Powder-based Additive Manufacturing Processes Research Articles

Correlation of Different Cemented Carbide Starting Powders with the Resulting Properties of Components Manufactured via Binder Jetting

For several years, researchers have been exploring the use of the binder jetting powder-based additive manufacturing process to produce WC-Co hardmetals. Compared to other additive manufacturing processes, binder jetting has the potential for high-volume production. However, due to the powder-based approach, the resulting green bodies typically have low green density, limiting the achievable hardness and requiring higher Co content. Choosing the appropriate starting powder and post-processing can extend previous limitations and allow the selection of a suitable powder based on the application. This investigation focuses on exploring and evaluating the correlation between varying morphologies of WC-Co starting powders, their processability using the BJT method, and the resultant mechanical properties of sintered components.

Tailoring material properties of duplex stainless steel by DED-LB/M and in situ alloying with elemental powders

Stainless steels are established in various fields with challenging environments, e.g., offshore, petrochemical, and automotive industries. The combination of high-performance properties and high-value added applications makes stainless steels attractive for additive manufacturing (AM). In powder-based AM processes such as laser-directed energy deposition (DED-LB/M), typically prealloyed powders are used for part generation. By an innovative approach called in situ alloying, the chemical composition of prealloyed powder can be adjusted by mixing it with an additional powder material. This allows the material properties to be flexibly and efficiently tailored for specific applications. In this work, a standard duplex stainless steel (DSS) is modified for the first time with elemental powders in order to systematically adjust the resulting phase formation, mechanical properties, and corrosion resistance. For this, powder mixtures were generated consisting of prealloyed DSS 1.4462 and additions of pure chromium (1.0–7.0 wt. %) or nickel (1.0–5.0 wt. %) powder. Processing them by means of DED-LB/M resulted in specimens (rel. density > 99.7%) with ferrite–austenite phase ratios ranging from almost 10%:90% to 90%:10%. Increasing the chromium content successively increased the ferrite percentage, resulting in higher material hardness, higher strength, and resistance against pitting corrosion but poor ductility and toughness compared to unmodified DSS. In contrast, an increased nickel content resulted in an increased austenite formation with lower hardness and strength but increased ductility. This strategy was shown to add flexibility to powder-based AM processes by enabling an on-demand material design for stainless steels.

Non-planar granular 3D printing

Most approaches to 3D printing at various scales are layer based, meaning they start with a 3D CAD model that is sliced into planar print paths to be translated to machine code. However, this approach entails a number of drawbacks, such as slow printing speeds, limited build volumes, allowable geometric properties, and material diversity. To overcome these limitations, the authors have developed a novel additive manufacturing process called Non-Planar Granular Printing (NGP). Compared to its layer-based counterpart, NGP enables non-planar 3D printing by selectively binding reusable granular particles to create free-form structures. In doing so, NGP leverages traditional powder-based additive manufacturing processes. However, instead of enclosing the extruded compounds within a three-axis layer-based system, NPG combines multi-axis robotic deposition capabilities with customizable build volume parameters, which drastically improves print speed, scalability and material versatility. The result is a process whose main advantage is to enable the rapid production of support-free and complex geometric forms using a wide range of materials in granular form. This paper introduces and analyzes a series of benchmark experiments conducted to demonstrate the practical workflow, general output capabilities, and volume-material limitations of the system. The research also lays a foundation of non-planar 3D extrusion that enables material transitions for functional gradience capabilities.

Biobased composite powders from PHA, waxes and lignocellulosic biomasses for powder-based additive manufacturing processes

Reducing our impact on the environment requires the use of biobased materials and their composites, which can be sourced from biomass feedstocks. However, due to technological limitations, these materials are not easily integrated into current Additive Manufacturing technologies like Selective Laser Sintering.The focus of the present study is to develop a new, environmentally friendly process that can prepare composite biobased powders for SLS. These powders are made from polyhydroxyalkanoate, waxes, and lignocellulosic fillers. The process is based on emulsification and dissolution/precipitation in eutectic solvents and has the potential to be utilized with a wide range of biobased materials.

Experimental approach for development of a powder spreading metric in additive manufacturing

The powder spreading is a vital step of powder-based additive manufacturing (AM) processes. The quality of spread powder can considerably influence the properties of fabricated parts. Poorly packed powder beds with high surface roughness result in printed part layers with large porosity and low dimensional accuracy, leading to poor mechanical properties. Therefore, the powder spreadability and its dependence on process parameters and powder characteristics should be quantified to improve the efficiency of powder-based AM methods. This study proposes a novel dimensionless powder spreadability metric that can be commonly used in different powder-based AM processes. The quality of spread powder in terms of powder bed density and surface roughness was evaluated by adjusting the process parameters including recoating velocity and layer thickness, and powder characteristics including particle size distribution. In addition, the dynamic repose angle was proposed and examined as another powder spreadability metric. The results showed that these two proposed metrics were strongly correlated and lower recoating velocity and larger layer thickness led to higher spreadability and lower dynamic repose angle.

