Powder Spreading Research Articles

Experimental metrics of the powder layer quality in the selective laser sintering process

According to the literature, the microscopic quality of the powder layer produced in the Selective Laser Sintering (SLS) process is related to the onset of macroscopic defects of the produced powder. This study proposes an experimental procedure able to quantify the quality of the powder layer obtained in the spreading step of the SLS process. A dedicated experimental set-up was developed, able to mimic the powder spreading step of the SLS process and to allow the photographic analysis of its surface. Four commercial polymeric powders for SLS applications were tested at two different speeds of the recoater. An image processing analysis was developed, converting a series of microscopic images of layer surface in grey level profiles along the spreading direction. The grey level profiles were further analysed with a wavelet analysis tool, and the major features of the wavelet powder spectral density were used to calculate specific indicators of the powder layer quality. The different indicators provide consistent results comparing the tested powders and the testing conditions. The powder ranking according to spreadability indexes differs from the one obtained using flowability indexes. This finding confirms that spreadability cannot be directly related to flowability.

Study on powder particle behavior in powder spreading with discrete element method and its critical implications for binder jetting additive manufacturing processes

ABSTRACT Understanding powder bed system behaviour in powder spreading is a fundamental issue in binder jetting additive manufacturing (BJAM). This work established a discrete element model incorporating a parallel bond model to compatibly depict local cross-links between powder particles. BJAM parameters including layer thickness, gap compensation, recoat speed, rotation speed, and layer number were studied quantitatively for their effects on recoated powder's packing density and microscopic pore size and bonded layer's breakage and layer shift. Evolutions and influence mechanisms on both layer shift and bond breakage were further elucidated. Some practical implications include: gap compensation corresponding to an ideal recoated powder structure is ∼75 μm; rotation speed should be controlled at 40–120 rad/s to avoid low-rotation-speed layer shift surge and high-rotation-speed breakage; layer shift occurring at a certain stage is irreversible and must deserve well-maintained. This research can provide theoretical guidance for developing BJAM and even support-free powder bed – based additive manufacturing.

An investigation of the effect of powder flowability on the powder spreading in additive manufacturing

Identification of the most reliable method to characterise powder flow behaviour in correlation with the conditions of powder spreading in additive manufacturing (AM) is still challenging. In this study, a number of standard and advanced flowability techniques were used to characterise the flowability of two grades of Ti6Al4V powder (gas atomized, GA, and hydride-dehydride, HDH) used for the powder bed fusion (PBF) based AM. In parallel, the powder spreading behaviour was characterised using an in-house spreading rig. It is found that GA powder has better spreading behaviour than HDH, owing to its better flowability due to the regular particle shapes. However, none of the flow test techniques investigated in this paper can offer a correlation between the dynamic powder flow and powder spreadability at varying speeds. The study in this work has revealed the shortcomings in correlating the flowability of powder and their spreadability under real process conditions. • Flowability of two grades of Ti6Al4V powder was characterised using a range of techniques. • The powder spreading behaviour was characterised using an in-house spreading rig. • Caution is needed when correlating powder flow behaviour with the spreadability. • The powder flow behaviour obtained in current study cannot predict the dynamic behaviour of spreading.

Molecular Dynamics Simulation of NiTi Shape Memory Alloys Produced by Laser Powder Bed Fusion: Laser Parameters on Phase Transformation Behavior.

In this study, the deposition, powder spreading, and laser fusion processes during the laser powder bed fusion (L-PBF) process were studied using molecular dynamics (MD) simulation. The effect of Ni content on the characteristic phase transformation temperatures was also investigated. Shape memory effect and superelasticity of NiTi alloys with Ni content ranged from 48.0% to 51.0% were analyzed. By employing MEAM potentials, the effects of the laser power, spot diameter, and scanning speed on the molten pool size and element evaporation were studied. Simulation results showed that a larger spot diameter renders a higher Ni content in the molten pool, also a larger molten pool. A faster scanning speed leads to a higher Ni content in the molten pool, and a smaller molten pool. The element is difficult to evaporate using small laser power and a large spot diameter. The element in the molten pool expresses a great evaporation effect when the Es is larger than 0.4 eV/ų. According to Ni content within the molten pool during laser fusion, characteristic phase transition temperatures in single crystalline NiTi alloys with variant Ni content were investigated by employing a 2NN-MEAM potential. Characteristic phase transition temperature changes as the Ni content increases from 48.0% to 51.0%. Austenite boundaries and Ni content in the boundary were found to be the keys for controlling the characteristic phase transformation temperature.

