Metal Additive Manufacturing Research Articles

Impact of process parameters on mechanical properties and surface characteristics in hybrid metal additive manufacturing of maraging steel

Impact of process parameters on mechanical properties and surface characteristics in hybrid metal additive manufacturing of maraging steel

Human-in-the-loop Multi-objective Bayesian Optimization for Directed Energy Deposition with in-situ monitoring

Directed Energy Deposition (DED) is a free-form metal additive manufacturing process characterized as toolless, flexible, and energy-efficient compared to traditional processes. However, it is a complex system with a highly dynamic nature that presents challenges for modeling and optimization due to its multiphysics and multiscale characteristics. Additionally, multiple factors such as different machine setups and materials require extensive testing through single-track depositions, which can be time and resource-intensive. Single-track experiments are the foundation for establishing optimal initial parameters and comprehensively characterizing bead geometry, ensuring the accuracy and efficiency of computer-aided design and process quality validation. We digitized a DED setup using the Robot Operating System (ROS 2) and employed a thermal camera for real-time monitoring and evaluation to streamline the experimentation process. With the laser power and velocity as inputs, we optimized the dimensions and stability of the melt pool and evaluated different objective functions and approaches using a Response Surface Model (RSM). The three-objective approach achieved better rewards in all iterations and, when implemented in a real setup, allowed to reduce the number of experiments and shorten setup time. Our approach can minimize waste, increase the quality and reliability of DED, and enhance and simplify human-process interaction by leveraging the collaboration between human knowledge and model predictions.

An automated computational framework to construct printability maps for additively manufactured metal alloys

In metal additive manufacturing (AM), processing parameters can affect the probability of macroscopic defect formation (lack-of-fusion, keyholing, balling), which can, in turn, jeopardize the final product’s integrity. A printability map classifies regions in the processing space where an alloy can be printed with or without porosity defects. However, the creation of these printability maps is resource-intensive. Previous efforts to generate printability maps have required single-track experiments on pre-alloyed powder, limiting the utilization of these printability maps for the high-throughput design of printable alloys. We address these challenges in the case of Laser Powder Bed Fusion AM (L-PBF-AM) by introducing a fully computational, predictive approach to create printability maps for arbitrary alloys. Our framework uses physics-based thermal models and a variety of defect formation criteria. We benchmark the predictive ability of the proposed framework against literature data for the following commonly printed alloys: 316 Stainless Steel, Inconel 718, Ti-6Al-4V, AF96, and Ni-5Nb. Furthermore, we deploy the framework on NiTi-based Shape Memory Alloys (SMAs) as a case study. We scrutinize the accuracy of various sets of defect criteria and use these accuracy measurements to create an uncertainty-aware probabilistic framework capable of predicting the printability maps of arbitrary alloys. This framework has the potential to guide alloy designers to potentially easy-to-print alloys, enabling the co-design of high-performing printable alloys.

High Efficiency Producing Technology Applied in Metal Optical Lens by 3D Wax Printing Combined with Investment Casting

3D printing technology can easily and quickly produce small batch models and full-size parts, which has obvious and important benefits in shortening development time. Since metals exhibit excellent mechanical strength and high wear resistance, metal additive manufacturing (MAM) is a popular technology for making metal parts. However, metal powders and 3D-printing machines are costly, which increases the difficulty of achieving mass production through MAM. In this study, the 3D wax printing and investment casting (WPIC) approach was developed to manufacture high-quality metal optical lenses with high efficiency and low cost. The manufactured lenses had a diameter of 38.1 mm, two radii of curvature (15 and 90 mm), and a cooling channel. These lenses were manufactured through 3D printing by using wax patterns produced through investment casting. The manufacturing efficiency and machining accuracy of the lenses produced using the proposed method were compared with those of lenses produced through MAM and investment casting. The results indicated that the total costs of manufacturing an optical lens through MAM and investment casting were nine and eight times greater, respectively than that of manufacturing an optical lens through WPIC. In addition, the surface roughness of metal lenses manufactured through WPIC was 45% lower than that of lenses manufactured through MAM. Finally, the time required to manufacture 50 metal lenses was only 15 days when WPIC was used; the corresponding time was 25 days and 6 months when MAM and investment casting were used, respectively. According to the above-mentioned results, the WPIC process has excellent advantages in product manufacturing cost and developing schedule over MAM and traditional methods of investment casting.

