Powder-bed Additive Manufacturing Research Articles

Lightweight Potential of Anisotropic Plate Lattice Metamaterials

Additive manufacturing enables the production of lattice structures, which have been proven to be a superior class of lightweight mechanical metamaterials whose specific stiffness can reach the theoretical limit of the upper Hashin–Shtrikman bound for isotropic cellular materials. To achieve isotropy, complex structures are required, which can be challenging in powder bed additive manufacturing, especially with regard to subsequent powder removal. The present study focuses on the Finite Element Method simulation of 2,5D anisotropic plate lattice metamaterials and the investigation of their lightweight potential. The intentional use of anisotropic structures allows the production of a cell architecture that is easily manufacturable via Laser Powder Bed Fusion (LPBF) while also enabling straightforward optimization for specific load cases. The work demonstrates that the considered anisotropic plate lattices exhibit high weight-specific stiffnesses, superior to those of honeycomb structures, and, simultaneously, a good de-powdering capability. A significant increase in stiffness and the associated surpassing of the upper Hashin–Shtrikman bound due to anisotropy is achievable by optimizing wall thicknesses depending on specific load cases. A stability analysis reveals that, in all lattice structures, plastic deformation is initiated before linear buckling occurs. An analysis of stress concentrations indicates that the introduction of radii at the plate intersections reduces stress peaks and simultaneously increases the weight-specific stiffnesses and thus the lightweight potential. Exemplary samples illustrate the feasibility of manufacturing the analyzed metamaterials within the LPBF process.

Powder BED Additive Manufacturing using Machine Learning Algorithms for Multidisciplinary Applications: A Review and Outlook

Abstract: Additive manufacturing overcomes the limitations associated with conventional processes, such as fabricating complex parts, material wastage, and a number of sequential operations. Powder-bed additives fall under the category of additive manufacturing process, which, in recent years, has captured the attention of researchers and scientists working in various fields of science and engineering. Production of powder bed additive manufacturing (PBAM) parts with consistent and predictable properties of powders used during the manufacturing process plays an important role in deciding printed parts' reliability in aeronautical, automobile, biomedical, and healthcare applications. In the PBAM process, the most commonly used powders are polymer, metal, and ceramic, which cannot be effectively used without understanding powder particles' physical, mechanical, and chemical properties. Several metallic powders like titanium, steel, copper, aluminum, and nickel, several polymer polyamides (nylon), polylactide, polycarbonate, glass-filled nylon, epoxy resins, etc., and the most commonly used ceramic powders like aluminum oxide (Al2O) and zirconium oxide (ZrO2) can be utilized depending upon the method being adopted during PBAM process. Adoption of some post-processing techniques for powder, such as grain refinement can also be employed to improve the physical or mechanical properties of powders used for the PBAM process. In this paper, the effect of powder parameters, such as particle size, shape, density, and reusing of powder, etc., on printed parts have been reviewed in detail using characterization techniques such as X-ray computed tomography, scanning electron microscopy, and X-ray photoelectron spectroscopy. This helps to understand the effect of particle size, shape, density, virgin and reused powders, etc., used during the PBAM process. This article has reviewed the selection of appropriate process parameters like laser power, scanning speed, hatch spacing, and layer thickness and their effects on various mechanical or physical properties, such as tensile strength, hardness, and the effect of porosity, along with the microstructure evolution. One of the drawbacks of additive manufacturing is the variability in the quality of printed parts, which can be eliminated by monitoring the process using machine learning techniques. Also, the prediction of the best combination of process parameters using some advanced machine learning algorithms (MLA), like random forest, k nearest neighbors, and support vector machine, can be effectively utilized to quantify the performance parameters in the PBAM process. Thus, implementing machine learning in the additive manufacturing process not only helps to learn the fundamentals but helps to identify, predict and help to make actionable recommendations that help optimize printed parts quality. The performance of various MLAs has been evaluated and compared for projecting future research directions and suggestions. In the last part of this article, multidisciplinary applications of the PBAM process have been reviewed in detail. Additive manufacturing processes carried out by using conventional machines, called hybrid additive manufacturing, have also been reviewed by discussing their methods and arrangements in detail.