Research on improving the spreadability of viscous powder in additive manufacturing

The cohesive effect between particles is crucial in influencing the quality of the powder layer in additive manufacturing (AM), which will induce low reproducibility of the subsequent particle fusion process and degrade the performance of final products. In this work, the phenomenon and mechanism of interparticle cohesive effect were investigated through numerical simulations, based on which the methods that may reduce the negative effects of high cohesive interactions were proposed, assessed, and optimized. Results indicated that increasing the particle size could weaken the cohesion and effectively improve the packing fraction of the powder layer, but the surface roughness becomes worse due to the serious boundary effect of large particles under the blade. Besides, the spreading of viscous powders at low velocity and high deposition height could facilitate dense powder layers to some extent, while it contradicts the rapid fabrication and thin layer thickness required by AM. In contrast, the methods of increasing the friction resistance of substrate and optimizing the blade geometry could recover the powder layer quality under multiple indicators through limiting the scattered motion of particles and facilitating powder downward deposition, respectively. Consequently, the optimal approach was preferentially proposed to reduce the cohesive effect during spreading and obtain the powder layer with optimum packing fraction, uniformity, and surface roughness. On this basis, the operation window was further extended to high velocity and low deposition height, which can provide effective references for the practical AM process. • Cohesive effects on spreading of Ti6Al4V powders were numerically investigated. • Methods that reducing the cohesive effects on powder spreading were proposed. • Effectiveness/adaptability of these methods were assessed from parametric studies. • The underlying mechanisms were analyzed and corresponding solutions were provided.

Raking Process for Powder Bed Fusion of Ti–6Al–4V Alloy Powder Analyzed by Discrete Element Method

In order to avoid the formation of defects in additive manufacturing (AM) by powder bed fusion (PBF) process, it is crucial to understand the relationship between the quality of powder bed and a powder spreading process. In this study, the influences of conditions of powder raking process on the densities and homogeneity of powder bed have been examined by computer simulation using Discrete Element Method (DEM) and experiment of powder bed formation using a blade-type spreader for Ti–6Al–4V powder by way of example. The results were analyzed with a special focus on the effects of the relative size of powder particles with respect to the gap between the blade and the build platform. It has been clearly shown that the gap needs to be larger than the upper bound of the distribution of powder particles diameter to obtain a high-density powder bed. The DEM simulation indicated that the blade can sweep even powder particles that are not in direct contact with the blade when the powder particles are in a close-packed tetragonal configuration. This is the probable reason for the experimental fact that powder particles smaller than half of the gap are suitable for PBF.

Simulation of powder spreading of functionally graded materials in powder bed fusion additive manufacturing

Simulation of powder spreading of functionally graded materials in powder bed fusion additive manufacturing

A process to spatially control the fraction of SS420 and bronze phases in binder jet infiltrated parts

Additive manufacturing (AM) is a useful tool to fabricate components with unique spatial control over material composition, phases, and geometry. However, spatially controlling the material phases in AM metals typically requires changing powder during the printing process or using multiple nozzles, and most methods only offer control in one dimension. This requires a significant printer hardware upgrade. This paper presents a method that exploits the binder jet additive manufacturing process to spatially control the fraction of stainless steel 420 (SS420) and infiltrated bronze. In our method, we modify the CAD file of the binder jet part to include completely enclosed voids within the printed part, which result in enclosed regions of loose steel powder without binder. This process does not induce extra porosity, nor require hardware modifications. Post-sintering, we use optical microscopy to show that zones of enclosed SS420 without binder contain up to a 25 % increase in SS420 phase compared to the zones printed using the conventional method (i.e., with binder). To understand the mechanisms behind the spatial distribution of phase fraction, we employ the method to print parts with higher SS420 concentration channels of different thicknesses in horizontal and vertical directions. Results show that the relative phase fraction of SS420 and bronze depends on channel size, channel orientation, and sintering direction. Further, the SS420 percentage can be uniform or spatially graded inside the channels depending on the sintering direction relative to the printing directions. We hypothesize that the underlying mechanisms of phase fraction variation in this method are powder spreading, packing during the print process as well as the effect of gravity on loose powder during sintering step. To establish a possible application of the method, the spatial variation of Rockwell B hardness was measured in selected samples. The hardness results show that our method obtains spatial variation of mechanical properties, and qualitatively corroborate the phase fraction variation obtained from optical microscopy. Although here we show phase fraction control over two dimensions, the method could be applied to obtain a 3D phase fraction control. The method only requires changes in the CAD model of the printed part, without any hardware or software modifications of the typical binder jet AM process.