Investigation of support structure configurations for selective laser melting of In718

The Selective Laser Melting (SLM), as a widely used metallic Additive manufacturing (AM) process, relies heavily on support structures. This study investigated the impact of different support structure configurations on the quality of In718 samples fabricated through SLM. On the basis of a comprehensive review of existing support structures configurations from the literature, three typical configurations: block, cone, and lattice, were designed to support cantilever parts for performance comparison. A coupled thermo-structural finite element simulation using ANSYS was performed to evaluate the temperature, deformation, and thermal stress evolution during the printing process of the three supported cantilever structures. The residual stress and deformation of the printed In718 cantilevers with different support structures were measured for validation. The results showed that block support exhibits the best strength and heat dissipation capability, making it the most effective support configuration for the SLM of In718 material. This research provides a fundamental procedure for evaluating the supporting performances among various support structures for the SLM process.

Advancing the understanding of metal additive manufacturing via physical simulation and in situ transmission electron microscopy: a viewpoint

Advancing the understanding of metal additive manufacturing via physical simulation and in situ transmission electron microscopy: a viewpoint

Probing rapid solidification pathways in refractory complex concentrated alloys via multimodal synchrotron X-ray imaging and melt pool-scale simulation

AbstractRefractory complex concentrated alloys (RCCAs) show potential as the next-generation structural materials due to their superior strength in extreme environments. However, RCCAs processed by metal additive manufacturing (AM) typically suffer from process-related challenges surrounding laser material interaction defects and microstructure control. Multimodal in situ techniques (synchrotron X-ray imaging and diffraction and infrared imaging) and melt pool-level simulations were employed to understand rapid solidification pathways in two representative RCCAs: (i) multi-phase BCC + HCP Ti0.4Zr0.4Nb0.1Ta0.1 and (ii) single-phase BCC Ti0.486V0.375Cr0.111Ta0.028. As expected, laser material interaction defects followed similar systematic trends in process parameter space for both alloys. Additionally, both alloys formed a single-phase (BCC) microstructure after rapid solidification processing. However, significant differences in microstructure selection between these alloys were discovered, where Ti0.4Zr0.4Nb0.1Ta0.1 showed a mixture of equiaxed and columnar grains, while Ti0.486V0.375Cr0.111Ta0.028 was dominated by columnar growth. These behaviors were well described by the influence of undercooling effects on columnar-to-equiaxed transition (CET). Distinct microstructure formation in each alloy was verified through CET predictions via analytical melt pool simulations, which showed a ~ 5 × increase degrees in undercooling for Ti0.4Zr0.4Nb0.1Ta0.1 compared to Ti0.486V0.375Cr0.111Ta0.028. Overall, these results show that microstructure control based on modulating the freezing range must be balanced with process considerations which resist defect formation, such as solidification crack formation in RCCAs. Graphical abstract

Microstructural characterisation on reused Ti6Al4V powder in Direct Metal Laser sintering Additive manufacturing

One of the biggest advantages in metal additive manufacturing using laser powder bed fusion is low powder usage compared to traditional manufacturing methods. The process can be made more efficient by enabling metal powder to be reused. Recycling promotes environmental sustainability by minimizing material wastage and decreasing the demand for raw materials, making the metal additive manufacturing process more resource efficient.In this study, Ti6Al4V powder was recycled and reused up to 50 times. In order to understand the effects of reusing powder, the study included a detailed examination of both the powder and the processing method. The microstructure and characteristics of the recycled powder were examined in extensive detail.

Solidification cracking susceptibility of alloy 718 during additive manufacturing and evaluating method

Although hot cracks frequently occur during metal additive manufacturing (AM), there are very few fundamental studies on the cracking behaviour and susceptibility. In this study, a horizontal tensile-type hot cracking test was investigated for evaluating the solidification cracking susceptibility of alloy 718 quantitatively during AM, particularly in laser powder bed fusion. The factors influencing the cracking susceptibility were also examined. The solidification cracking was reproduced by the melting of the AMed specimen with a tensile load under conditions of heat source simulating the AM process. The critical initial tensile stress for solidification crack initiation could apply as an evaluation index for cracking susceptibility. The critical initial stress decreased with increasing the laser power. A similar tendency was observed during the melting of the powders set on tiny groove for simulating AM process. The critical strain rate for solidification cracking (CST) was derived by a thermal elastic–plastic analysis using the critical initial stress measured experimentally. The CST at the laser power of 1125 W was higher than that of 1000 W for no crack condition. Therefore, high CST corresponding to penetration shape with high laser power induce to deteriorate the solidification cracking susceptibility.

