Powder Bed Fusion Process Research Articles

Comprehensive numerical investigation of laser powder bed fusion process conditions for bulk metallic glasses

The successful application of laser powder bed fusion (PBF-LB/M) for fabricating bulk metallic glass (BMG) parts heavily relies on the development of effective process strategies. An optimal process strategy for BMGs is required to go beyond manufacturing defect-free parts and address the critical aspect of minimizing crystallization. However, traditional trial-and-error experimental methods for process development are time-consuming and costly. This paper uses an in-house developed simulation software, SAMPLE2D, to systematically explore PBF-LB/M process conditions for BMGs, with the Zr-based glass-forming alloy Zr59.3Cu28.8Al10.4Nb1.5 (at.%, trade name: AMZ4, AMLOY-ZR01) as an example. We uncover that BMG crystallization during PBF-LB/M is a localized phenomenon, primarily induced by short-range in-situ heat treatment. We comprehensively explore process conditions, encompassing laser beam-related parameters (beam power, speed, diameter, and line offset), as well as powder bed-related parameters (powder layer thickness, preheating temperature, and oxygen level of AMZ4). Leveraging insights derived from the parameter study, we delve into innovative scanning strategies. Various scanning strategies are explored, including line jumping, adding waiting times, translating the scan pattern, and rotating the scan pattern. Remarkably, our findings highlight line jumping as a highly effective scanning strategy to reduce crystallization while maintaining relative density. While either layer-wise translation or non-180° rotation of the scan pattern is generally not recommended, when focusing solely on consolidation and crystallization aspects. This study not only provides an in-depth understanding of how PBF-LB/M process conditions shape the properties of BMG parts, but also offers a fresh perspective on applying PBF-LB/M technology in BMG part production.

Energy absorption of AlSi10Mg origami cellular structures fabricated via laser powder bed fusion

We experimentally study the energy absorption of metallic origami cellular structures additively manufactured from an AlSi10Mg alloy. We fabricate AlSi10Mg origami using the laser powder bed fusion (L-PBF) process. Since the as-fabricated AlSi10Mg has limited elongation at break, we systematically examine the heat treatment conditions and achieve the large deformation (i.e., wide folding range) of AlSi10Mg origami without fracture of origami creases. In addition, we use a drop tower impact system to demonstrate the effectiveness of AlSi10Mg origami’s folding behavior for impact energy absorption. Based on our experimental results, AlSi10Mg origami cellular structures could be exploited to develop a highly efficient lightweight impact absorber.Graphical abstract

Microstructure and Mechanical Properties of a Novel Al-Mg-Sc-Ti Alloy Fabricated by Laser Powder Bed Fusion.

(TiH2 + ScH3)/Al-Mg composite powders with different Ti contents were produced by ball milling. These composite powders were fabricated to cube and cuboid shape samples via a laser powder bed fusion process with optimal processing parameters. The TiH2 and ScH3 particles underwent dehydrogenation during the laser powder bed fusion process, and these composite powders ultimately formed Al-Mg-Sc-Ti alloys. The relative density, printability, microstructure, hardness and tensile properties of these alloy samples were investigated. The results show that these Al-Mg-Sc-Ti alloys have lower hot-crack sensitivity, having fine equiaxed grains. An Al18Mg3(Ti,Sc)2 intermetallic phase and in situ L12-Al3(Sc,Ti) precipitations formed during the laser powder bed fusion process, which is beneficial for nucleation and dispersion strengthening. The ultimate tensile strength of the Al-Mg-0.7Sc-1.0Ti alloy was 313.6 MPa with an elongation of 6.6%. During the hot isostatic pressing treatment, most of the Mg element precipitated from the matrix and changed the Al3(Sc,Ti) into a Al18Mg3(Ti,Sc)2 precipitate completely. The Al-Mg-Sc-Ti alloys were nearly fully dense after the hot isostatic pressing treatment and exhibited better mechanical properties. The ultimate tensile strength of the Al-Mg-0.7Sc-1.0Ti was 475 MPa with an elongation of 8.5%.