Powder spreading over realistic laser melted surfaces in metal additive manufacturing

Powder recoating is a key step in metal Additive Manufacturing (AM) processes where powder is spread across laser processed surfaces to add material for the next layer. Achieving the desired thin powder layers that are both sufficiently dense and uniform is essential for maintaining the requisite geometric tolerances and final part quality. In this study, we focus on the influence of the substrate surface topography by comparing spreading performance over a set of realistic surfaces. We simulate powder spreading over these surfaces using a calibrated non-spherical particle Discrete Element Model for Ti-6Al-4V that incorporates cohesion and Coulomb friction interactions between particles and surfaces. We identify the four key length scales of the recoating process determined by frictional contacts, powder size distribution, the layer thickness and the melted surface topography. We find that realistic AM surfaces show markedly different powder coverage compared to an idealised flat-plane. Rougher surfaces are found to be recoated with larger amounts of powder than smoother surfaces, as smaller particles get trapped by the grooves and valleys across the surface. Counterintuitively, we find that a finer more cohesive powder can achieve the best layer coverage over realistic surfaces - indicating that powder flowability is an incomplete measure of powder spreading performance on realistic AM surfaces. We also demonstrate how the recoating process can significantly size segregate the feedstock powder, favouring deposition of smaller sized particles on the melted surfaces.

Preparation and properties of CoCrMo-Ni@Al2O3 composite by selective laser melting

In this study, nickel coated alumina (Ni@Al 2 O 3 ) particles were prepared via electroless plating, and ball milled with CoCrMo alloy powder in the proportion of 0 wt% to 2 wt%. Then the Ni@Al 2 O 3 reinforced CoCrMo alloy were manufactured by selective laser melting (SLM) process. The microstructure, mechanical property and wear resistance performance of the CoCrMo alloy were characterized. By increasing the content of Ni@Al 2 O 3 particles from 0 wt% to 1.0 wt%, the CoCrMo alloy kept flawless with the highest hardness of 435 HV 1 and best abrasion performance, which could be attributed to the pinning dislocation slip effect of Al 2 O 3 phase and the metallurgical bonding of Ni phase with CoCrMo alloy during the SLM process. When the content of Ni@Al 2 O 3 increased to 2 wt%, the inconsistent fluidity between Ni@Al 2 O 3 and CoCrMo powders has led to the uneven distribution of mixed particles during the powder spreading process, which resulted in the lowest compressive strength and wear resistance. • In the field of joint replacement surgery, the SLM-processed CoCrMo alloy implants are gaining more popularity for their excellent mechanical properties. In order to promote the wear resistance and prolong the service life of implants, small amounts of ceramic particles can be added into the alloy matrix. • In this work, we have fabricated the uniformly core-shell structure of Ni coated Al 2 O 3 particle by electroless plating, and the CoCrMo composites with different amounts of Ni@Al 2 O 3 particles were prepared by SLM technology. As the Ni phase acted as a bridge during the melting process, the surface of CoCrMo-Ni@Al 2 O 3 composites were smooth without obvious cracks. Moreover, the CoCrMo composites demonstrated better wear resistance and stable coefficient of friction for the introduction of Al 2 O 3 .

Electrostatic powder spreading for metal powder bed fusion applications

Typical powder bed fusion processes spread each layer of powder by pushing it across the build area with a spreader bar or roller. While simple, these methods require good flowing powder and do not have the ability to place more than one powder type per layer. This naturally limits the ability to incorporate more than one material onto each powder layer in powder bed additive manufacturing processes. Here we demonstrate electrostatic powder spreading, a method to deposit a powder layer without mechanical contact with the previous layers. Electrostatic powder spreading (ESPS) uses an electric field formed between a powder container and a counter electrode to move powder particles from the container to the powder bed. We show that the rate at which powder is deposited can be controlled by adjusting the strength of the electric field. Correspondingly, the deposited layer thickness is controlled by the strength of the electric field and the recoating speed. To demonstrate the feasibility of ESPS for laser powder bed fusion powder spreading, nearly fully dense (> 99.8%) coupons were built in a commercial L-PBF machine using the ESPS setup. Finally, we achieve 2D patterning of a single layer by using an array of electrodes and switching the applied electric field on and off. ESPS represents a method to produce an arbitrary patterned multi-material powder bed without complicated powder removal steps and easy implementation into existing L-PBF machines. Furthermore, ESPS presents an opportunity to build parts with 3D gradients in material properties.