Integrated top-down process and voxel-based microstructure modeling for Ti-6Al-4 V in laser wire direct energy deposition process

Laser-wire metal additive manufacturing (AM) is one of the ideal direct energy deposition (DED) processes for creating large-scale parts with a medium level of complexity. However, the DED process involves complex thermal signatures and wide length scales making the fabrication of realistic AM components and part qualification often reliant on experimental trial-and-error optimization. While experimental measurements over the full volume of a part are valuable and necessary, measuring the entire area of a part is significantly laborious and practically infeasible, particularly for large parts in terms of cost and rapid qualification. Therefore, in this work, we developed an effective thermal and microstructure modeling framework based on the Johnson–Mehl-Avrami-Kolmogorov (JMAK) and Koistinen & Marburger (KM) models through a top-down approach that considers plate distortion-affected thermal profiles. A voxel-by-voxel simulation method is used to predict individual phase fractions of Ti-6Al-4 V. The predicted results were validated through detailed metallurgical measurements. A combined voxel-by-voxel approach with a sparse data reconstruction technique produced a near-perfect reconstruction of the original data. This approach anticipates a significant reduction in data points and computation time and resources. Lastly, we conclude with potential extensions of this work to other modeling efforts.

Area-based composition predictions of materials fabricated using simultaneous wire-powder-directed energy deposition

Functionally graded materials are an emergent method for designing components with programmable site-specific material properties. These materials are typically fabricated using metal additive manufacturing tools by simultaneously feeding multiple wire and/or powder feedstocks at various rates to achieve spatial composition change. The wire-powder-directed energy deposition (WP-DED) technique is of particular interest for many functionally graded material applications by balancing the low raw materials cost of wire with the high resolution of powder. However, feeding wire and powder are inherently different processes since all extruded wire enters the melt pool, while much of the blown powder is scattered, which makes determining the composition of the build challenging. In this study, we devise a simple area-based measurement method for estimating the composition of WP-DED structures. WP-DED single beads are printed using 309L stainless steel wire and commercially pure Fe powder at five wire feed rates (0.5, 0.75, 1.00, 1.25, 1.50 mm/mm) and five powder feed rates (2, 4, 6, 8, 10 rpm). Characteristic defects including interface gaps and macrosegregation (lack of mixing) tendencies are examined. High powder feed rates (8, 10 rpm) result in interface gaps at all wire feed rates, but smooth deposition and complete mixing is achieved at low powder feed rates, particularly with lower wire feed rates as well. The area-based composition measurement method is within ±20% of energy dispersive x-ray spectroscopy measurements for all samples, showing its effectiveness as a rapid composition estimate for WP-DED materials development.

Metal additive manufacturing of damage-controlled elements for structural protection of steel members

This paper develops hybrid steel members by integrating additively manufactured, ultra-lightweight, damage-controlled elements (DCEs) into hot-rolled structural steel members. This approach relies on segmenting a structural member into distinct sections; one or two segments are enlarged to be capacity protected; however, anotherend or middle DCE segment is optimized to emulate theconventional member’s strength and stiffness. A small-scale DCE was topologically optimized and then additively manufactured using apowder bed fusion technique through adirect metal laser sintering process of 17-4PH stainless steel andthen was experimentally tested to study the buckling behavior under compression. The experimental testing of the optimized DCE shows acompressive strength of 81,000 times the specimen’s weight with stable post-peak buckling behavior. Numerical simulation confirms experimental results, showing agood correlation in fracture energy. A parametric study on four DCE specimens, scaled up by three, four, five, and six times, was performed and compared to hollow structural sections (HSS) of A500 Gr. C in tensile and compression strengths. The numerical simulation shows a linear relation between the weight ratio and HSS length. Additionally, numerical simulation of conventional member, DCE (scaled by three), and three hybrid members revealed that failure occurred in DCE as intended.

Intensify the hindrance to gas entrapment on the construction of Al 5356 thin-walled structure by tuning the WAAM process parameters

Abstract Compared to other metallic additive manufacturing methods, Wire Arc Additive Manufacturing (WAAM) has a number of advantages, such as less equipment capital required and more material composition flexibility. However, uneven welding and feed rates, as well as inadequate gas flow, can result in flaws such oxidation, gas entrapment, and humping. This study aims to reduce gas entrapment, maximize tensile strength, and reduced elastic modulus of the WAAM Al5356 wall by optimizing gas flow rate (13, 16 and 19 l min−1) in conjunction with welding and feed rates. The study highlighted gas flow rate as the most important component in pore formation and used the Entropy approach in conjunction with the COmplex PRoportional ASsessment (COPRAS) tool to identify ideal settings. The reduction in gas entrapment to 0.02%, as shown in the confirmation studies, resulted in a 33.9% rise in tensile strength and a 64.7% rise in elastic modulus. To verify these ideal parameters, elastic modulus mapping was done on the printed WAAM Al5356 wall. Moreover, the damage processes connected to gas entrapment and humping development were examined using fractography. Consequently, the research determined the ideal conditions to generate a multi-layer structure free of defects, improving its practicality in aerospace and automotive sectors.

