Powder-bed Additive Manufacturing Process Research Articles

Noncontact measurement of density and thermal properties of SS 316L powder bed through flash thermography

PurposePowder bed density is a key parameter in powder bed additive manufacturing (AM) processes but is not easily monitored. This research evaluates the possibility of non-invasively estimating the density of an AM powder bed via its thermal properties measured using flash thermography (FT).Design/methodology/approachThe thermal diffusivity and conductivity of the samples were found by fitting an analytical model to the measured surface temperature after flash of the powder on a polymer substrate, enabling the estimation of the powder bed density.FindingsFT estimated powder bed was within 8% of weight-based density measurements and the inferred thermal properties are consistent with literature findings. However, multiple flashes were necessary to ensure precise measurements due to noise in the experimental data and the similarity of thermal properties between the powder and substrate.Originality/valueThis paper emphasizes the capability of Flash Thermography (FT) for non-contact measurement of SS 316 L powder bed density, offering a pathway to in-situ monitoring for powder bed AM methods including binder jetting (BJ) and powder bed fusion. Despite the limitations of the current approach, the density knowledge and thermal properties measurements have the potential to enhance process development and thermal modeling powder bed AM processes, aiding in understanding the powder packing and thermal behavior.

Development of Analysis Method for Laser Metal Powder Bed Additive Manufacturing Process by Lattice Boltzmann・Multi-Phase Field Methods

Development of Analysis Method for Laser Metal Powder Bed Additive Manufacturing Process by Lattice Boltzmann・Multi-Phase Field Methods

Explosive fragmentation of additively manufactured stainless steel

Properties of fragmentation from an explosively driven 316L stainless steel spherical shell section fabricated by a laser powder bed additive manufacturing process with minimal surface finishing are investigated. This shell is driven by an insensitive high explosive, resulting in high strain rate deformation (>8 × 103 s−1) and failure of the stainless steel. Photonic Doppler velocimetry measures the expansion rate; dynamic radiography and high-speed imaging capture the fracture behavior of the stainless steel. The fracture response of the additively manufactured stainless steel shell is compared to published experimental results on additively manufactured 316L stainless steel and conventionally manufactured wrought 316L and 304 stainless steel shell fragmentation. Despite preferred crack orientation, suggesting the influence of surface grooves on fracture time, fragment size is identical to that measured in a similar experiment on wrought 304 stainless steel. Further analysis indicates that the 316L additively manufactured stainless steel shell exhibits comparable spall strength and fragmentation toughness to conventionally manufactured stainless steel yet lower failure strain due to surface stress concentrations.

An efficient ray tracing methodology for the numerical analysis of powder bed additive manufacturing processes

An efficient ray tracing methodology for the numerical analysis of powder bed additive manufacturing processes

Tensile properties of SS316L produced by LPBF: Influence of specimen dimensions and surface condition

This study is part of the global effort to develop precise and accurate mechanical testing methodologies for metallic parts in as-built condition produced by powder-bed additive manufacturing processes. Miniature 316L stainless steel specimens with a 7 × 1 × 1.5 mm3 reduced section were produced by laser powder bed fusion. Three distinct surface conditions were considered. Standard specimens were also produced for comparison. Special attention was given to the non-destructive measurement of the cross-sectional area of small as-built specimens. The ultimate tensile strength of the as-built miniature specimens was 12% below standard-sized or machined specimens. Using caliper measurements lead to an overestimation of the section by as much as 20% compared to CT-scan values, resulting in an underestimation of UTS. Point micrometer measurements yielded more accurate estimations of cross-sectional area. With the experimental error taken into account, the specimen dimensions and surface condition influenced UTS. A coarser average microstructure for miniature as-built specimens was linked to a reduction of UTS by about 4% compared to standard specimens produced in the same conditions. Despite a larger scatter obtained with miniature specimens, no effect of specimen dimensions on the average value of elongation at break could be observed. Higher surface roughness of the order of Ra = 15 μm resulted in an elongation at break reduced from 52.7 ± 5.2 to 39.2 ± 5.0% for as-built miniature specimens. It was concluded that using large-scale or machined specimens may produce less accurate tensile characterization of thin 316L sections produced by laser powder bed fusion. Mechanical coupons with dimensions comparable with the structural part of interest should be employed. Accurate measurement of the cross-sectional area of small as-built specimens is critical for accurate measurements of mechanical strength. These results rationalize the scatter on tensile properties of LPBF 316L available in the literature.

