Powder Bed Fusion Additive Manufacturing Research Articles

Influence of Electron Beam Powder Bed Fusion Process Parameters at Constant Volumetric Energy Density on Surface Topography and Microstructural Homogeneity of a Titanium Aluminide Alloy

In powder bed fusion additive manufacturing, the volumetric energy density E V is a commonly used parameter to quantify process energy input. However, recent results question the suitability of E V as a design parameter, as varying the contributing parameters may yield different part properties. Herein, beam current, scan velocity, and line offset in electron beam powder bed fusion (PBF‐EB) of the titanium aluminide alloy TNM–B1 are systematically varied while maintaining an overall constant E V. The samples are evaluated regarding surface morphology, relative density, microstructure, hardness, and aluminum loss due to evaporation. Moreover, the specimens are subjected to two different heat treatments to obtain fully lamellar (FL) and nearly lamellar (NLγ) microstructures, respectively. With a combination of low beam currents, low‐to‐intermediate scan velocities, and low line offsets, parts with even surfaces, relative densities above 99.9%, and homogeneous microstructures are achieved. On the other hand, especially high beam currents promote the formation of surface bulges and pronounced aluminum evaporation, resulting in inhomogeneous banded microstructures after heat treatment. The results demonstrate the importance of considering the individual parameters instead of E V in process optimization for PBF‐EB.

A lightweight Fe–Mn–Al–C austenitic steel with ultra-high strength and ductility fabricated via laser powder bed fusion

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (∼9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology.

Novel isotropic mechanical properties of laser powder-bed fusion Sc/Zr modified Al alloy

To explore the mechanical anisotropy of high-strength Al alloys for laser powder bed fusion (LPBF) additive manufacturing, the Al–Mn–Mg-Sc-Zr alloys were built along X, Y, Z axial and 45° directions by LPBF subjecting to a series of different heat treatments. All the printed and heat treated components displayed a columnar/equiaxed bimodal microstructure, where the secondary Al6Mn and nano-size Al3Sc precipitates ubiquitously dispersed in the columnar and equiaxed grain regions, respectively. The Al–Mn–Mg-Sc-Zr alloy exhibited a continuous strength increase from 453 MPa to 577 MPa after the heat treatment through the synergistic effect of the solid solution strengthening, grain boundary strengthening and Orowan dislocations strengthening from Al6Mn as well as Al3Sc precipitates. But its ductility suffered from a decrease from 14.1% to 2.3%. Especially, the optimal collaboration between hard equiaxed grain and soft columnar grain contributed to the mechanical properties isotropy of the printed and heat-treated alloy components along different tensile directions with strength difference only 1.3–2%. Thus, the synergetic effects of hierarchical bimodal microstructure and secondary precipitations could provide the effective avenues to tune the mechanical property and anisotropy of LPBF Al alloys.

On the process of designing material qualification type specimens manufactured using laser powder bed fusion

Recent investigations involving specimens for material and process qualification related to the Laser Powder Bed Fusion (L-PBF) additive manufacturing (AM) method, point that microstructural quality and surface properties vary significantly based on feedstock material and process parameters. There is currently the need, therefore, to create systematic ways to design specimens for process and material qualification. This manuscript provides an approach to evaluate the effects on the as-built quality based on specific metrics for specimens produced by L-PBF. Surface quality, as well as micro- and sub-microstructures and defects are related to specific aspects of the L-PBF process. To accomplish this goal, a digital engineering approach was first developed to design geometries based on process simulations to account for mechanical and thermal process effects. A parametric AM fabrication plan was then chosen to produce statistically significant populations of AM parts. Moreover, on axis, melt-pool scale, in-situ monitoring data, collected during the AM process, was examined in conjunction with the formation of flaws. X-ray micro-computer tomography analysis was additionally used to characterize porosity levels. Finally, scanning electron microscopy (SEM) and electron back-scatter diffraction (EBSD), as well as surface profilometry were combined to correlate specific process parameters and conditions with microstructural and surface effects.

Powder Spreading Mechanism in Laser Powder Bed Fusion Additive Manufacturing: Experiments and Computational Approach Using Discrete Element Method.