Thermal Modeling of Polyamide 12 Powder in the Selective Laser Sintering Process Using the Discrete Element Method.

Selective laser sintering (SLS) is one of the key additive manufacturing technologies that can build any complex three-dimensional structure without the use of any special tools. Thermal modeling of this process is required to anticipate the quality of the manufactured parts by assessing the microstructure, residual stresses, and structural deformations of the finished product. This paper proposes a framework for the thermal simulation of the SLS process based on the discrete element method (DEM) and numerically generated in Python. This framework simulates a polyamide 12 (PA12) particle domain to describe the temperature evolution in this domain using simple interaction laws between the DEM particles and considering the exchange of these particles with the boundary planes. The results obtained and the comparison with the literature show that the DEM frame accurately captures the temperature distribution in the domain scanned by the laser. The effect of laser power and projection time on the temperature of PA12 particles is investigated and validated with experimental settings to show the reliability of DEM in simulating powder-based additive manufacturing processes.

Numerical Modeling of Distortion of Ti-6Al-4V Components Manufactured Using Laser Powder Bed Fusion

The laser powder bed fusion (L-PBF) process is a powder-based additive manufacturing process that can manufacture complex metallic components. However, when the metallic components are fabricated with the L-PBF process, they frequently encounter the residual stress and distortion that occurs due to the cyclic of rapid heating and cooling. The distortion detrimentally impacts the dimensional and geometrical accuracy of final built parts in the L-PBF process. The purpose of this research was to explore and predict the distortion of Ti-6Al-4V components manufactured using the L-PBF process by using numerical modeling in Simufact Additive 2020 FP1 software. Firstly, the numerical model validation was conducted with the twin-cantilever beam part. Later, studies were carried out to examine the effect of component sizes and support-structure designs on the distortion of tibial component produced by the L-PBF process. The results of this research revealed a good agreement between the numerical model and experiment data. In addition, the platform was extended to predict the distortion in the tibial component. Large distortion arose near the interface between the tibial tray and support structure due to the different stiffness between the solid bulk and support structure. The distortion of the tibial component increased with increasing component size according to the surface area of the tibial tray, and with increasing thickness of the tibial tray. Furthermore, the support-structure design plays an important role in distortion reduction in the L-PBF process. For example, the maximum distortion of the tibial component was minimized up to 44% when a block support-structure design with a height of 2.5 mm was used instead of the lattice-based support. The present study provides useful information to help the medical sector to manufacture effective medical components and reduce the chance of part failure from cracking in the L-PBF process.

Discrete Element Modeling (DEM) simulations of powder bed densification using horizontal compactors in metal additive manufacturing

Efficient packing of the powder bed plays a key role in ensuring high quality of parts printed with Powder Bed Fusion (PBF) based additive manufacturing technologies. This paper presents simulations and analysis of a new technique based on horizontal compactors for improved densification of the spread powder layer. Discrete Element Modeling (DEM) based simulation of this technique shows much improved bed densification and force reduction on the layer underneath, thereby contributing to improved part quality. Results are found to be in excellent agreement with past work. Simulations predict the void fraction distribution as a function of various process parameters. Simulations are carried out to understand the effect of number of particles on stresses acting on the previously printed layer. The technique discussed here is a general one, and may also help analyze other powder-based additive manufacturing processes such as selective laser sintering and binder jetting.

Effect of contaminations on the acoustic emissions during wire and arc additive manufacturing of 316L stainless steel

Additive Manufacturing (AM) processes allow the creation of complex parts with near net shapes. Wire and arc additive manufacturing (WAAM) is an AM process that can produce large metallic components with low material waste and high production rates. Typically, WAAM enables over 10-times the volumetric deposition rates of powder-based AM processes. However, the high depositions rates of WAAM require high heat input to melt the large volume of material, which in turn results in potential flaws such as pores, cracks, distortion, loss of mechanical properties and low dimensional accuracy. Hence, for practical implementation of the WAAM process in an industrial environment it is necessary to ensure flaw-free production. Accordingly, to guarantee the production-level scalability of WAAM it is fundamental to monitor and detect flaw formation during the process. The objective of this work is to characterize the effects of different contaminations on the acoustic spectrum of WAAM and lay the foundations for a microphone-based acoustic sensing approach for monitoring the quality of WAAM-fabricated parts. To realize this objective, WAAM parts were processed with deliberately introduced flaws, such as material contamination, and the acoustic signals were analyzed using the time and frequency domain techniques, namely, Power Spectral Density, and Short Time Fourier Transform. The signatures obtained were used to pinpoint the location of flaw formation. The results obtained in this study show that the effects of contamination in WAAM can be identified through the analysis of the acoustic spectrum of the process. • Acoustic monitoring of the WAAM process is performed. • Defect detection using acoustic signal is validated with CT scans. • Acoustic monitoring is a expedite and low-cost solution for defect detection during WAAM.