Facile production of titanium aluminide intermetallic powder for powder metallurgy and metal additive manufacturing

Facile production of titanium aluminide intermetallic powder for powder metallurgy and metal additive manufacturing

Modelling process monitoring data in laser powder bed fusion: A pragmatic route to additive manufacturing quality assurance

Quality assurance remains a significant challenge for laser powder bed fusion and metal additive manufacturing. Despite system manufacturers offering process monitoring as a possible solution, datasets are large and cumbersome with practical use limited without direct comparative data. Model datasets would enable individual build validation, highlight deviations, and facilitate intelligent build planning whereby challenging features or build strategies could be pre-emptively assessed.Herein a pragmatic approach has been developed to model process monitoring data from a commercial system using a relatively simple algorithm. Using a heuristic method, the algorithm response has been fitted to an experimental dataset to derive governing constants and their relationship to key process parameters. Predictability of constants and model fit has been shown to improve with increasing line energy up to a maximum R2=0.8. Algorithm variable trends, supported by corresponding sensitivity analysis, identified two different behavioural regimes. Under low linear energy density (<0.2J/mm) the cumulative spacetime proximity time-weight variable shows a low sensitivity index, characterised by a flat model response reflected in the experimental data. At higher energies (≥0.2J/mm) algorithm variables become more predictable, reflected in stabilising sensitivity indices, as measurements adopt a form characteristic of the cumulative spacetime proximity function.Effectiveness has been demonstrated through presentation of experimental and model data. Refining the methodology to accommodate noise, geometry, and systematic behaviours are identified as key steps to future development. This feasibility study has laid the groundwork for a generalised predictive tool, capable of realising the quality assurance ambitions promised by laser powder-bed fusion process monitoring.

A review on aluminum alloys produced by wire arc additive manufacturing (WAAM): Applications, benefits, challenges and future trends

Metal additive manufacturing is advancing with increasing momentum and attracting great attention. The Wire Arc Additive Manufacturing (WAAM) process, one of the metal additive manufacturing methods, involves melting a filler wire with an electric arc and depositing metal droplets layer by layer along the planned path. Aluminum alloys produced by the WAAM process have been in high demand in the industry, especially in the last decade. The WAAM process stands out as a suitable method for many industries due to its low investment cost, high deposition rates and the advantages of creating relatively complex parts. Key application areas of aluminum alloys produced using WAAM include aerospace, automotive, marine, and energy sectors, where lightweight structures, corrosion resistance, and high strength are critical. Much research has been done and innovative applications, including hybrid systems, have been developed to prevent defects such as residual stresses, cracks, porosity and delamination. This review article provides a comprehensive overview of the use of the WAAM process in aluminum alloys over the past decade. In the article, firstly, aluminum alloys, the WAAM technique and its types are introduced. In the following section, the methods used to improve mechanical properties and optimize the microstructure are examined in detail. In the next section, the difficulties encountered when using aluminum alloys in WAAM applications are discussed in detail. In the discussion section, current developments are evaluated, and in the last section, suggestions for future studies and inferences obtained from this study are presented. As a result, WAAM-CMT and hybrid systems were found to be effective in reducing defects such as porosity, distortion and residual stress. In addition, post-processing heat treatments and surface treatment methods are also crucial for improving mechanical properties. Finally, more research is needed in the areas of 7xxx series alloys, repair applications and environmental sustainability.