Laser powder bed fusion of poly-ether-ether-ketone/bioactive glass composites: Processability, mechanical properties, and bioactivity

Poly-ether-ether-ketone (PEEK) implants fabricated by laser powder bed fusion (LPBF) are promising candidates for bone tissue engineering because of the excellent biocompatibility of the material and the ability to realize personalized bone repair. However, the weak LPBF processability and biological inertness of PEEK limit the clinical application. In this work, bioactive glass (BG) is blended into PEEK and found to improve the LPBF processability and bioactivity. The results show that PEEK/BG composite powders exhibit better LPBF processability due to the wider sintering window (48.9%–79.1% wider) and higher thermal conductivity (5.7%–23.0% higher) compared with the pure PEEK as well as the crystallization inhibition during the cold powder spreading. The melting enthalpy and thermal stability of the composite reduce when the BG content increases, thereby leading to the decrease of the optimal laser power during the LPBF process. The modulus of PEEK/BG composites ranges from 2685.82 MPa to 3729.33 MPa, which can match the modulus of human cancellous bone. The variation of lattice constant c and cell volume with the laser power of the composites all show a similar trend to the mechanical properties. BG can promote hydroxy-carbonate-apatite deposition, suggesting that BG has great potential to promote osteogenesis. By varying the amount of BG incorporated, the PEEK composite implants can be applied to different regions in the body depending on the specific clinical requirements.

Difference between powder bed density and green density for a free-flowing powder in binder jetting additive manufacturing

In binder jetting additive manufacturing, the final part density is closely related to powder bed density and green density. Though powder bed density is considered one of the most critical factors to control and predict green density, their difference has not been fully understood. In this work, experiments and simulations were employed to investigate their difference for a free-flowing powder in a counter-rotating roller powder spreading system. Using an alumina powder with excellent flowability, both experiments and simulations show that powder bed density is higher than green density. Furthermore, simulations provide an in-depth understanding of the density difference. Specifically, in the powder bed density scenario where particles are able to move across different powder layers, a slower powder flow with a smooth velocity transition is observed. In the green density scenario where powder is spread on a printed powder layer, the confined layer space generates a powder flow with higher velocity and more turbulence. As a result, the powder packing structure in the green density scenario has more void space near layer interface than that in the powder bed density scenario. This paper reports a reason for the difference between powder bed density and green density for the first time.

A literature review on powder spreading in additive manufacturing

Powder-bed additive manufacturing, including powder bed fusion and binder jetting, has a wide range of applications in various industries. Powder spreading is a critical step of powder-bed additive manufacturing and has a determinative impact on powder bed quality and thus final part quality. This paper provides a literature review on powder spreading, focusing on the effects of influencing factors on powder bed quality. Three groups of influencing factors are discussed: spreaders, spreading parameters, and feedstock powder properties. Besides the effects of individual factors, the interaction effects between these factors are also discussed where applicable. Powder bed quality is discussed in terms of powder bed density and powder bed surface condition. Furthermore, knowledge gaps and research opportunities are presented as concluding remarks.

Powder-bed-fusion additive manufacturing of molybdenum: Process simulation, optimization, and property prediction

In this paper, the whole process of laser powder-bed-fusion (LPBF) additive manufacturing (AM) in the fabrication of molybdenum (Mo) material was numerically reproduced. Firstly, parameters of Mo powder with continuous size distribution utilized in actual AM production were calibrated and input into discrete element model (DEM) for parametric study on powder spreading. Then, the laser melting of the spread powder bed was simulated by computational fluid dynamics (CFD). On this basis, a back propagation neural network (BPNN) model was built for powder bed quality and molten track property prediction and evaluation. Results show that properly reducing the spreading velocity V or increasing the gap height H can contribute to the optimal structure of the powder bed. Corresponding mechanism analyses reveal that the residual velocity of particles and force chain block are the main reasons for the decrease of powder bed quality. And the molten track performance is not positively correlated with the packing density of the powder bed due to the defects such as balling and porosity caused by the over-thickness of powder bed. The selection rule of powder bed should satisfy as higher as possible the packing density within the bed thickness threshold. The BPNN model can accurately predict the powder bed quality and the molten track property and develop a reasonable map for the appropriate choice of operating parameters in real processes.

Powder spreading and spreadability in the additive manufacturing of metallic materials: A critical review

This review aims to build a coherent picture of the problem of powder spreading and spreadability in metal Additive Manufacturing (AM) because of its impact on ensuring highly consistent production, optimization of the process and reduction of the manufacturing costs. The review shows the current progress in understanding spreading dynamics, the role of powder characteristics, the spreading systems and the testing tools developed for assessing powder spreadability. The problem of finding appropriate quantitative metrics and the recent advances in the use of standardized methods to assess powder spreadability is critically discussed. Attention is given to future trends and research gaps and opportunities.