Large-Scale Synthesis of Metal Additively-Manufactured Microstructures Using Markov Random Fields

A data-driven framework is developed and examined for creating spatially-varying crystallographic textures over component-scale Computer-Aided Design (CAD) models. Here, a set of three orthogonal 2D micrographs of an Additively-Manufactured (AM) specimen are first obtained experimentally through Electron Backscatter Diffraction (EBSD) and subsequently converted to a 3D representative unit cell using the Markov Random Field (MRF) technique. Features such as grain size, crystallographic orientation, and grain boundary misorientation distributions are used to validate the reconstructed 3D microstructure against input experimental EBSD images. The variations of microstructural features during a powder-based additive manufacturing process are subsequently modeled by merging patches from the 3D snapshot of AM microstructural unit cell in a part-scale geometry using a tensor-based optimization process. The optimization algorithm repeatedly pastes microstructural elements from the reconstructed MRF unit cell onto the geometrical CAD domain until it is entirely covered. Here, through a simple Graphical User Interface (GUI), the user specifies a tensor field over the volumetric CAD model, defining the local control over grain-scale, anisotropy, and crystal growth orientation. This new approach provides a workflow for reconstructing global maps of AM microstructures in real-time by embedding site-specific images based on known AM microstructural patterns seen in experimental characterization techniques. The numerical results are helpful specifically for the visualization of process–microstructure relationships in metal additive manufacturing techniques.

Processing of Aluminium-Silicon Alloy with Metal Carbide as Reinforcement through Powder-Based Additive Manufacturing: A Critical Study.

Powder-based additive manufacturing (PAM) is a potential fabrication approach in advancing state-of-the-art research to produce intricate components with high precision and accuracy in near-net form. In PAM, the raw materials are used in powder form, deposited on the surface layer by layer, and fused to produce the final product. PAM composite fabrication for biomedical implants, aircraft structure panels, and automotive brake rotary components is gaining popularity. In PAM composite fabrication, the aluminium cast alloy is widely preferred as a metal matrix for its unique properties, and different reinforcements are employed in the form of oxides, carbides, and nitrides. However, for enhancing the mechanical properties, the carbide form is predominantly considered. This comprehensive study focuses on contemporary research and reveals the effect of metal carbide's (MCs) addition to the aluminium matrix processed through various PAM processes, challenges involved, and potential scopes to advance the research.

High temperature oxidation behavior and characterization of DMLS fabricated Ni based superalloys

Direct metal laser sintering (DMLS) is a type of powder-based additive manufacturing process in which the fabrication of components is done in a layer by layer system with melting and solidification of powder (raw material) employing a laser heat source. The objective of the present research is to analyze cyclic oxidation behaviour of DMLS fabricated Nickel based superalloy i.e. IN 625 and IN 718 in the air at 700 °C. Cyclic oxidation was carried out in a silicon carbide furnace for fifty cycles and one cycle involves heating of the specimen for 1 h in the furnace at a temperature of 700 °C followed by 20 min of cooling in the air at room temperature. The oxidation kinetics was evaluated by measuring weight change after every cycle with the implementation of the thermogravimetric technique. Evaluation study of oxidation products was done by using charcterization techniques i.e. X-ray diffraction, scanning electron microscopy and X-ray mapping. The IN 625 proved to have better oxidation resistance than IN 718 under cyclic oxidation.

A gravity-independent powder-based additive manufacturing process tailored for space applications

The future of space exploration missions will rely on technologies increasing their endurance and self-sufficiency, including manufacturing objects on-demand. We propose a process for handling and additively manufacturing powders that functions independently of the gravitational environment and with no restriction on feedstock powder flowability. Based on a specific sequence of boundary loads applied to the granular packing, powder is transported to the printing zone, homogenized and put under compression to increase the density of the final part. The powder deposition process is validated by simulations that show the homogeneity and density of deposition to be insensitive to gravity and cohesion forces within a discrete element method (DEM) model. We further provide an experimental proof of concept of the process by successfully 3D printing parts on-ground and on parabolic flight in weightlessness. Powders exhibiting high and low flowability are used as model feedstock material to demonstrate the versatility of the process, opening the way for additive manufacturing of recycled material.