Processing, microstructures and mechanical response of a β-metastable Ti-14Mo alloy fabricated by Electron Beam Powder Bed Fusion

Defect-tolerant materials are good candidates to be produced by additive manufacturing as parts often suffer from the presence of various kinds of defects: internal (pores) and especially surface defects (roughness). A β-metastable binary Ti-14Mo alloy exhibiting a TWIP effect with a composition adapted to take into account constraints of powder bed additive manufacturing processes was fabricated by electron powder bed fusion (E-PBF). The processing window was identified and dense samples with a relative density > 99.9% measured by X-ray computed tomography were fabricated. Microstructures were examined using metallography, X-ray diffraction, and electron microscopy. The mechanical properties were determined using monotonous and cyclic loading-unloading tensile testing. The as-built microstructure shows a two-phase α + β microstructure with a gradient in size of the α phase along the building direction. Post-fabrication heat treatment is therefore required to achieve a β-metastable microstructure. The peculiarities and similarities with other β-metastable binary Ti-Mo alloys fabricated by the more traditional cast and wrought processing route are highlighted. The possibility to tailor the mechanical response by low-temperature ageing via precipitation of the ωiso phase is also investigated. Such Ti-alloy could be used to improve the energy absorption capacity of architected materials for which the surface-to-volume ratio is very high and thus defect tolerance is of utmost importance.

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.

A new approach to quantify powder's bed surface roughness in additive manufacturing

The powder bed surface roughness plays an important role in the quality of the final parts fabricated using powder bed Additive Manufacturing processes. This paper reports the development and application of a new technique and prototype instrument which can be used to simulate the creation of a powder bed and reveal the surface properties of that bed. The tester was successfully used to study powder bed surface roughness, but can also be used to evaluate powder bed relative packing fraction, change in particle size and shape over the build plate and electrostatic charges over the powder bed. The focus of this paper is on the developments of metrics to define powder bed surface roughness. In this investigation, six plastic and two metal powders, as well as two recoater blade shape, were used. Two gap sizes of the recoaters were tested, namely two and five times higher than the powder D90. A novel shadowgraphy technique based on illuminating the surface with low-angle collimated light and analysing the image was employed to quantify powder bed surface roughness. Two main metrics to quantify the surface roughness of the powder bed were found to be useful. The first metric is amplitude of variation in surface height which is defined as the difference between surface height at each data point and the average height over 100 points. The second metric is wavelength of roughness which is calculated as the average horizontal distance between positive peaks, averaged over 100 data points. The surface roughness results showed that the shadowgraphy technique as well as the metrics developed by this method to quantify powder bed surface roughness, are capable of quantifying and distinguishing various powder bed features (and therefore potential quality failures in the bed). These metrics successfully captured the impact of different spreading variables; i.e. recoater shape, gap size and particularly the powder flow functions on the powder bed surface roughness.

Part and supports optimization in metal powder bed additive manufacturing using simplified process simulation

This paper is concerned with shape and topology optimization of parts and their supports, taking into account constraints coming from the metal powder bed additive manufacturing process. Despite the high complexity of this process, it is represented by the simple inherent strain model, which has the advantage of being computationally cheap. Three optimization criteria, evaluated with this model, are proposed to minimize defects caused by additive manufacturing: vertical displacements, residual stresses and deflection of the part after baseplate separation. Combining these criteria with a constraint on the compliance for the final use of the part leads to optimization problems which deliver optimized manufacturable shapes with only a slight loss on the final use performance. The numerical results are assessed by manufacturing some optimized and reference geometries. These experimental results are also used to calibrate the inherent strain model by an inverse analysis. The same type of optimization is applied to supports in the case of a fixed non-optimizable part. For our 3-d numerical tests we rely on the level set method, the notion of shape derivatives and an augmented Lagrangian algorithm for optimization.