Functionally Graded Steels Obtained via Electron Beam Powder Bed Fusion

Electron-Beam Powder Bed Fusion (EB-PBF) is one of the most important metal additive manufacturing (AM) technologies. In EB-PBF, a focused electron beam is used to melt metal powders in a layer by layer approach. In this investigation two pre-alloyed steel-based powders, stainless steel 316L and V4E, a tool steel developed by Uddeholm, were used to manufacture functionally graded materials. In the proposed approach two powders are loaded into the feeding container, V4E powder on top of 316L one, preventing their mixing. Such type of feeding yields components with two distinct materials separated by a zone with gradual transition from 316L to V4E. Microstructure and local mechanical properties were evaluated in the manufactured samples. Optical Microscopy, Scanning Electron Microscopy and EDX on the polished cross-sections show a gradual microstructural and compositional transition from characteristic 316L at the bottom of the specimens to the tool steel towards the top. Nanoindentation experiments confirmed a consequent gradient in hardness and elastic modulus, which gradually increase towards the top surface of the samples. The achieved results provide great possibilities to tailor the composition, microstructure, mechanical properties, and wear resistance by combining different powders in the powder bed AM technology. Potential applications include the tooling industry, where hard and wear-resistant materials are demanded on the surface with tougher and more ductile materials in the core of the tool.

Residual stress analysis through numerical simulation in powder bed additive manufacturing using the representative volume approach

Residual stress analysis through numerical simulation in powder bed additive manufacturing using the representative volume approach

Quantitative analysis of thin metal powder layers via transmission X-ray imaging and discrete element simulation: Roller-based spreading approaches

A variety of tools can be used for spreading metal, ceramic, and polymer feedstocks in powder bed additive manufacturing (AM) methods. Rollers are often employed when spreading powders with limited flowability, as arises in powders comprising fine particle sizes or high surface energy materials. Here, we study roller-based powder spreading for powder bed AM using the unique combination of a purpose-built powder spreading testbed with a proven method for X-ray mapping of powder layer depth. We focus on the density and uniformity of nominally 100 μm thick layers of roller-spread Ti-6Al-4V and Al-10Si-Mg powders. Our results indicate that when rotation is too rapid, roller-applied forces including shear and medium fluid drag impede the creation of dense and uniform layers from powders of high innate flowability, or where inertial forces driven by particle density dominate cohesive forces. Roller counter-rotation augments the uniformity of cohesive powder layers, primarily though reducing the influence of particle clusters in the flowing powder, which are otherwise shown to cause deep, trench-like streaks. Companion discrete element method (DEM) simulations further contextualize the experiments through isolation of the effects of cohesion on layer attributes. Results suggest that roller motion parameters could apply a strategic level of additional shear force to the flowing powder, thereby mitigating the clumping behavior characteristic of highly cohesive feedstocks while maintaining high layer uniformity.

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.

Comparison between laser and TIG welding of electron beam melted Ti6Al4V parts

Abstract A large number of metal parts specific to the aviation, energy, and biomedical industries are produced by the electron beam melting (EBM) method, which is one of the powder bed additive manufacturing techniques. The limited build volume of EBM machines does not allow the production of parts in the desired dimensions. One way to overcome this limitation is to weld small size additive manufactured parts. In this study, EBMed Ti6Al4V tensile specimens were joined by laser (LBW) and tungsten inert gas (TIG) welding. Welding morphologies, microstructures, and mechanical properties of joints were investigated. The main defects in the samples are pore formation and insufficient penetration. The weld zones of TIG samples contain a higher amount of pores than laser samples, and these pores are distributed over the entire area of the weld. The pores are less than 200 µm in diameter. TIG welded samples exhibited higher mechanical properties than laser welded samples. The highest microhardness was measured in the weld zone. Microhardness of laser welded samples are higher than TIG welded samples. While the welding regions of TIG welded samples consist of coarse and acicular α and α + β structures, laser welded samples consist of thin and acicular α′ structure.

Concurrent topology optimization of parts and their supports for additive manufacturing with thermal deformation constraint

A typical manufacturing failure in powder bed additive manufacturing (AM) is caused by the collision between the already printed structure and the powder recoater due to large thermal deformation. This paper presents a density-based topology optimization (TO) approach to concurrently design parts and their supports that are not susceptible to such a manufacturing failure. The thermal deformation during the layer-by-layer AM process is predicted based on an inherent strain method, and the top surfaces' upward deformations are constrained below the powder layer thickness to avoid recoater collision. To increase the design freedom of TO, the parts and their supports are composed of lattice unit cells with different volume fractions, whose effective stiffness matrixes are predicted by the numerical homogenization and surrogate models. Besides, an overhang constraint and a two-field-based length scale control formulation are also utilized, ensuring overall manufacturability. With the proposed approach, lightweight structures with optimized mechanical properties and controllable manufacturing qualities can be obtained. Numerical examples are given to demonstrate the effectiveness of the proposed approach.