Modelling of Microstructure Formation in Metal Additive Manufacturing: Recent Progress, Research Gaps and Perspectives

Microstructures encountered in the various metal additive manufacturing (AM) processes are unique because these form under rapid solidification conditions not frequently experienced elsewhere. Some of these highly nonequilibrium microstructures are subject to self-tempering or even forced to undergo recrystallisation when extra energy is supplied in the form of heat as adjacent layers are deposited. Further complexity arises from the fact that the same microstructure may be attained via more than one route—since many permutations and combinations available in terms of AM process parameters give rise to multiple phase transformation pathways. There are additional difficulties in obtaining insights into the underlying phenomena. For instance, the unstable, rapid and dynamic nature of the powder-based AM processes and the microscopic scale of the melt pool behaviour make it difficult to gather crucial information through in-situ observations of the process. Therefore, it is unsurprising that many of the mechanisms responsible for the final microstructures—including defects—found in AM parts are yet to be fully understood. Fortunately, however, computational modelling provides a means for recreating these processes in the virtual domain for testing theories—thereby discovering and rationalising the potential influences of various process parameters on microstructure formation mechanisms. In what is expected to be fertile ground for research and development for some time to come, modelling and experimental efforts that go hand in glove are likely to provide the fastest route to uncovering the unique and complex physical phenomena that determine metal AM microstructures. In this short Editorial, we summarise the status quo and identify research opportunities for modelling microstructures in AM. The vital role that will be played by machine learning (ML) models is also discussed.

Roughly Spherical: Tailored PMMA-SiO2 Composite Supraparticles with Optimized Powder Flowability for Additive Manufacturing.

Particulate materials with well-engineered properties are of key importance for many aspects in our daily life. Polymer powders with high flowability, for example, play a crucial role in the emerging field of powder-based additive manufacturing processes. However, the polymer- and composite material selection for these technologies is still limited. Here, we demonstrate the design of spherical polymethyl methacrylate (PMMA) and PMMA-SiO2 composite supraparticle powders with excellent powder flowability and tailored composition for powder-based additive manufacturing. Our process assembles these powders from the bottom up and affords a precise control over surface roughness and internal morphology via the choice of colloidal primary particles. We establish process-structure-property relationships connecting external spray-drying parameters and primary particle sizes with the resulting supraparticle roughness and, subsequently, with the macroscopic powder flowability and powder bed density. In a second step, we demonstrate the control of composition and internal morphology of PMMA-SiO2 composite supraparticles based on different mass mixings and diameter ratios of the two primary particle dispersions. Finally, we successfully apply the prepared supraparticle powders in powder bed additive manufacturing. The optimized flowability of the composite powders allows the production of two-layered square specimens with fusion between the individual layers and a uniform and tunable distribution of nanoscale SiO2 additives without requiring the addition of any flowing aids.

Metallographic Preparation of Single Powder Particles

Abstract This work developed a systematic method for a metallographic preparation of single powder particles with diameters of approx. 20 to 40 μm. It was motivated by the objective of understanding additive manufacturing processes such as Laser Powder Bed Fusion. A fundamental aspect of the relationship between manufacturing, structure, and properties is the correlation of rapid solidification and resulting microstructure. During powder-based additive manufacturing processes, cooling rates up to 1 MK/s are attained. A thermal analysis determining the characteristics of solidification at such rapid cooling rates can be performed with the aid of chip sensor-based, dynamic Differential Fast Scanning Calorimetry, DFSC. For this purpose, the heat flow during the solidification of single powder particles is measured and, for instance, the solidification onset temperature is evaluated as a function of cooling rate. It is thus possible to estimate the undercooling which has a significant impact on the resulting structure. Subsequently, cross sections of single powder particles must be prepared for the analysis of the resulting structure.

