Metal Powder Bed Fusion Research Articles

Beam shaping to tackle laser powder bed fusion challenges

AbstractAdditive manufacturing (AM), a term synonymous with the future of fabrication, has revolutionized industries by offering unparalleled flexibility in design and production. At the heart of this transformative technology is laser‐based powder bed fusion of metals (PBF‐LB/M), the process with the highest geometrical resolution having the largest market share (86 %, Wohlers) amongst all AM processes. By selectively melting and fusing powder material layer by layer with a laser, PBF‐LB/M enables the creation of complex and high‐strength components, previously unthinkable with traditional subtractive manufacturing methods.

Electrical Smoothing of the Powder Bed Surface in Laser-Based Powder Bed Fusion of Metals

Achieving a homogeneous and uniform powder bed surface as well as a defined, uniform layer thickness is crucial for achieving reproducible component properties that meet requirements when powder bed fusion of metals with a laser beam. The existing recoating processes cause wear of the recoater blade due to protruded, melted obstacles, which affects the powder bed surface quality locally. Impairments to the powder bed surface quality have a negative effect on the resulting component properties such as surface quality and relative density. This can lead either to scrapped components or to additional work steps such as surface reworking. In this work, an electric smoother is presented with which a wear-free and contactless smoothing of the powder bed can be realized. The achievable powder bed surface quality was analyzed using optical profilometry. It was found that the electric smoother can compensate for impairments in the powder bed surface and achieve a reproducible surface quality of the powder bed regardless of the initial extent of the impairments. Consequently, the electric smoother offers a promising opportunity to reduce the scrap rate in PBF-LB/M and to increase component quality.

An approach to estimate the low cycle fatigue probabilistic curves of PBF-LB/M 316L steel from small size datasets using the remora optimization algorithm

The significant dispersion in fatigue properties is a prevalent attribute observed in metals manufactured by the Additive Manufacturing (AM). To ascertain the safety of components subjected to low cycle fatigue (LCF) loadings at a temperature of 550 °C, it is necessary to carry out a fatigue reliability assessment of AM metals. Nevertheless, the number of LCF life tests is limited owing to time-consuming nature of test and high total production cost of AM materials. Such a small size dataset cannot satisfy the criteria of the traditional reliability assessment method. This work aims to develop a novel method to evaluate the LCF reliability of 316L stainless steel manufactured by laser-based powder bed fusion of metals (PBF-LB/M) technology. Firstly, the Weibull model is coupled with the Coffin-Manson-Basquin relationship in order to characterize the dispersion of life data points at various strain levels. Secondly, reliability results from a small size dataset show a maximum relative error in fatigue life of less than 25 %, which is similar to results from a large size dataset and the traditional method using fatigue data from public sources. Among this step, the remora optimization algorithm is firstly applied to calculate the characteristic parameters of newly-proposed method. Thirdly, the LCF reliability of PBF-LB/M 316L based on the small size dataset is evaluated. The N95% is equivalent to 44 % of N50%. Finally, the PBF-LB/M 316L is compared with traditional 316L considering the reliability. The LCF properties of PBF-LB/M 316L is similar to the traditional 316L at 50 % reliability, however it’s slightly worse at 95 % reliability.

Impact of processing gas composition on process stability and properties of PBF-LB/M processed alloy 718

The almost unlimited design freedom of the laser-based powder bed fusion of metals (PBF-LB/M) makes this technology very attractive for industry. However, as a developing technology, it still faces some challenges when it comes to productivity and robustness, to name some. Whereas numerous studies covered the impact of laser-based parameters on material properties and robustness, the effect of the processing gas received limited attention. The objective of this study was to evaluate the effect of processing gas composition, containing helium (He) and hydrogen (H2), compared to conventionally used argon (Ar), during PBF-LB/M processing of virgin alloy 718 powder, on printing behavior and part properties. The four gases studied were Ar, Ar +30%He, Ar +30%He +2%H2, and Ar +70%He. Optical Tomography (OT) was used to monitor process stability, which unveiled a significant decrease in process-by products (spatters) between 51 % and 89 % using He and H2-containing gases. It was also found that the process gas decreased the bulk porosity from an average value of 0.08 % when processed with Ar to 0.04 % when using Ar + 70%He. The oxygen pickup by the spatter particles was reduced from 630 ppm (Ar) to 331 ppm (Ar +70%He). EBSD analysis revealed that there were no evident changes in microstructure with the processing gas. The samples processed also had similar tensile properties with yield and ultimate tensile strength of 1180 MPa and 1395 MPa, respectively. However, there was a slight increase in ductility from 16.5 % to 17.2 %, when processed with pure Ar and Ar + 70%He, respectively. This study shows that utilizing standard Ar processing atmosphere with He addition leads to a more stable process with reduced spatter, porosity and a marginal increase in ductility for Alloy 718.