Particle size and shape analyses for powder bed additive manufacturing

Technical advances in dynamic imaging have enabled routine sampling and analysis of particle shape and shape distributions. Size and shape distributions are relevant to many particulate processes involving flow, spreading, packing and densification. Powder bed additive manufacturing is a prime example requiring uniform spreading, packing and sintering of fine metal powders. This study focuses on quantitative representations of shape described in the International Standards Organization specifications and considers three aspects for improvement thereof: (1) reduced-order mapping of shape distributions using principal component analysis of shape descriptors; (2) uncertainty of shape distribution statistics based on pixel resolution; and (3) opportunities for analysis using machine learning for enhanced image resolution.

What alternatives to computed tomography for inspection of additive manufacturing parts with channels

Non-destructive inspection of parts with small diameter channels is a major challenge. Additive Manufacturing (AM) offers many advantages compared to the traditional subtractive manufacturing process for the manufacturing of these complex structures. Thales, Safran and ArianeGroup joined forces to find a way to inspect parts with small diameter channels by technics other than X-ray computed tomography. LNE and Institut de Soudure (French welding institute) worked with them to identify, propose and test non-destructive techniques capable to detect flaws and cavities containing unfused powder unique to the powder-bed fusion AM process category. This paper will present some results of this project called FA- Canalsafe®. Artificial defects created on mock-ups will be described. Some results and limitations on eddy current testing and on visual endoscopy will be discussed. Finally, some recommendations on NDT implementation will be proposed.

On the structural integrity and fatigue performance of additively manufactured Ti-6Al-4V parts processed using mechanically recycled powders

In light of the steadily increasing importance of resource efficiency, powder recycling represents one of the major prospects in additive manufacturing. The present study focuses on Ti6Al4V parts manufactured by electron beam-based powder bed fusion using blends of virgin and recycled powder. The latter powder was gained by mechanical comminution of support structures and, thus, addresses a novel topic beyond the well-known reuse of un-melted powder. Microstructure analysis is conducted by scanning electron microscopy and micro-computed tomography, mechanical properties are analyzed by quasi-static tensile and fatigue tests. Thereby, the applicability of recycled powder is assessed, eventually revealing that mechanically recycled powder can be qualified to partially substitute virgin powder in powder bed additive manufacturing.

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.

Study on the Powder-Spreading Process of Walnut Shell/Co-PES Biomass Composite Powder in Additive Manufacturing.

Powder laying is a necessary procedure during powder bed additive manufacturing (PBAM), and the quality of powder bed has an important effect on the performance of products. Because the powder particle motion state during the powder laying process of biomass composites is difficult to observe, and the influence of the powder laying process parameters on the quality of the powder bed is still unclear, a simulation study of the biomass composite powder laying process during powder bed additive manufacturing was conducted using the discrete element method. A discrete element model of walnut shell/Co-PES composite powder was established using the multi-sphere unit method, and the powder-spreading process was numerically simulated using two different powder spreading methods (rollers/scrapers). The results showed that the quality of powder bed formed by roller laying was better than that formed by scrapers with the same powder laying speed and powder laying thickness. For both of the two different spreading methods, the uniformity and density of the powder bed decreased as spreading speed increased, although the spreading speed had a more important influence on scraper spreading compared to roller spreading. As powder laying thickness increased, the powder bed formed by the two different powder laying methods became more uniform and denser. When the powder laying thickness was less than 110μm, the particles were easily blocked at the powder laying gap and are pushed out of the forming platform, forming many voids, and decreasing the powder bed's quality. When the powder thickness was greater than 140 μm, the uniformity and density of the powder bed increased gradually, the number of voids decreased, and the quality of the powder bed improved.

Effect of powder properties on mesoscale thermal FEM simulations of powder bed additive manufacturing

Numerous studies have used FEM simulations to assess the effects of the heat source parameters on the melt pool volume during metal powder bed additive manufacturing. However, considerable debate still exists on how to incorporate the evolution of the thermophysical properties used to describe the powder as it undergoes heating, melting, consolidation and finally solidification. For single layer studies, since powder volume is much smaller compared to the substrate volume, highly detailed, computationally expensive powder property descriptions may not provide a commensurate increase in accuracy of simulation results. This study aims to quantify the effect of powder properties on the melt pool volume created during electron beam melting of Ti6Al4V powder using predictions from a FEM-based heat conduction model. The dependence of thermal conductivity, specific heat, and density of the powder on temperature and beam power density will be studied. Additionally, the relevance of the powder properties with changing layer height and beam power and speed will also be quantified.