Influence of the LPBF Process Parameters on the Porosity of the AlSi10Mg Alloy

Abstract: Laser powder bed fusion (LPBF) process has a great ability to produce complex AlSi10Mg 3D components with uncommon degrees of freedom for broad span of applications in different industries. Presence of the microstructural imperfections such as porosity, dependent on the parameters of the process can be detrimental to the printed products for different engineering applications. Parameters of the process and different post-processing heat and surface treatments are recognized for decrease of the occurrence of microstructural defects and for the improvement of the mechanical properties. The influence of laser power by applying four different laser speeds at one layer thickness with a constant hatch distance, on the microstructure and microhardness of the AlSi10Mg alloy was examined in this paper. The goal of the research was to determine whether increasing the laser speed will have a significant impact on the change in microstructure and the appearance of porosity in the tested samples.

Electromagnetic Characterization of Silicon–Iron Additively Manufactured Cores for Electric Machines

This paper deals with the electromagnetic characterization of a laminated toroidal ferromagnetic core made through additive manufacturing, specifically using the laser powder bed fusion process. The continuing demand for increasingly efficient, lightweight, and higher performance electric machines is creating huge challenges in the design and realization of new electric motor solutions. The constant improvements in additive manufacturing technologies have prompted researchers to investigate the possibility of adopting these production techniques for the manufacture of high-value electric motors. For these reasons, this paper investigates the ferromagnetic characteristics of an additively manufactured core made with FeSi6.5 powder. The BH curve and the specific iron losses of the processed material have been measured so that they can be compared with a commercial lamination, and have the possibility of carrying out more precise finite element simulations.

Influence of laser powder bed fusion process on microstructures and low cycle fatigue performance of Invar 36 alloy

Influence of laser powder bed fusion process on microstructures and low cycle fatigue performance of Invar 36 alloy

A strong fracture-resistant high-entropy alloy with nano-bridged honeycomb microstructure intrinsically toughened by 3D-printing

Strengthening materials via conventional “top-down” processes generally involves restricting dislocation movement by precipitation or grain refinement, which invariably restricts the movement of dislocations away from, or towards, a crack tip, thereby severely compromising their fracture resistance. In the present study, a high-entropy alloy Al0.5CrCoFeNi is produced by the laser powder-bed fusion process, a “bottom-up” additive manufacturing process similar to how nature builds structures, with the microstructure resembling a nano-bridged honeycomb structure consisting of a face-centered cubic (fcc) matrix and an interwoven hexagonal net of an ordered body-centered cubic B2 phase. While the B2 phase, combined with high-dislocation density and solid-solution strengthening, provides strength to the material, the nano-bridges of dislocations connecting the fcc cells, i.e., the channels between the B2 phase on the cell boundaries, provide highways for dislocation movement away from the crack tip. Consequently, the nature-inspired microstructure imparts the material with an excellent combination of strength and toughness.

Effects of base plate temperature on microstructure evolution and high-temperature mechanical properties of IN718 processed by laser powder bed fusion using simulation and experiment

Base plate preheating is a relatively new strategy to influence the mechanical properties and microstructure of IN718. Base plate preheating was studied to reduce Niobium (Nb) segregation in the interdendritic region of IN718 superalloy and to improve mechanical properties through the laser powder bed fusion (L-PBF) process. Here, we compared experimental results for high-temperature (650℃) mechanical properties of specimens built with 200℃ (PH200) and 600℃ (PH600) preheated base plates. The as-built PH200 and PH600 specimens had relatively similar grain morphologies and orientations along the building direction. The PH200 specimen showed a cellular structure and higher Nb segregation at the interdendritic region, whereas the PH600 specimen had a dendritic structure and lower Nb segregation. The lower amount of Nb segregation in the PH600 specimen is mainly because of the cooling rate difference between specimens during the L-PBF process. The PH600 specimen exhibited slightly better tensile properties, longer creep life, and elongation than the PH200 specimen in both the as-built and heat-treated conditions. These differences mainly occurred due to differences in Laves and δ-phase fractions between the PH200 and PH600 specimens. The simulation result indicates that the temperature distribution in the block remains relatively uniform during the building process.

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion.