Designing advanced intermetallic titanium aluminide alloys for additive manufacturing

Lightweight intermetallic γ-TiAl based alloys are innovative high-temperature structural materials. So far, these alloys are in use as turbine blades or turbocharger turbine wheels in advanced aerospace and automotive engines, where they are produced by means of investment casting as well as wrought processing, e.g. hot-forging. Through the development of powder-based additive manufacturing processes within the last decade, a real paradigm shift for future component production as well as their design and materials properties was created. While so-called proven alloy systems are presently used worldwide for additive manufacturing, the approach of this work is the development of novel process-adapted γ-TiAl based alloys, which on the one hand fulfill the specific requirements of additive manufacturing and on the other hand provide excellent high temperature properties after a suitable heat treatment. Based on the concept of an engineering γ-TiAl based alloy, i.e. the so-called TNM alloy, two alloys are presented. Due to the chemical reactivity of titanium aluminide alloys, electron beam melting processes come into consideration as production methods using optimized manufacturing parameters, providing dense components with only small variations in the Al content between the individual powder layers, which is a decisive factor for the subsequent heat treatment above the γ solvus temperature. The additively produced samples show a fine equiaxed microstructure, whereas the heat-treated samples exhibit a fully lamellar α₂/γ microstructure with an excellent creep resistance. In summary, the adaptation of the additive manufacturing parameters in combination with innovative alloys and subsequent heat treatments are the basis for producing reliable high-performance TiAl components in the near future.

On the development of pseudo-eutectic AlCoCrFeNi2.1 high entropy alloy using Powder-bed Arc Additive Manufacturing (PAAM) process

A new Powder-bed Arc Additive Manufacturing (PAAM) processing which includes on-line remelting of deposited material has been developed for the manufacturing of high entropy alloys (HEAs) based on an existing AlCoCrFeNi2.1 pseudo-eutectic system. The remelting process is typically applied in the arc melting process to improve the homogeneity of prepared material. We investigated the microstructure and mechanical properties of produced AlCoCrFeNi2.1 HEA after applying a remelting process (1, 3, and 6 times) on each deposited layer. The results show the formation of the pseudo-eutectic microstructure, which consists of relatively large columnar grains of the dominant FCC phase (~90 wt%) and fine dendritic grains of the minor BCC phase (~10 wt%). The applied layer-remelting process shows negligible effects on the phase fractions and their compositions, however, it significantly degraded the tensile strength and ductility of prepared alloys. Particularly, the ductility of the alloy reduced dramatically from about 27% after one time layer-remelting to only about 3% after 3 times layer-remelting. This is rationalised by the significant localisation of thermally induced plasticity caused by repeated remelting of deposited material. We also show that this thermally induced plasticity leads to an increased amount of local misorientation in both constitute phases, which suggests an increased amount of stored dislocations in the microstructure. Despite the potentially strain hardening due to this accumulation of the thermally induced plasticity, the appreciable growth and constrained dendritic morphology of BCC grains that developed after remelting play a prevailing role on the materials strength, which limit the interfacial strengthening of the eutectic microstructure and consequently result in the loss of the tensile strength. The obtained results will assist in the further development and microstructure optimisation of novel HEAs using powder-based additive manufacturing processes.

Bottom-Up Design of Composite Supraparticles for Powder-Based Additive Manufacturing.

Additive manufacturing promises high flexibility and customized product design. Powder bed fusion processes use a laser to melt a polymer powder at predefined locations and iterate the scheme to build 3D objects. The design of flowable powders is a critical parameter for a successful fabrication process that currently limits the choice of available materials. Here, a bottom-up process is introduced to fabricate tailored polymer- and composite supraparticles for powder-based additive manufacturing processes by controlled aggregation of colloidal primary particles. These supraparticles exhibit a near-spherical shape and tailored composition, morphology, and surface roughness. These parameters can be precisely controlled by the mixing and size ratio of the primary particles. Polystyrene/silica composite particles are chosen as a model system to establish structure-property relations connecting shape, morphology, and surface roughness to the adhesion within the powder, which is accessed by tensile strength measurements. The adhesive properties are then connected to powder flowability and it is shown that the resulting powders allow the formation of dense powder films with uniform coverage. Finally, successful powder bed fusion is demonstrated by producing macroscopic single layer specimens with uniform distribution of nanoscale silica additives.

A new approach to eliminating enclosed voids in topology optimization for additive manufacturing

Topology optimization is increasingly used in lightweight designs for additive manufacturing (AM). However, conventional optimization techniques do not fully consider manufacturing constraints. One important requirement of powder-based AM processes is that enclosed voids in the designs must be avoided in order to remove and reuse the unmelted powder. In this work, we propose a new approach to realizing the structural connectivity control based on the bi-directional evolutionary structural optimization technique. This approach eliminates enclosed voids by selectively generating tunnels that connect the voids with the structural boundary during the optimization process. The developed methodology is capable of producing highly efficient structural designs which have no enclosed voids. Furthermore, by changing the radius and the number of tunnels, competitive and diverse designs can be achieved. The effectiveness of the approach is demonstrated by two examples of three-dimensional structures. Prototypes of the obtained designs without enclosed voids have been fabricated using AM.