Reliability of metal additive manufactured materials from modeling the microstructure at different length scales

As metal additive manufacturing transitions from a prototypical manufacturing process to producing in-service parts, there is an urgent need for methodologies that are capable of predicting material response and reliability. There is a large body of research that examines physics-based methodologies and, more recently, data-driven models to simulate the relationships surrounding the process–structure–properties paradigm of additive manufactured materials. Both approaches share the same objective; namely, for a given set of process parameters, predict the resulting micro-structure and/or mechanical response of the printed material. Physics-based methodologies come with a high computational cost as the physical phenomena behind the manufacturing process spans multiple length and time scales. Conversely, data-driven models have a low computational cost at the expense of by-passing the physical mechanisms and instead finding correlation between diverse input and output data sets. As a result, the interpretation of data-driven models can be difficult and they have the potential to be bias and brittle. This paper presents a novel workflow that takes into consideration process parameters, build strategy and data obtained from standard material science tests to develop realistic, statistical, finite element models of material micro-structure that can be used to predict reliability without the need to explicitly model the physics behind the manufacturing process. Using micro-structural information extracted from as-fabricated material builds, we show that porosity can be modeled using marked spatial point patterns and scan track morphology can be idealized as concentric, multi-phase, half cylindrical volumes assembled according to the build strategy specified for the material. Furthermore, we show that the finite element model can be tuned to experimental test data, consistent with the concurrent or top-down approach in virtual materials testing. To illustrate this process, we apply the workflow to data obtained from various sources in the literature for as-fabricated AlSi10Mg manufactured using selective laser melting (SLM), a powder bed additive manufacturing process.

Mechanized spreading of ceramic powder layers for additive manufacturing characterized by transmission x-ray imaging: Influence of powder feedstock and spreading parameters on powder layer density

Spreading of uniform, dense powder layers is a critical requirement for powder bed additive manufacturing (AM) processes, and layer quality is influenced by powder feedstock selection and spreading parameters. In prior work, quantification of powder layer density has required disruption of the powder layer after spreading, or compromise in the precision and/or design of the spreading mechanism compared to actual AM equipment. This work demonstrates the use of a precision, mechanized powder spreading testbed coupled with transmission x-ray imaging for spatially-resolved, non-contact powder layer density measurements. Specifically, the influence of several variables on the spreading of aluminum oxide powders is studied: powder size and shape, spreading tool choice (i.e., blade versus roller), traverse speed and/or rotation rate, and powder dispensing methodology (i.e., piston-fed vs hopper). For coarse powders, the density of layers spread with a roller geometry outperforms a blade geometry, reaching the tapped density for the coarse spherical powder. In addition, spreading with roller counter-rotation increases layer density for fine powders but decreases layer density for coarse powders. Increasing traverse speed or the use of textured rollers results in reduced powder layer density for fine powders. Finally, for fine powders, deposition with a vibrating hopper dispenser instead of a piston-fed mechanism, coupled with spreading by a counter-rotating roller, gives spread layer density equal to the tapped density.

Plasma Spheroidisation of Irregular Ti6Al4V Powder for Powder Bed Fusion

Metal powders suitable for use in powder bed additive manufacturing processes should ideally be spherical, dense, chemically pure and of a specified particle size distribution. Ti6Al4V is commonly used in the aerospace, medical and automotive industries due to its high strength-to-weight ratio and excellent corrosion resistance properties. Interstitial impurities in titanium alloys have an impact upon mechanical properties, particularly oxygen, nitrogen, hydrogen and carbon. The plasma spheroidisation process can be used to spheroidise metal powder consisting of irregularly shaped particles. In this study, the plasma spheroidisation of metal powder was performed on Ti6Al4V powder consisting of irregularly shaped particles. The properties of the powder relevant for powder bed fusion that were determined included the particle size distribution, morphology, particle porosity and chemical composition. Conclusions were drawn regarding the viability of using this process to produce powder suitable for additive manufacturing.

Optimization of permeable membrane microchannel heat sinks for additive manufacturing