Additively manufactured 3D micro scarf adhesive joints

AbstractHybrid manufacturing enables to overcome additive manufacturing (AM) constraints regarding the maximum feasible part dimension and/or complexity through part separation and subsequent adhesive joining of AM sub-parts. To ensure structural integrity of the joint at a minimum use of substrate volume, the AM inherent freedom of design can be exploited by realizing 3D micro scarf adhesive joints. The performance of this novel adhesive joint design was assessed by conducting optical measurements and static tensile tests using samples fabricated by laser-based powder bed fusion of metals (PBF-LB/M).

Data-driven prediction of inter-layer process condition variations in laser powder bed fusion

The pressing problem of laser powder bed fusion of metals (PBF-LB/M) is the inability to predict and mitigate undesired process conditions in a build. This study aims to develop an efficient and geometric-agnostic prediction tool for the variations of the average meltpool temperature of each layer given a laser scanning path. The approach is a data-driven model based on defined physics-based features and measurement data from a two-color coaxial photodiode system. Although the coaxial photodiode system cannot measure absolute meltpool temperature, it can measure relative changes in the meltpool temperature if the process is performed in the shallow or no-keyhole regimes, the focus of this study. Once trained, the model can predict meltpool temperature variations before the start of the build process for a part geometry which had not yet been printed. The results show that variations in the layer average meltpool temperature can be predicted with the average coefficient of determination (r2) score of 0.65. Furthermore, the method shows the significance of considering the effect of surrounding parts on the average meltpool temperature profile of an observed part. For part geometries investigated in this study, the model shows the information from at least 40 previous layers is needed to enable sufficient and stabilized prediction performance.

Statistical parameterized physics-based machine learning digital shadow models for laser powder bed fusion process

This paper presents a statistical physics-based machine learning model for predicting defects, such as surface roughness and lack-of-fusion porosity, in the laser powder bed fusion of metals (PBF-LB/M) additive manufacturing process. The statistical physics-based model is calibrated and validated against controlled single-track experiments and used for statistical prediction for multi-layer and multi-track cases for PBF-LB/M defects. A mechanistic reduced-order-based stochastic calibration process is introduced to capture the stochastic nature of the melt pool. The calibrated physics-based digital shadow model is demonstrated for predicting the surface roughness of the National Institute of Standards and Technology (NIST) overhang part X4, with a difference of 9.3% compared to the experimental results. By leveraging data obtained from both the physics-based model and experiments, a machine learning model has been trained for fast predictions (inference time of 0.4 ms) with high accuracy (error bound of 6.7%). This model can predict melt pool geometries under various processing conditions, offering a control strategy for the PBF-LB/M process. Further, the trained machine learning model is showcased to demonstrate a control application of melt pool geometries (width and depth) for specific processing parameters. These developed models (physics-based and machine learning) serve as a digital shadow of the PBF-LB/M process, offering predictive capabilities to build a digital twin model for process control, optimization, and online monitoring.

Influence of argon, helium, and their mixtures on the powder bed fusion of an Al–Cu–Li–Ti alloy using a laser beam: Evaporation, microstructure, and mechanical properties

The role of the inert processing gas during the powder bed fusion of metals using a laser beam (PBF-LB/M) is to prevent oxidation and remove process by-products, such as metal vapor and spatter particles. The present study aims to unveil additional impacts of using argon (Ar), helium (He), and two mixtures thereof as the processing gas on the material properties of a high-strength Al–Cu–Li–Ti alloy fabricated by PBF-LB/M. The part density, microstructure, static tensile properties, and volatile element evaporation were characterized as functions of the processing gas. Decreased porosity levels and increased melt penetration depths were found across a range of processing parameters when increasing the fraction of He in Ar indicating a more stable process and melt pool dynamics. A trend towards increasing yield and ultimate tensile strength was also observed and was attributed to a slightly refined grain size when processing under He-containing gases. The process gas had no significant influence on the evaporation of alloying constituents in the material. Overall, several advantages of using He-containing process gases over pure Ar in PBF-LB/M are demonstrated and discussed.