Laser powder bed fusion (LPBF) additive manufacturing (AM) has been adopted by various industries as a novel manufacturing technology. Powder spreading is a crucial part of the LPBF AM process that defines the quality of the fabricated objects. In this study, the impacts of various input parameters on the spread of powder density and particle distribution during the powder spreading process are investigated using the DEM (discrete element method) simulation tool. The DEM simulations extend over several powder layers and are used to analyze the powder particle packing density variation in different layers and at different points along the longitudinal spreading direction. Additionally, this research covers experimental measurements of the density of the powder packing and the powder particle size distribution on the construction plate.

Multi-Track Melt Pool Width Modeling in Powder Bed Fusion Additive Manufacturing

Abstract While powder bed fusion (PBF) additive manufacturing offers many advantages and exciting applications, its broader adoption is hindered by issues with reliability and variations during the manufacturing process. To address this, researchers have identified the importance of using both finite element modeling and control-oriented modeling to predict and improve the quality of printed parts. In this paper, we propose a novel control-oriented multi-track melt pool width model that utilizes the superposition principle to account for the complex thermal interactions that occur during PBF. We validate the effectiveness of the model by applying a finite element model of the thermal fields in PBF.

Developing a novel lightweight Al–Mg–Li alloy for laser powder bed fusion additive manufacturing: Parameter optimization, microstructure evolution, and mechanical performance

With the advancement of laser powder bed fusion (LPBF) for aluminum alloys, developing novel lightweight Al–Li alloy systems present enormous potential for aerospace applications. Conventional Al–Mg–Li alloys exhibit low densities but suffer from poor strength due to the lack of inherent strengthening phases. In the present work, a novel lightweight Al–Mg–Li–Ag-Sc-Zr alloy was developed for LPBF after optimizing the processing parameters. The as-built alloy featured a bimodal microstructure consisting of fine equiaxed grains and columnar grains. The submicron primary Al3(Sc, Zr) phases with a cubic L12 structure served as inoculants for grain refinement and exhibited good coherency with the α-Al matrix. Besides, submicron spherical quasicrystalline T-Mg32(Al, Ag)49 phases of and nanometer rod-shaped S1–Al2MgLi phases were scattered inside the grains. These results produced a yield strength (σy) of 286 ± 8 MPa, ultimate tensile strength (σUTS) of 406 ± 3 MPa, and elongation at fracture (εf) of 12.5 ± 0.3%. The direct aging at 325 °C for 12 h led to an increase in hardness to a peak value of 170 HV. The secondary phases at the grain boundaries were breached and a large amount of submicron T and S1 phases within the grains were prominently increased. Besides, spherical Al3(Sc, Zr, Li) and tiny δ′-Al3Li precipitates were observed in the α-Al matrix. A considerably enhanced σy of 375 ± 12 MPa and σUTS of 469 ± 4 MPa were achieved mainly due to the particle strengthening but decreased εf to 5.8 ± 0.2%. The alloys in both states exhibited a moderate work-hardening capability. The feasibility of LPBF for lightweight Al–Li alloy was successfully established but required further optimization of the alloy composition.

Laser powder bed fusion of Alumina/Fe–Ni ceramic matrix particulate composites impregnated with a polymeric resin

Additive Manufacturing (AM) plays a key role in meeting the vital demands of Industry. The AM industry needs the range of applicable materials to be expanded by conducting research on novel ones. In the present investigation, alumina/Fe–Ni (steel) ceramic matrix particulate composite was fabricated employing laser powder bed fusion (LPBF) additive manufacturing (AM) technology. The quality of the printed samples was associated with the LPBF process parameters, which were optimized for this process. In general, the fabricated samples showed a microstructure of alumina matrix with uniform distribution of steel (Fe–Ni) particles. The as-printed samples exhibited pores. Thus, they were subjected to a sintering heat treatment cycle under an inert atmosphere. Although the sintering cycle considerably increased the average Vickers hardness, pores were not eliminated entirely. Therefore, polymer impregnation of the as-sintered samples was carried out to reduce porosities and microcracks. The mercury porosimeter showed that the porosity decreased sequentially after sintering and polymer impregnation. In addition, mechanical investigations revealed that the polymer impregnation improved the compressive strength of the sintered samples (from 56 to 120 MPa). Alumina-based materials find wide applications in various fields, including the manufacturing of electronic components, cutting tools, biomedical implants, and catalyst converters, owing to their low density, high hardness, wear and corrosion resistance, and biocompatibility. This study presents a viable approach for the fabrication of these materials, with developed samples exhibiting promising properties. The study emphasizes the potential of additive manufacturing as an approach for the fabrication of ceramic matrix composites reinforced with metallic particulates in future research.