The design freedom brought by additive manufacturing (AM) can be leveraged in the design of microchannel heat sinks to improve their cooling performance. The permeable membrane microchannel (PMM) heat sink geometry was inspired by the ability of powder bed AM processes to fabricate partially porous metal parts having small internal flow features on the order of the powder size. The design routes coolant through a parallel array of thin permeable membranes arranged in a single-layer-manifold configuration. The permeable membranes provide effective heat exchange surfaces and the manifold configuration yields a low flow resistance across the PMM heat sink, all incorporated in a single layer by the use of AM. Past work has introduced the PMM heat sink concept, but the optimal geometric feature sizes were not explored or identified. The n current study is first to explore design optimization of the PMM heat sink to identify target feature sizes for AM fabrication, assessment of the conditions under which the PMM geometry outperforms other standard microchannel heat sink designs, and inspection of the ability of metal 3D printing process to produce the optimal features. To this end, a reduced-order PMM heat sink model is developed, a gradient-based-multi-objective optimization is performed to identify the optimal feature sizes for different coolants (water and 48/52 water/ethylene glycol mixture) at different flow rates (100–500 mL/min), footprint areas (49–900 mm2), and channel heights (0.5–2.5 mm). The optimization results are benchmarked against an optimized straight microchannel (SMC) heat sink design. Optimized PMM designs offer up to 68% lower thermal resistance at a set pressure drop compared to optimized SMC designs. A pair of SMC and PMM heat sinks optimized for the same operating conditions are 3D printed using direct-metal-laser-sintering (DMLS) of AlSi10Mg. X-ray microtomography is used to characterize the geometry of the 3D-printed parts. The model identifies that optimal membrane gap sizes on the order of ~ 10 s μm are required for the PMM to realize performance advantages compared to SMC heat sinks under the same operating conditions. The performance is predicted to be highly sensitive to this pore size, and even though DMLS is shown to produce parts with gaps as small as 26.7 µm, morphological deviations between the design and as-printed part are shown to lead to noticeable performance differences. Albeit excellent performance potential reinforced by this work, these findings call for further AM process development to ensure reliable, as-predicted PMM heat sinks to realize this potential.

Towards an agent-based model to simulate osseointegration in powder-bed 3D printed implant-like structures

The orthopedic industry is still searching for an efficient way to replace bone loss due to surgical procedures such as arthroplasty and limb-sparing surgery. Additive manufacturing (AM) presents an opportunity to manufacture affordable patient-specific implants. Optimization of the implant–bone interface to maximize osseointegration (bone ingrowth) has not been appropriately addressed. Mechanobiological models, suited to predict mechanical adaptation of bone, cannot be used to predict osseointegration inside implants as the implant is not exposed to any mechanical loading until it is fully accepted by the host body. Biological models relying on partial differential equations based on continuum approximation are not well-suited to predict the discrete phenomenon of osseointegration. This study proposes an agent-based modeling (ABM) approach for representing the osseointegration process for orthopedic implants produced by powder-bed additive manufacturing processes. Agent-Based Modeling (ABM) is a cellular automata based discrete computing technique that uses rule-based mathematics derived from experimental studies to simulate evolutionary phenomena. In this paper, osseointegration inside a hexagonal closed packing of AM powder particles is modeled using ABM. Cellular agents such as pre-osteoblasts and osteoblasts are realistically modeled as cubic cells. The proposed model underpredicts osseointegration at early stages but predicts osseointegration at around 21 days with sufficient accuracy when compared to the in vitro test conducted by Xue et al. in 2007.

Fabrication of aluminum/stainless steel bimetallic composites through a combination of additive manufacturing and vacuum-assisted melt infiltration casting

This paper provides a hybrid method for net shape, lattice based, complex bimetallic composites using a combination of laser powder bed additive manufacturing and vacuum-assisted melt infiltration casting process. 316L stainless steel lattice structures were built using a selective laser melting (SLM) technique. Then, their cavities were filled with an aluminum alloy using vacuum-assisted melt infiltration to yield a bimetallic composite. For comparison purposes, monolithic aluminum alloy was also cast under the same casting parameters. Tensile properties of the fabricated stainless steel lattice and bimetallic composite were found to be insignificantly different. This was explained by the observed continuous gap in the 316L stainless steel/aluminum alloy interfaces which prevented load transfer from the stainless steel lattice to the aluminum matrix during tension. However, compressive properties of the bimetallic composite were found to be significantly greater than those of the stainless steel lattice implying that the aluminum alloy matrix plays an important role during compressive deformation of the bimetallic composites. The monolithic aluminum alloy sample exhibited a noticeably higher elastic modulus, yield stress and ultimate tensile strength but a dramatically lower elongation than both the steel lattice and bimetallic composite specimen. Detachment of the stainless steel lattice from the aluminum matrix was determined to be the root cause of failure for the bimetallic composite in tension.