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

Influence of processing parameters on the corrosion resistance of additively manufactured nitinol parts for biomedical applications

The usefulness of additively manufactured (AM) nitinol and Ti6Al4V parts for the aerospace, automotive, machine and tooling, and biomedical industries depends on how well they withstand corrosion. AM is a manufacturing process that makes it possible to create intricate geometries at a reasonable price. Although significant progress has been made in decreasing metal corrosion, not much research has been done on optimizing input processing parameters to lower corrosion rates. Unique phase structures and preferential evaporation of alloying components might arise because of the melting and quick re-solidification that take place during additive manufacturing. This study looks at how processing parameter changes impact the metal parts made by laser-powder bed fusion (L-PBF) in terms of their ability to resist corrosion in a bodily environment. Electrochemical testing was used to conduct the research at a body temperature of 37 °C in both Hanks and Ringers solutions. The findings suggest that an increase in laser power during AM improves the passivation layer of the metal. Furthermore, compared to nitinol, Ti6AL4V exhibits a greater corrosion resistance. When a smaller hatch distance and lower laser beam strength were used, the nitinol sample's susceptibility to corrosion was reduced. This study demonstrates how the corrosion resistance of metal parts made by additive manufacturing can be increased by adjusting the laser powder bed fusion processing parameters in a bodily environment.

In situ three-dimensional reconstruction of laser powder bed fusion parts by light field camera

The assessment of output quality in the laser powder bed fusion process entails the analysis of the three-dimensional morphology of the manufactured parts, which plays a crucial role in quality control to prevent metallurgical defects. This study proposes a novel approach of three-dimensional reconstruction for laser powder bed fusion parts using a light field camera. Initially, a consistency method for high-precision camera calibration was explored to determine the virtual camera pixel size and coefficient of effective focal length of light field camera. Subsequently, the model based light field epipolar-plane image Unet is designed to obtain disparity information without any data augmentation techniques. By leveraging both binocular and light field optical paths, a robust mapping relationship of the disparity, depth, and visually coherent three-dimensional contour was established. Finally, the three-dimensional contours of laser powder bed fusion parts were reconstructed by the established mapping with a single exposure of the light field camera. The proposed method enables three-dimensional contour visualization of laser powder bed fusion parts from multi-view perspectives, which facilitates in situ monitoring of the spattering distance, three-dimensional spatial points and lines of the printed layers and contours of printed parts. With a calibration error of 50 μm and resolution of 180 μm for the light field camera (Lytro illum camera), the maximum relative and absolute errors between reconstructed three-dimensional spatial points were 4.33 % and 260 μm respectively when compared with theoretical dimension, and 0.5 % and 210 μm respectively when compared with manufactured dimension. The maximum root-mean-square error of reconstructed three-dimensional contour surfaces was found to be 1.55 mm. This study represents the first application of a light field camera for in situ three-dimensional reconstruction of laser powder bed fusion parts, which notably can be obtained from only a single round of calibration and exposure, enabling seamless monitoring of their surface morphology and facilitating online quality control. These advancements have vast potential for enhancing high-end additive manufacturing.

Strain rate-dependent tensile response and deformation mechanism of laser powder bed fusion 316L stainless steel

The laser powder bed fusion (LPBF) process is renowned for producing metal parts with exceptional mechanical properties, attributed to their unique microstructures. However, there is a lack of discussion in the literature regarding the plastic deformation mechanism at wide strain rates. To address this research gap, this study employs both quasi-static tensile (QST) tests and dynamic Split-Hopkinson tensile bar (SHTB) experiments to investigate the tensile properties and deformation mechanisms of a well-characterized material, 316L stainless steel (SS), across an extensive range of strain rates spanning from 10−3 s−1 to 103 s−1. Our results reveal the superior quasi-static and dynamic stretching behavior exhibited by LPBF specimen in comparison to the wrought 316L counterpart. This enhanced behavior can be primarily attributed to the cellular and hierarchical structures inherent to LPBF specimen. Notably, the cellular structure emerges as the primary controlling factor in mechanical deformation due to its capacity for increasing the critical strain required for deformed twinning and martensite transition. Consequently, under quasi-static loading, twinning and martensite transition act as the dominant deformation mechanism, while dynamic loading conditions are characterized by a prevalence of dislocation interactions. This comprehensive understanding of the deformation mechanism and strain rate-dependent behavior of LPBF 316L SS provides valuable insight for optimizing its mechanical properties under a wide range of loading conditions.