Additive manufacturing of a metastable high entropy alloy: Metastability engineered microstructural control via process variable driven elemental segregation

Compositional paradigm shift in high entropy alloys (HEAs) provided new opportunities for microstructural engineering, whereas process control during laser powder bed fusion (LPBF) additive manufacturing (AM) enable fine microstructure tailoring. Metastability engineering in transformation induced plasticity (TRIP) HEAs by addition of minor alloying elements is an attractive strategy for fine microstructural tuning. This study explored in detail the microstructural evolution during LPBF AM of a metastable Fe40Mn20Co20Cr15Si5 (at.%) dual phase HEA (CS-HEA). LPBF processing window for CS-HEA was established based on quantitative analysis and experiments. Based on melt pool overlap lack of fusion pores were observed at lower energy densities (J) of J ≤ 31.25 J/mm3 and key-hole formation by melt pool destabilization in case of J ≥ 75 J/mm3. The microstructure of CS-HEA consists of metastable FCC-γ and HCP-ε phases; LPBF process parameters governed the final phase fraction in the alloy which has been correlated to metastability alteration of the high temperature γ phase. Final microstructural engineering was devised by LPBF process control which enabled cooling rate manipulation to guide Mn and Si segregation at the cell boundaries, thereby controlling the matrix metastability and final phase fraction. Additionally, high resolution transmission electron microscopy (TEM) revealed disparity in stacking fault morphology in CS-HEA with LPBF process variable alterations associated with local variations in chemical composition and stacking fault energy. The phase evolution with process parameters also affected the nanomechanical behavior of the alloy.

Experimental Investigation on Friction Behavior of Selective Laser Sintering Processed Parts

Selective laser sintering (SLS) is a powder bed fusion additive manufacturing process that uses polymer powders to produce functional parts directly from digital 3D models. SLS supports small- to medium-batch fabrication of customized products for various end-use applications. These parts can be used as tooling to support conventional manufacturing and inspection where mechanical and tribological behaviors are important. This article evaluates the friction behavior of parts fabricated by SLS polyamide (PA12) and glass bead-filled polyamide (PA-GF) materials. Pin-on-Disk tribometer was used to characterize the behavior in dry sliding conditions with part build orientation, load, and speed as factors. Taguchi's approach and analysis of variance are used to quantify the influence of these factors on the friction coefficient. Both materials show reduction in friction coefficient with the increase in load; on the other hand, an increase in speed affects adversely. However, the influence of part orientation is comparatively lesser than the other two factors considered in this study. The debris, pin, and disk wear surfaces were examined to learn wear mechanisms. It is observed that surface porosity resulting from the fabrication process plays a significant role in friction behavior. The glass beads in PA-GF material function as reinforcement against load and influences the friction behavior. Low friction and wear characteristics make both materials as a prospective contender for tooling application.

A point field driven approach to process metrics based on laser powder bed fusion additive manufacturing models and in situ process monitoring

The widespread adoption of additive manufacturing (AM) in different industries has accelerated the need for quality control of these AM parts. Some of the complex and labor-intensive challenges associated with qualification and certification of AM parts are addressed by modeling and monitoring process conditions. Quantifying melt-track process conditions remains a significant computational challenge due to the large-scale differential between melt pool and part volumes. This work explores a novel point field (PF) driven AM model-based process metric (AM-PM) approach for calculating melt track resolved process conditions with maximal computational speed. A cylindrical Ti-6Al-4V test article with 16 equiangular zones having varied process parameters was built. The melt-track resolved AM-PMs were calculated and mapped to porosity existence for the 5.8-million-point PF of the test article. AM-PMs were calculated in 6.5 min, ~ 665 × faster than a similarly sized finite element calculation. This approach enables efficient prediction, assessment, and adjustment of AM builds.Graphical abstract