Adaptive Threshold Algorithm for Outlier Elimination in 3D Topography Data of Metal Additive Manufactured Surfaces Obtained from Focus Variation Microscopy

The topography of surfaces produced by metal additive manufacturing is a challenge for optical measurement systems such as focus variation microscopes. These irregularities can lead to artifacts, such as incorrectly measured protrusions or spikes, hampering reliable topographic characterization. In order to eliminate this problem, we introduce a new algorithm based on dual convolving a vertical Sobel operator with cross sections of an image stack parallel to the scanning direction of the so-called depth scan. This has proven beneficial in order to distinguish the focus region from out-of-focus areas where outliers are frequently detected. This paper introduces a method for deriving self-adaptive thresholds from the convolution result and compares the effects of different operators in creating self-adaptive thresholds. Additionally, a simulation model of focus variation microscopy is introduced to validate both the measuring system and the proposed algorithm, thereby enhancing the overall performance of focus variation microscopy. Finally, comparisons of measurement results on rough metal additive manufacturing workpieces with and without self-adaptive thresholds are discussed to demonstrate the algorithm’s effectiveness.The utilization of self-adaptive thresholds demonstrably reduces the uncertainty range in roughness parameter calculations. For example, in the case of an additive manufactured metal sample due to outlier elimination, the Sz roughness value reduces from 543 µm to 413 µm.

Electro-discharge machining using copper-coated additively-manufactured AlSi10Mg electrodes

Customized fabrication of electrodes for electro-discharge machining (EDM) is considered as a useful emerging application of metal additive manufacturing technologies for building complex shaped tools in a short period of time. This approach of producing electrodes not only effectively addresses the design flexibility and complexity issues of the tools but also enables the use of various materials so as to ingrain the desired properties in them. The current study explores the production of laser powder bed fusion (LPBF) AlSi10Mg tools for machining of titanium alloy. Moreover, it explicitly assesses the machining performance of additively manufactured electrodes when the tools are subjected to a thin layer of copper coating. Three types of acidic baths are used for electroless coating of tools. The machining performance of the tools in terms of material removal rate, tool wear rate, surface crack density, surface roughness, white layer thickness, and microhardness of the white layer is compared for different electroless copper coating processes. It is observed that the coated tools significantly enhance material removal rate; however, uncoated LPBF tools exhibit superior surface morphology and surface roughness.

3D Printed Metallic Pillar Nanomechanical Resonators Decorated with TiO2 Nanotubes for Highly Sensitive Environmental Applications

AbstractMicro and nanomechanical devices offer enhanced sensing capabilities for detecting biological and chemical small molecules. However, miniaturization necessitates advanced fabrication processes and complex measurement systems, hindering routine sensor analysis. While alternative methods like 3D printing show promise, challenges such as low device resolution persist due to intrinsic damping of polymer inks. In this study, an array of micrometric pillar resonators is fabricated in Ti6Al4 V alloy using additive manufacturing based on laser powder bed fusion technology. These metallic nanomechanical resonators exhibit a very high quality factor with minimal difference between air and vacuum measurements due to low intrinsic damping. Furthermore, titania nanotubes grown on the pillars via anodic oxidation heighten sensitivity for molecular dye degradation evaluation. Leveraging the weak coupling phenomenon among the pillars in the array, these devices facilitate large‐scale parallelized measurements, here demonstrated with real‐time analysis of dye degradation process. This approach to creating mass sensing devices via metallic additive manufacturing can usher in a new generation of highly performing resonating sensor arrays, offering a cost‐effective and efficient alternative to traditional silicon microfabrication methods.

Lightweight and conformal acousto‐ultrasonic sensing network for multi‐scale structural health monitoring: A review

AbstractStructural health monitoring (SHM) has been increasingly investigated for decades. Different physical principles have been developed for damage identification, such as electronics, mechanics, magnetics, etc., with different coverage (i.e., global, large‐area, and local monitoring) and sensitivity. Mechanical acousto‐ultrasonic‐based methods have formed a big family in SHM technologies. Multiple wave/resonance modes have been utilized for versatile SHM tasks. The permanently integrated sensing networks play a significant role in achieving a cost‐effective and reliable SHM system, with major concerns including weight increase for large‐scale deployment and conformity for complex geometry structures. In this review, typical acousto‐ultrasonic sensors made of different material systems are discussed, along with advantages and limitations. Moreover, advanced network installation methods have been introduced, including surface‐mounting with pre‐integrated networks on substrates and in situ printing, and embedding with composite layup and metal additive manufacturing. Sensor versatility and usage in multi‐scale SHM techniques are then highlighted. Different wave/resonance modes are transmitted and received with corresponding elements and network designs. In conclusion, this systematic review mainly covers a collection of acousto‐ultrasonic sensors, two modalities of network installation, and their employment with various SHM methods, hopefully providing a useful guide to building lightweight and conformal networks with passive or active‐passive sensors, and developing complete and reliable SHM strategies by integrating different damage identification methods on multiple scales.