Superior mechanical properties of a Zr-based bulk metallic glass via laser powder bed fusion process control

Additive manufacturing has made the fabrication of large-dimensioned bulk metallic glasses (BMGs) achievable; however, questions remain regarding how to control the processing parameters to obtain dense and fully amorphous BMGs with desirable mechanical properties. Here, laser powder bed fusion (LPBF) was used to produce dense and fully amorphous Zr59.3Cu28.8Nb1.5Al10.4 BMG samples from two different starting powders within a large processing window of laser powers and scanning speeds. X-ray diffraction (XRD) revealed that fully amorphous XRD patterns were obtained for samples with high relative densities (>99 %) when the LPBF energy density ranged from ∼20 J/mm3 up to ∼33 J/mm3 for coarse powder with low oxygen and up to ∼30 J/mm3 for fine powder with higher oxygen. For the fully XRD amorphous samples, strength and hardness increased with increasing energy density while the relaxation enthalpy and ductility decreased. Transmission electron microscopy revealed that the softer samples contain larger medium range order clusters within the amorphous matrix. With higher LPBF energy density, high relative density was still achieved along with devitrification and embrittlement. While lower energy densities below ∼20 J/mm3 could retain a fully XRD amorphous structure, such samples had relative densities <99 %. When comparing the two powders, the coarse powder with four times lower oxygen content gave better glass forming ability, compression ductility up to 6 % plastic strain, and fracture toughness up to ∼38 MPa√m. These findings demonstrate that it is possible to tailor the structure and mechanical properties of BMGs by tuning the LPBF process parameters within a wide processing window.

Effects of particle damper design parameters on the damping performance of laser powder bed fused structures

Particle dampers (PD), a passive damping technology, absorb energy from particle-particle and particle-cell wall interactions originating from friction and collision. PDs offer advantages such as design simplicity, low cost, applicability in harsh conditions, and flexibility to be used in a wide frequency band range. Additive manufacturing, specifically the powder bed fusion process, can fabricate structures with integrated PDs in a single printing process, eliminating the need to implement external dampers. However, the dynamic behavior of PDs must be determined to utilize their full potential. In this study, we examined 16 cases of integrated PDs by varying specific parameters including size, number, and locations on the structure to understand the effects of these parameters on the dynamic behavior of the first and second modes of the structure. Modal tests were conducted on additively manufactured samples to extract frequency response functions and calculate modal parameters (natural frequency and damping ratio) using the rational fraction polynomial method, studying the effects of PDs. The results showed that the damping performance of the parts was increased by a factor of up to 10 using body-integrated PDs compared with the fully fused specimen. The effectiveness of body-integrated PDs was shown to be strongly dependent on their volume and location. For instance, the damping generally increased as the volume fraction increased, which also reduced the total weight of the specimens by up to 60 g. Furthermore, the damping performance significantly increased for a specific mode when the PDs were located near the maximum displacement regions.

Printability, microstructures and mechanical properties of a novel Co-based superalloy fabricated via laser powder bed fusion

High levels of Al and Ti in superalloy compositions normally lead to cracking formation during the laser powder bed fusion process, while these elements are key constituents of strengthening phases. In the current study, a novel Co-based superalloy with the basic chemical composition of Co-Al-W-Ta-Ti resolved this contradiction, indicating that the part was formed without cracking and simultaneously contained a large amount of strengthening precipitates in the microstructure fabricated via laser powder bed fusion. The printability, microstructures, and mechanical properties of the sample were analysed before and after heat treatment, providing a potential superalloy that can replace Ni-based superalloys fabricated by additive manufacturing in aerospace and other industries with higher temperature and more efficiency.

Monitoring of Laser Powder Bed Fusion process by bridging dissimilar process maps using deep learning-based domain adaptation on acoustic emissions

Advances in sensorization and identification of information embedded inside sensor signatures during manufacturing processes using Machine Learning (ML) algorithms for better decision-making have become critical enablers in building data-driven monitoring systems. In the Laser Powder Bed Fusion (LPBF) process, data-driven-based process monitoring is gaining popularity since it allows for real-time component quality verification. Real-time qualification of the additively manufactured parts has a significant advantage as the cost of conventional post-manufacturing inspection methods can be reduced. Also, corrective actions or build termination could be done to save machine time and resources. However, despite the successful development in addressing monitoring needs in LPBF processes, less research has been paid to the ML model's robustness in decision-making when dealing with variations in data distribution from the laser-material interaction owing to different process spaces. Inspired by the idea of domain adaptation in ML, in this work, we propose a deep learning-based unsupervised domain adaptation technique to tackle shifts in data distribution owing to different process parameter spaces. The temporal waveforms of acoustic emissions from the LPBF process zone corresponding to three regimes, namely Lack of Fusion, conduction, and keyhole, were acquired on two different 316 L stainless steel powder distributions (> 45 µm and < 45 µm) with two different parameter sets. Temporal and spectral analysis of the acoustic waveforms corresponding to the powder distributions treated with different laser parameters showed the presence of offset in the data distribution, which was subsequently treated with the proposed unsupervised domain adaptation technique to have an ML model that could be generalized. Furthermore, the prediction accuracy of the proposed methodology between the two distributions showed the feasibility of adapting to the newer environment unsupervisedly and improving the ML model's generalizability.