Deep learning-based data registration of melt-pool-monitoring images for laser powder bed fusion additive manufacturing

Melt-pool monitoring (MPM) has been widely used in the laser powder bed fusion (LPBF) additive manufacturing process for process control and part quality prediction. Achieving this requires appropriate MPM-data alignments to the process parameters, part inspection, and testing data. This task is challenging when laser positioning is not synchronized with MPM-data acquisition. To address this challenge, this paper proposes a novel deep learning-based methodology to directly estimate melt pool positions in the machine-build coordinate system from the melt-pool images. First, we present two image-preprocessing methods, including image transformation and spatter reduction, using a stacked convolutional autoencoder to reduce noises from raw MPM images. Second, a convolutional neural network (CNN) based on self-supervised learning (SSL) is developed to identify the scan direction associated with an individual MPM image. Finally, Kalman Filtering is applied to estimate melt-pool positions given their scan directions. A case study based on an experimental build shows that the SSL-based CNN predicts the associated scan directions from the MPM images with an average error of about 1.37∘, and the Kalman filter effectively estimates the positions of melt pools with an average error of about 24.86 μm. The proposed methodology can benefit AM research and practice, enhancing data correlation and fusion, real-time defect prediction, and process quality control.

Modeling the process behavior in laser additive manufacturing of metallic materials—A tribute to professor Jyoti Mazumder

This paper provides an overview of Professor Jyoti Mazumder's contribution in modeling of laser-matter interaction during materials processing over the past four decades, particularly in the area of laser-based metal additive manufacturing of metallic components, followed by the work at The University of Manchester in modeling and simulation of powder/wire-feeding laser additive manufacturing, in-space laser additive manufacturing, high deposition rate laser metal deposition, and multiple-material laser powder bed fusion additive manufacturing processes. Future challenges and opportunities in this field are discussed.

Numerical investigation of fiber orientations and homogeneity in powder bed fusion of fiber/polymer composites

ABSTRACT The packing characteristics of fiber/polymer powder in powder bed fusion additive manufacturing exhibit a high correlation with the mechanical behaviours of printed composite parts such as homogeneity and anisotropy. A discrete element model has been developed to investigate the packing characteristics of glass fiber/polyamide 12 (PA12) powder, which include fiber orientations, fiber homogeneity, and packing density. The predicted probability distributions of fiber orientations in the powder bed are comparable with those measured in glass fiber–reinforced PA12 composites printed via multi jet fusion. Three types of fibers with different length distributions are adopted to study the effects of the fiber length distribution on their packing characteristics. The simulation results reveal that a large average fiber length is beneficial to fiber alignment in the powder spreading direction but lowers the fiber homogeneity and packing density of the powder bed. Furthermore, varying the fiber length can provide an effective way to regulate fiber orientations in the powder packing process, which would help achieve satisfactory anisotropic mechanical properties for composite parts.

Numerical modelling of SS316L powder flowability for laser powder-bed fusion

This work aims to improve the powder-bed spreading process for laser powder bed fusion additive manufacturing by gaining a greater understanding of metal powder flowability through numerical modelling and in-situ experimentation.Using the Discrete Element Method (DEM) to study the flowability of the powder and its intrinsic properties. A high-fidelity particle-scale model was developed to capture the dynamics of metal particle interactions in a virtual Hall flow meter based on a modified Beverloo law. The results are validated experimentally using the Hall flow static powder characterisation technique.For SS316L powder alloy with the hall-value of 29s/50g and with an angle of repose (AOR) of 32, the modelled powder that exhibited the same flow behaviour was found using 0.5 for both rolling and sliding coefficients resulting in simulated Hall value of 28.55s/50g with a simulated flow rate of 0.571 g/s, which is validated by AOR of the simulated powder [31.2-32.6]. However, rolling friction had minimal effect on the mass flow rate but increased the angle of repose. Sliding friction significantly decreased the mass flow rate and increased AOR.DEM is an ideal method to study flowability. However, there are certain constraints imposed on the computational power by a number of simulated particles and simulation time-step. Future research may involve investigating other dynamic flowability characterisation techniques.Enabling a better understanding of powder particle flow at a micro-scale by modelling powder flowability. This leads to simulating a more realistic powder bed and improving the powder spreading process, leading to better AM parts quality.This paper provides a unique approach for modelling the flowability of SS316L powder using a Beverloo law-based design of the Hall flow meter. This will improve the modelling of the spreading process needed for metal 3D printing.