The effects of submerged laser peening, cavitation peening, and shot peening on the improvement of the torsional fatigue strength of powder bed fused Ti6Al4V produced through laser sintering

This study demonstrates the improvement in the fatigue strength of additive manufacturing (AM) metals such as laser-based powder bed fusion of metals by post-processing. Titanium alloy samples manufactured by powder bed fused (PBF) Ti6Al4V produced through laser sintering (LS), treated by submerged laser peening (SLP), cavitation peening (CP), and shot peening accelerated via a water jet (SPwj), were subjected to torsional fatigue testing and compared with the as-built specimen. At SLP, the samples were treated by laser ablation (LA) and laser cavitation (LC) which was developed following LA. A cavitating jet was used for CP. For comparison, conventional post-processing using SPwj was also performed. To characterize the microstructural modification caused by the three post-processing methods, the cross-section of the treated surface was observed by electron backscatter diffraction. The fatigue strengths at 107 cycles were found to be 217, 361, 313, and 285 MPa for the as-built, SLP, CP, and SPwj specimens, respectively. The primary factors contributing to fatigue strength improvement by post-processing were surface smoothing and the introduction of compressive residual stress. The experimental observations were used to derive correlation formulas to estimate the fatigue life improvement due to post-processing as the function of the surface roughness and surface residual stress.

On machining-induced surface integrity of Inconel 718 fabricated by powder bed fusion

Additive manufacturing (AM) introduces unique grain feature and anisotropy in metals, as well as relatively poor surface quality, so the knowledge about the formation of post-machining-induced surface integrity needs to be extended. This study aims to understand the machining phenomena in orthogonal cutting of Inconel 718 produced via powder bed fusion of metals using a laser beam system (PBF-LB/M), paying particular attention to the cutting energy, chip formation, geometrical defects, and microstructural deformation. Experiments are conducted on both wrought (W 718) and PBF-LB/M (PBF 718) Inconel 718, whereby the cutting speed and the anisotropy of the workpiece in the raw state play an important role. The results indicate that less cutting energy is consumed when cutting PBF 718 in the direction perpendicular to its build direction (BD), followed by cutting in its BD. Denser shearing-induced slip lines and relatively continuous chip morphology are found when cutting PBF 718 in its BD, moreover, the effect of cutting speed on shearing deformation of columnar grains under this condition is analysed. More importantly, this study identifies a significant geometrical defect phenomenon which is unique to PBF 718 and highly depends on the cutting speed and anisotropy of grain feature. A detailed characterisation shows that this behaviour is caused by tearing within the grains in the matrix material and not by the presence of hard inclusions, which has rarely been reported in the literature. The microstructure in the subsurface area exhibits that the density of grain boundaries in the cutting direction plays the key role in plastic deformation, as the machining process mainly causes dragging behaviour in the area below the machined surface. Thus, cutting PBF 718 in the direction perpendicular to its BD shows similar deformation layer to W 718, while cutting PBF 718 in its BD displays much stronger subsurface deformation. The obtained results greatly help to understand the cutting phenomena in post-machining of additively manufactured Ni-based components, especially the integrity for a better functional surface.

In Situ Performance Monitoring of Electrochemical Oxygen and Hydrogen Peroxide Sensors in an Additively Manufactured Modular Microreactor.

Miniaturized and microstructured reactors in process engineering are essential for a more decentralized, flexible, sustainable, and resilient chemical production. Modern, additive manufacturing methods for metals enable complex reactor-geometries, increased functionality, and faster design iterations, a clear advantage over classical subtractive machining and polymer-based approaches. Integrated microsensors allow online, in situ process monitoring to optimize processes like the direct synthesis of hydrogen peroxide. We developed a modular tube-in-tube membrane reactor fabricated from stainless steel via 3D printing by laser powder bed fusion of metals (PBF-LB/M). The reactor concept enables the spatially separated dosage and resaturation of two gaseous reactants across a membrane into a liquid process medium. Uniquely, we integrated platinum-based electrochemical sensors for the online detection of analytes to reveal the dynamics inside the reactor. An advanced chronoamperometric protocol combined the simultaneous concentration measurement of hydrogen peroxide and oxygen with monitoring of the sensor performance and self-calibration in long-term use. We demonstrated the highly linear and sensitive monitoring of hydrogen peroxide and dissolved oxygen entering the liquid phase through the membrane. Our measurements delivered important real-time insights into the dynamics of the concentrations in the reactor, highlighting the power of electrochemical sensors applied in process engineering. We demonstrated the stable continuous measurement over 1 week and estimated the sensor lifetime for months in the acidic process medium. Our approach combines electrochemical sensors for process monitoring with advanced, additively manufactured stainless steel membrane microreactors, supporting the power of sensor-equipped microreactors as contributors to the paradigm change in process engineering and toward a greener chemistry.