On the effect of irradiance on dimensional accuracy in multijet fusion additive manufacturing

Purpose The amount of radiated energy is known to be a crucial parameter in powder-bed additive manufacturing (AM) processes. The role of irradiance in the multijet fusion (MJF) process has not been addressed by any previous research, despite the key role of this process in the AM industry. The aim of this paper is to explore the relationship between irradiance and dimensional accuracy in MJF. Design/methodology/approach An experimental activity was carried out to map the relationship between irradiance and dimensional accuracy in the MJF transformation of polyamide 12. Two specimens were used to measure the dimensional accuracy on medium and small sizes. The experiment was run using six different levels of irradiance. For each, the crystallinity degree and part density were measured. Findings Irradiance was found to be directly proportional to part density and inversely proportional to crystallinity degree. Higher irradiance leads to an increase in the measured dimensions of parts. This highlights a predominant role of the crystallisation degree and uncontrolled peripherical sintering, in line with the previous literature on other powder-bed AM processes. The results demonstrate that different trends can be observed according to the range of sizes.

A modular testbed for mechanized spreading of powder layers for additive manufacturing.

Powder bed additive manufacturing (AM) processes, including binder jetting (BJAM) and powder bed fusion (PBF), can manufacture complex three-dimensional components from a variety of materials. A fundamental understanding of the spreading of thin powder layers is essential to develop robust process parameters for powder bed AM and to assess the influence of powder feedstock characteristics on the subsequent process outcomes. Toward meeting these needs, this work presents the design, fabrication, and qualification of a testbed for modular, mechanized, multi-layer powder spreading. The testbed is designed to replicate the operating conditions of commercial AM equipment, yet features full control over motion parameters including the translation and rotation of a roller spreading tool and precision motion of a feed piston and the build platform. The powder spreading mechanism is interchangeable and therefore can be customized, including the capability for dispensing of fine, cohesive powders using a vibrating hopper. Validation of the resolution and accuracy of the machine and its subsystems, as well as the spreading of exemplary layers from a range of powder sizes typical of BJAM and PBF processes, are described. The precision engineered testbed can therefore enable the optimization of powder spreading parameters for AM and correlation to build process parameters in future work, as well as exploration of spreading of specialized powders for AM and other techniques.

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We used high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

Layer-wise anomaly detection and classification for powder bed additive manufacturing processes: A machine-agnostic algorithm for real-time pixel-wise semantic segmentation

Increasing industry acceptance of powder bed metal Additive Manufacturing requires improved real-time detection and classification of anomalies. Many of these anomalies, such as recoater blade impacts, binder deposition issues, spatter generation, and some porosities, are surface-visible at each layer of the building process. In this work, the authors present a novel Convolutional Neural Network architecture for pixel-wise localization (semantic segmentation) of layer-wise powder bed imaging data. Key advantages of the algorithm include its ability to return segmentation results at the native resolution of the imaging sensor, seamlessly transfer learned knowledge between different Additive Manufacturing machines, and provide real-time performance. The algorithm is demonstrated on six different machines spanning three technologies: laser fusion, binder jetting, and electron beam fusion. Finally, the performance of the algorithm is shown to be superior to that of previous algorithms presented by the authors with respect to localization, accuracy, computation time, and generalizability.

In-situ optical emission spectroscopy of selective laser melting

The variances in local processing conditions during Selective Laser Melting (SLM), a powder bed Additive Manufacturing (AM) process, can cause defects that lead to part failure. The nature of SLM permits in-situ monitoring of radiometric signals emitted from the part surface during the process, including optical emission from excited alloying elements. Using Optical Emission Spectroscopy (OES) to measure the spectral content of light emitted gives insight into the chemistry and relative intensities of excited species vaporized during SLM processing. The contribution from investigating the use of in-situ OES to gain information about local processing conditions during SLM is reported in this paper. A spectrometer is split into the SLM system laser beam path to measure visible light emitted from the melt pool and plume during the processing of 304L stainless steel. The in-line configuration allows signal collection regardless of the laser scan location. The spectroscopic information is correlated to the melt pool size and features of SLM samples for various build conditions (i.e., process parameters, build chamber atmosphere type, and pressure).The limitations that exist in OES implementation for certain build chamber conditions are discussed. The results in this paper are initial progress towards the use of OES in SLM part qualification and controls applications.