjust the permeability. The strongest effect originates from the hatch distance for a given build-up direction. Depending on the scan rotation, the flow transitions from a turbulent pipe flow to a Darcy flow as present in conventional porous media. A structured alignment and connectivity of pores can be realized as evident in the µXRCT results, surface topography and the flow measurements. Residual powder, powder adhering to the pore walls and stochastic closure of pores or channels lead to deviations and need to be considered when designing respective parts. Nonetheless, the results further show that a directional dependence of the permeability and the build-up direction can be realized and controlled. Consequently, when considering the AM build-strategy in the design of components, this directed permeability can be functionalized in the generation of gas transporting and gas mixing layers separately by adjusting the AM processing parameter.

Support structure topology optimization considering the residual distortion for laser powder bed fusion metal additive manufacturing

Support structure topology optimization considering the residual distortion for laser powder bed fusion metal additive manufacturing

In-line process monitoring in laser welding and powder bed fusion of metals using directional reflection measurements

In-line process monitoring in laser welding and powder bed fusion of metals using directional reflection measurements

Applying systems engineering principles to develop an open source laser based metal powder bed fusion system

Purpose Conventional powder bed fusion systems, with their high costs, proprietary nature and restrictive fees, limit research opportunities. This study aims to unveil an affordable, open-source hardware, open-source software laser-based metal powder bed fusion system. Recognizing the distinction between DIY and open-source hardware is crucial for widespread acceptance. Design/methodology/approach The authors present a comprehensive system architecture using object process methodology for functions and architecture, a design structure matrix to model system dependencies and classical technical drawing exploded views for select subsystems. Modularization enables high adaptability, fostering potential adoption. Findings The fully open system enables unrestricted research, mirroring common industrial metal laser-based powder bed fusion (L-PBF) systems. While “open” systems are available for purchase, they remain closed-source, lacking source code and technical drawings sharing, hindering contribution and co-development. The authors’ is the pioneering and sole open-source metal L-PBF system, boasting 1,500+ print hours. A series of industrial and academic adopters are currently implementing the system. Originality/value The open system, slicer software and controller offer unique process control, supporting multimaterial printing. The authors shared the design on the OpenAM GitHub page under the CERN-OHL-P v2 Open Source Hardware license. While it is functional for additive manufacturing (e.g. aluminum, tool steel, titanium and stainless steel), the entire process chain is actively evolving, ideal for co-development with the additive manufacturing community.

Investigations on the Heat Balance of the Melt Pool during PBF-LB/M under Various Process Gases

During the powder bed fusion of metals using a laser beam (PBF-LB/M), an inert atmosphere is maintained in the build chamber to avoid reactions of the liquid metal with ambient air leading to the creation of oxides or nitrides, which alter the mechanical properties of the processed part. A continuous gas flow is guided over the process zone to remove spatters and fumes. This flow induces a convective heat transfer from the molten metal to the gas, which, depending on the level of the heat flow, may alter the melt pool dimensions by influencing the cooling rate. The present work investigated these phenomena with single-line trials, both experimentally and numerically. For this reason, a smoothed-particle hydrodynamics model was utilized to investigate the temperatures of the melt pool, cooling rates, and the integral heat balance with various gas atmospheres. In parallel, an on-axis pyrometer was set up on an experimental PBF-LB/M machine to capture the surface emissions of the melt pool. The atmosphere in the simulations and experiments was varied between argon, helium, and two mixtures thereof. The results showed a slight increase in the cooling rates with an increasing fraction of helium in the process gas. Consistently, a slight decrease in the melt pool temperatures and dimensions was found.

Local porosity prediction in metal powder bed fusion using in-situ thermography: A comparative study of machine learning techniques

The formation of flaws such as internal porosity in parts produced by Metal-based Powder Bed Fusion with Laser Beam (PBF-LB/M) significantly hinders its broader industrial application, as porosity can potentially lead to part failure. Addressing this issue, this study explores the efficacy of in-situ thermography, particularly short-wave infrared thermography, for detecting and predicting porosity during manufacturing. This technique is capable of monitoring the part’s thermal history which is closely connected to the flaw formation process. Recent advancements in Machine Learning (ML) have been increasingly leveraged for porosity prediction in PBF-LB/M. However, previous research primarily focused on global rather than localized porosity prediction which simplified the complex prediction task. Thereby, the opportunity to correlate the predicted flaw position with expected part strain to judge the severity of the flaw for part performance is neglected. This study aims to bridge this gap by studying the potential of SWIR thermography for predicting local porosity levels using regression models. The models are trained on data from two identical HAYNES®282® specimens. We compare the effectiveness of feature-based and raw data-based models in predicting different porosity types and examine the importance of input data in porosity prediction. We show that models trained on SWIR thermogram data can identify systematic trends in local flaw formation. This is demonstrated for forced flaw formation using process parameter shifts and, moreover, for randomly formed flaws in the specimen bulk. Furthermore, we identify features of high importance for the prediction of lack-of-fusion and keyhole porosity from SWIR monitoring data.

Influence of Laser-Based Powder Bed Fusion of Metals Process Parameters on the Formation of Defects in Al-Zn-Mg-Cu Alloy Using Path Analysis.

High-strength aluminium alloys are prone to porosity and cracking during laser-based powder bed fusion of metals (PBF-LB/M) due to the complex solidification behaviour, thus limiting the preparation of high-quality aluminium alloys. In order to effectively reduce the defect formation, this study investigated the influence mechanism of different process parameters on the formation of porosity and cracks in Al-Zn-Mg-Cu alloys in the PBF-LB/M process by combining experimental and numerical simulation. The degree of influence of the process parameters on the temperature field and the temperature field on the defect formation was also quantified using path analysis. The results show that modulation of the process parameters can effectively reduce the formation of cracks and pores, although it is difficult to eliminate them. The melt pool temperature has a significant effect on the formation of porosity, and the temperature gradient has a significant effect on the formation of cracks. The degree of influence of laser power on the melt pool temperature and temperature gradient was greater than that of scanning speed, with values of 0.980 and 0.989, respectively. Therefore, the priority of modulating the laser power is higher than that of scanning speed in order to reduce the formation of defects more effectively.