Influence of part temperature on in-situ monitoring of powder bed fusion of metals using eddy current testing

AbstractPowder bed fusion of metals (PBF-LB/M) is currently the most widely adopted additive manufacturing technology for the fabrication of metal parts. However, the inconsistent quality of PBF-LB/M-manufactured parts and high costs for part certification are impeding wider industrial adoption. In-situ monitoring technologies are expected to enable process control in order to ensure consistent quality, and to replace some of the post-process inspection steps, therefore, reducing part certification costs. Eddy current testing (ECT) is a standardized nondestructive testing technique, which can be used as an in-situ monitoring technology to measure the part quality during the PBF-LB/M build cycle. However, the process-induced complex temperature fields in PBF-LB/M parts during the build cycle are among the most relevant disturbances due to the temperature dependence of the electrical conductivity. This study investigates the process-induced temperature influence on in-situ monitoring of relative density using ECT. Parts made from AlSi10Mg were manufactured on a PBF-LB/M machine and the build cycle was monitored using ECT and an infrared camera, which was used to extract the part surface temperature right before the ECT measurement. The results demonstrate that the temperature increase of the parts during the build cycle decreases the electrical conductivity independently of the relative part density, which was measured via micro-computed tomography. Therefore, a temperature compensation method was proposed and applied demonstrating that a layer-to-layer difference of 0.15 % relative density can be detected via ECT. Consequently, it has been demonstrated that ECT is an effective in-situ monitoring technology for PBF-LB/M, even in the presence of temperature disparities within parts.

On the fatigue behavior of a tool steel manufactured by powder bed based additive manufacturing—a comparison between electron- and laserbeam processed AISI H13

In recent years, additive manufacturing (AM) techniques have gained increased attention. The most common AM technologies to realize complex parts are powder bed-based fusion processes, especially electron beam powder bed fusion of metals (PBF-EB/M) and laser-based powder bed fusion of metals (PBF-LB/M). Focusing on industrial applications, cyclic loading scenarios and fatigue properties of components produced by such techniques came into focus of research. The present work deals with a comparison between microstructure, hardness, density and fatigue properties of a high-alloy tool steel AISI H13 (1.2344, X40CrMoV5-1) manufactured by PBF-EB/M and PBF-LB/M. The investigated specimens are characterized by a complex phase composition containing ferrite, perlite, bainite and martensite, eventually resulting in different hardness values depending on the used AM technology. Fatigue data for PBF-EB/M AISI H13 are reported for the first time in open literature. It is shown that the fatigue behavior is significantly influenced by the specimen density. Accordingly, parts with a high density are characterized by superior fatigue strength.

Novel strategy for automated quality enhancement of up-facing inclined surfaces by incremental dual laser powder bed fusion

The low quality of up-facing inclined surfaces, combined with a lack of in-situ treatments, is a crucial challenge in Laser Powder Bed Fusion of metals. A recently proposed strategy, so-called Incremental Dual Laser Powder Bed Fusion (IDLPBF), aims to enhance the quality of up-facing inclined surfaces of metal parts directly during building. This is achieved through automatically alternating between laser remelting and building in height steps of 1.5 mm. Laser remelting involves selectively removing powder that is covering the inclined surface through nanosecond pulsed laser-induced shock waves and subsequently remelting the uncovered surface using a continuous wave laser. Treated surfaces are hence composed of laser remolten zones separated by elevated ridges in the overlap region, referred to as stitching zones. These stitching zones can compromise the geometrical accuracy and, consequently, pose a serious risk to fatigue performance. This work focuses on the enhancement of stitching zones and resulting quality of inclined surfaces through IDLPBF of a novel tool steel (M789). The paper covers the effect of various scan strategies for laser remelting on the stitching zone size. By optimizing the orientation of consecutive remelting passes and the position of the remelting fields, the stitching zone width could be reduced from 830 µm to 70 µm. Moreover, the optimized IDLPBF process was successfully applied to a large range of surface inclinations with respect to the horizontal build plate (5°-60°). For the first time, a significant quality improvement for 60° inclined surfaces was achieved, reducing the stress concentration factor by 35 %. The significantly reduced maximum stress concentrations were largely observed at stitching zones, in contrast to multiple high stress concentration sites randomly scattered across as-built surfaces. As a proof of concept, 60 mm high demonstrator parts including typically inaccessible surfaces located in the shadow zone were fully automated manufactured by IDLPBF.