Review of state-of-the-art research on the design and manufacturing of support structures for powder-bed fusion additive manufacturing

Review of state-of-the-art research on the design and manufacturing of support structures for powder-bed fusion additive manufacturing

Density-Based Optimization of the Laser Powder Bed Fusion Process Based on a Modelling Framework

One of the main challenges encountered in the Laser-based Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) process is the fabrication of defect-free parts. The presence of defects severely degrades the mechanical performance of AM parts and especially their fatigue strength. The most popular and reliable method to assess the ability of the employed process parameters for the fabrication of full-density parts is the process windows map, also known as printability map. However, the experimental procedure for the design of the printability maps and the identification of the optimum-density process parameters is usually time-consuming and expensive. In the present work, a modelling framework is presented for the determination of a printability map and the optimization of the L-PBF process based on the prediction and characterization of melt-pool geometric features and the prediction of porosity of small samples of 316L SS and Ti-6Al-4V metal alloys. The results are compared with available experimental data and present a good correlation, verifying the modelling methodology. The suitability of the employed defect criteria for each material and the effect of the hatch-spacing process parameter on the optimum-density parameters are also presented.

Additive Manufacturing of a Miniaturized X-Band Single-Ridge Waveguide Magic-T for Monopulse Radar Applications

A low-profile single-ridge waveguide magic-T is proposed as a combination of two T-junctions at an X band. A slot coupling technique is used to reduce the component dimensions in the E-plane, thus leading to a low profile. The device can assume two configurations by arranging the sum and difference ports in the same or opposite direction, an attractive feature in the design of beamforming networks with complex routing. A magic-T prototype is fabricated using laser powder bed fusion additive manufacturing techniques. Good agreement between simulations and measurements is found.

Effect of post-processing methods on the surface quality of Ti6Al4V fabricated by laser powder bed fusion

Ti6Al4V is widely used in aerospace and medical applications, where high demands on dimensional accuracy and surface quality require the application of post-processing to achieve optimal performance. However, the surface quality of parts fabricated by LPBF is inferior due to the inherent defects of LPBF. Therefore, it is important to investigate the effect of post-processing on the surface quality of Ti6A14V parts fabricated by LPBF. In this work, the effect of post-processing methods (i.e., sandblasting, electrolytic polishing, chemical polishing, and abrasive flow polishing) on the surface quality of Ti6Al4V fabricated by laser powder bed fusion (LPBF) additive manufacturing was investigated. The changes in surface roughness and morphology of the 45° inclined square and curved pipe Ti6Al4V samples processed with post-processing were observed, and the weight and elemental changes of the parts were also analyzed. The result reveals that sandblasting, electrolytic polishing, chemical polishing, and abrasive flow polishing are all effective in improving the surface quality of Ti6Al4V parts fabricated by LPBF. The effect of sandblasting is mainly caused by sharp-edged grit driven by high-speed airflow, resulting in the lowest surface roughness and the least influence on the weight, but may contaminate the surface with residual brown corundum. Electrolytic polishing and chemical polishing achieve surface quality improvement through different corrosion patterns without changing the surface composition. The surface smoothness of parts processed with chemical polishing is the best, while the weight loss rate of the sample processed with electrolytic polishing is the most at about 7.47%. Abrasive flow polishing presents a remarkable effect on polishing the internal surface of the Ti6Al4V sample by the extrusion scratching, extrusion deformation, and micro-cutting effects of abrasive on the surface. The findings can provide important engineering references for the post-processing of precision Ti6Al4V parts fabricated by LPBF and further promote the engineering applications of Ti6Al4V parts.

3D thermal simulation of powder bed fusion additive manufacturing of stainless steel

3D thermal simulation of powder bed fusion additive manufacturing of stainless steel