Microphone signal specialities in laser powder bed fusion: single-track scan and multi-track scan

Acoustic emission is a promising candidate among online process monitoring methods in laser powder bed fusion. Although previous studies have demonstrated the feasibility for acoustic-based monitoring, an underlying understanding of the acoustic specialities related to laser–powder interactions in the enclosed chamber is scarce. This research employed a microphone to collect the acoustic emission signal during laser printing processes. Two contents are contained in the raw data: static pressure variation and acoustic signal. The features of each content are investigated and it follows several significant findings. First, more violent fluctuations of ambient gas static pressure in the chamber are due to the high temperature gradient of ambient gas and recoil pressure over the laser-material interaction zone, which typically occurs in a very low frequency band (<22.4 Hz). Second, spectral analysis for the acoustic signals has indicated that standing wave patterns are commonly occurrences in the chamber. The fundamental frequency of the relevant acoustic emission strongly depends on the number of melt tracks scanned per unit time. Additionally, with investigations of single-track scan and multi-track scan, it is certain that more powder particles participated in laser melting can result in larger acoustic emission energy in a relative high frequency range (>10 kHz). For powder bed additive manufacturing, these results offer a guidance for signal processing and machine learning to dig out the signal signatures of a specific defect in terms of acoustic monitoring.

Thermo-Mechanically Assisted Grain Growth in Ti6Al4V Fabricated Using the Powder Bed Additive Manufacturing During High-Temperature Mechanical Testing

Thermo-Mechanically Assisted Grain Growth in Ti6Al4V Fabricated Using the Powder Bed Additive Manufacturing During High-Temperature Mechanical Testing

Methods for rapid identification of anomalous layers in laser powder bed fusion

In situ process monitoring is a key requirement for increased industry acceptance of powder bed Additive Manufacturing. As sensing technologies increase in maturity, attention must also be given to effective data exploration techniques. These data are often high-resolution and multi-modal, with each build consisting of thousands of layers. Here, the authors propose two methods enabling users to rapidly identify layers of interest within a build. Both methods leverage results from deep learning based segmentations of in situ powder bed images. The first method is an unsupervised “reverse layer search” algorithm while the second method uses supervised machine learning.

Processing diagram for powder bed additive manufacturing

This paper presents the developed software for processing parameter simulation and optimization of powder bed additive manufacturing by concentrated energy beams. The simulations are realized by implementation of a normalized processing diagram and analytical model simulating heating of powder layers by a moving linear heat source. Their implementation is demonstrated for electron beam or laser additive manufacturing of industrial alloys. The developed software and the processing diagram provide a useful reference and methodology to support the selection of appropriate processing parameters during the early development stages of concrete powder bed additive manufacturing technology, building production digital twins or development of integrated process management system.

Effect of Powder Characteristics on Relative Density and Porosity Formation During Electron Beam Selective Melting of Al2024 Aluminum Alloy

Abstract Defects, such as pores and cracks, can be found in parts fabricated by powder-bed additive manufacturing techniques. The origin of certain defects, such as some voids, can be linked to initial powder quality, which makes it an important factor in the process. Powders used in additive manufacturing processes are produced by different methods such as gas atomization (GA), plasma atomization (PA), and plasma rotating electrode process (PREP); each gives different powder quality. In this study, two different Al2024 powders, produced by electrode induction GA and PREP techniques, were used to investigate the effect of powder characteristics on defect formation during electron beam melting process (EBM). Powders were first characterized by using Hall flowmeter funnel and scanning electron microscope (SEM); then, the EBM process was carried out, and finally, samples were examined by density measurement using Archimedes method, SEM analysis, and tensile test. PREP powder showed higher levels of sphericity and surface smoothness without attached satellites. Consequently, a higher apparent density and decreased flowing time were achieved in PREP powder. Moreover, gas-induced internal pores were observed in GA particles. The results also revealed the average relative density of 96.7% and 99.4% for the parts built by GA and PREP powders, respectively. SEM micrographs confirmed the results of density measurement of the fabricated parts and showed higher degrees of both spherical and irregular-shaped pores in samples built by GA powder. Additionally, they showed deprived mechanical properties due to the higher porosity contents which can form stress-concentrated areas.