Dry powder coating in additive manufacturing

Dry powder coating is used in many industries to tailor the bulk solid characteristics of cohesive powders. Within this paper, the state of the art of dry coating of feedstock materials for powder based additive manufacturing (AM) processes will be reviewed. The focus is on feedstock materials for powder bed fusion AM processes, such as powder bed fusion of polymers with a laser beam and powder bed fusion of metals with lasers or an electron beam. Powders of several microns to several ten microns in size are used and the feedstock’s bulk solid properties, especially the flowability and packing density are of immanent importance in different process steps in particular for powder dosing and spreading of powder layers onto the building area. All these properties can be tuned by dry particle coating. Moreover, possibilities to improve AM processability and to manipulate the resulting microstructure (c.f. grain refinement, dispersion strengthening) by adhering nanoparticles on the powders will be discussed. The effect of dry coating on the obtained powder properties along the whole AM process chain and the resulting part properties is assessed. Moreover, appropriate characterization methods for bulk solid properties of dry-coated AM powders are critically discussed.

Particle scale modelling of powder recoating and melt pool dynamics in laser powder bed fusion additive manufacturing: A review

Particle scale modelling of the process physics involved in laser powder bed fusion (LPBF) is a recent research hotspot, and many efforts have been made in the literature. However, a comprehensive review of the physics in LPBF and the effects of key variables such as powder- and operation-related parameters, and the mechanisms of defects formation is still lacking. This paper aims to offer a state-of-the-art review on multi-physics related to metal powder recoating and further melting and solidification process. The studies on powder bed recoating explored by discrete element method are presented first, including model theory and validation, effects of process parameters, and physics of particle flow and size segregation. Then powder melting approach based on computational fluid dynamics and the involved phenomena such as melt pool dynamics, keyhole dynamics, defects formation mechanisms of pores, and balling and spattering are described. The needs for future research are also discussed. • Powder bed recoating explored by discrete element method (DEM) is reviewed. • Physics of powder flow and size segregation in powder spreading is presented. • Powder melting based on computational fluid dynamics (CFD) is summarized. • Melt pool flow dynamics and defects formation are discussed.

Multivariate correlation of PolyArylEtherKetone powder properties for additive manufacturing and a method for predicting spreading in polymer powder bed fusion

In a study of unique scale, twenty-four milled Polyaryletherketone (PAEK) polymer powders produced during the development of new grades for Powder Bed Fusion (PBF) were tested using a universal powder rheometer and particle size and shape analyser. Multivariate correlation was used to identify the linear relationships between bulk and dynamic properties and particle size. The flow energy, which measures the energy required to displace powder when in a loosely packed state, was found to have very strong relationships with both the powder density and its compressibility, and both the density and compressibility share a very strong relationship with each other. Partition modelling determined that normalised aeration sensitivity (NAS) was the key indicator when predicting powder spreading. The study highlights the importance for complete and pertinent datasets to allow the development of accurate correlations and the need to capture the PBF spreading performance when developing materials for additive manufacturing. • Bulk and dynamic flow properties are captured with a Universal Powder Rheometer. • Multivariate Correlation interprets linear relationships between properties. • Key relationships between PSD, Circularity and Powder Rheology are identified. • Normalised Aeration Sensitivity used to predict spreading.

Deep Learning Applied to Defect Detection in Powder Spreading Process of Magnetic Material Additive Manufacturing.

Due to its advantages of high customization and rapid production, metal laser melting manufacturing (MAM) has been widely applied in the medical industry, manufacturing, aerospace and boutique industries in recent years. However, defects during the selective laser melting (SLM) manufacturing process can result from thermal stress or hardware failure during the selective laser melting (SLM) manufacturing process. To improve the product’s quality, the use of defect detection during manufacturing is necessary. This study uses the process images recorded by powder bed fusion equipment to develop a detection method, which is based on the convolutional neural network. This uses three powder-spreading defect types: powder uneven, powder uncovered and recoater scratches. This study uses a two-stage convolutional neural network (CNN) model to finish the detection and segmentation of defects. The first stage uses the EfficientNet B7 to classify the images with/without defects, and then to locate the defects by evaluating three different instance segmentation networks in second stage. Experimental results show that the accuracy and Dice measurement of Mask-R-CNN network with ResNet 152 backbone can reach 0.9272 and 0.9438. The computational time of an image only takes approximately 0.2197 sec. The used CNN model meets the requirements of the early detected defects, regarding the SLM manufacturing process.