Investigation of the effects of energy density in Laser Sintering of polypropylene on morphological and dielectric properties for high-frequency antennas

Advancements in the Internet of Things demand more capable antenna systems, which benefit from the complex geometries enabled by additive manufacturing. Novel approaches, such as external metallization of polymers, enable the design of these geometries but require the processing of low dielectric-loss polymers in additive manufacturing. Arising from prevailing limitations on additively manufactured low-loss components, this study investigates the effect of energy density on polypropylene’s dielectric properties in powder bed fusion processes. Variations in laser power significantly influenced material density and mechanical characteristics. Both insufficient and excessive energy densities resulted in lower quality parts due to issues like fused particles or inadequate melting. Optimal dimensional accuracy and surface quality were achieved with energy levels slightly below those for peak density. While dielectric loss remained mostly stable, relative permittivity decreased at very low densities, where partial melting occurred. Relying on derived optimized parameters, the functionality of passive high-frequency components was demonstrated.

Effects of Ni-based powder reuse on porosity, surface quality and reproducibility of thin-walled structures in Laser Powder Bed Fusion process

Inconel 718 alloy parts were manufactured by a laser powder bed fusion (PBF-LB) process using virgin and reused nickel-chromium powder produced by an argon gas atomization. PBF-LB is an emerging technology for the additive manufacturing of metallic end-products with complex shapes. At the same time, optimization of the PBF-LB parameters and powder reuse/recycling evaluation are required to achieve high-quality manufactured superalloy products for a critical manufacturing sector, such as aeronautical and aerospace applications. This paper focused on studying the effects of virgin and reused powders after 10 iterations on the powder properties and material density, surface roughness/topography of the PBF-LB-built superalloy parts, as well as repeatability of thin-walled structures. Results showed that the oxygen content and particle size of the reused powder increased. In addition, the micro-porosity and surface roughness values varied depending on the amount of reused powder. The quality and repeatability of the thin-walled structures are improved after increasing the number of builds.

Impact of process parameters and gas atmospheres on density and microstructure of super duplex stainless steel produced by Laser Powder Bed Fusion

Super duplex stainless steel (2507 SDSS) is an alloy renowned for its excellent corrosion resistance and mechanical properties. This unique combination arises from a duplex microstructure characterized by austenite and ferrite. However, when processed using the laser powder bed fusion (LPBF) process, this steel contains only the ferritic phase due to the rapid cooling rates inherent in LPBF, which suppresses the formation of the austenitic phase. This study explores a parameter process optimization for this steel in two different atmospheres, Ar and N, with the latter being an austenite-stabilizing element intended to enhance the formation of the austenitic phase. A comparison of the optimal process windows between the two atmospheres is conducted, and the amount of austenitic content is evaluated as a function of the process parameters and the shielding gas employed. Findings demonstrate that utilizing a nitrogen atmosphere, in conjunction with process parameters that reduce normalized enthalpy and material evaporation, increases austenite content post-manufacture. Additionally, nitrogen as the processing gas effectively minimizes and stabilizes nitrogen content within the samples.

A model for the rapid prediction of small feature width producible by Metal AM

In this paper, an analytical parametric model is presented for the swift prediction of small features producible in the X-Y plane through the Metal AM Laser Powder Bed Fusion (LPBF) process. This model can be employed to design and create surface textures on Additive Manufactured parts without the need for costly post-processing steps. The Rosenthal equation is the basis for the model, which considers both the build parameters of the LPBF process and the thermo-physical properties of the materials. The initial model was constructed and assessed using one LPBF machine followed by the implementation of a tuning method utilizing the Limited Memory Algorithm for Bound Constrained Optimization to enhance the model’s accuracy. Overall, the findings suggest that with a simple optimization step based on a single printed tuning sample, precise analytical models can be established for specific LPBF machines and materials combinations.