Rapid fatigue evaluation of additive manufactured specimens: Application to stainless steel AISI 316L obtained by laser metal powder bed fusion

Laser powder bed fusion additive manufacturing is a promising technology for manufacturing components in many industrial applications. These components are often subjected to cycling loading and there are concerns about their fatigue performance due to inherent anisotropy, defects, and surface roughness. However, conventional fatigue assessment is time-consuming and expensive. Consequently, several attempts have been made in the last decades to reduce the time and cost associated with these tests by introducing the concept of rapid fatigue testing. Most of these accelerated methods necessitate advanced laboratory equipment and high-precision tests. Recently, a novel approach to rapid fatigue assessment, the stiffness method, has emerged, based on evaluating damage accumulation during the test. This method has been successfully applied and validated across a wide range of wrought metal sheets. In this study, the stiffness method is deployed to evaluate the fatigue performance of additively manufactured stainless steel AISI316L. The results are compared with predictions of the empirical model based on Murakami's approach and the conventional staircase method. A good agreement is obtained between both approaches, showing the stiffness method can estimate the fatigue limit of additive manufacturing specimens in a reliable, fast, and cost-effective way while using a significantly reduced number of tests.

Additive Metallization of Alumina with Copper-Titanium Powder Blends for Power Electronic Applications

Additive manufacturing shows great potential to further increase the performance of power electronic modules through novel packaging concepts. Such an approach is the integrated manufacturing of metal-ceramic substrates by means of laser powder bed fusion of metals (PBF-LB/M). With this layered additive manufacturing process, planar ceramic substrates can be metallized and electrically functionalized for power electronic applications. In this paper Al2O3 ceramic substrates are metallized via PBF-LB/M by selectively melting applied powder layers with software defined geometries. The investigated powders are mixtures of copper and titanium powders with 1 wt.%, 5 wt.% and 10 wt.% titanium in order to enable bonding by creating a titanium-oxide reaction layer at the interface to the ceramic. Shear tests and microstructural investigations show that a subsequent heat treatment increases the adhesion and density of the metallization. By energy dispersive X-ray microscopy (EDX) the partial formation of reaction layers is detected.

Enhancing Part Quality Management Using a Holistic Data Fusion Framework in Metal Powder Bed Fusion Additive Manufacturing

Abstract Metal powder bed fusion additive manufacturing (AM) processes have gained widespread adoption for the ability to produce complex geometries with high performance. However, a multitude of factors still affect the build process, which significantly impacts the adoption rate. This, in turn, leads to great challenges in achieving consistent and reliable part quality. To address this challenge, simulations and measurements have been progressively deployed to provide valuable insights into the quality of individual builds. This paper proposes an AM data fusion framework that combines data sources beyond a single-part, development cycle. Those sources include the aggregation of measurements from multiple builds and the outputs from their related models and simulations. Both can be used to support decision-makings that can improve part quality. The effectiveness of the holistic AM data fusion framework is illustrated through three use case scenarios: one that fuses process data from a single build, one that fusses data from a build and simulation, and one that fuses data from multiple builds. The case studies demonstrate that a data fusion framework can be applied to effectively detect over-melting scan strategies, monitor material melting conditions, and predict down-skin surface defects. Overall, the proposed method provides a practical solution for enhancing part quality management when individual data sources or models have intrinsic limitations.

Pathways toward the Use of Non-Destructive Micromagnetic Analysis for Porosity Assessment and Process Parameter Optimization in Additive Manufacturing of 42CrMo4 (AISI 4140).

Laser-based powder bed fusion of metals (PBF-LB/M) is a widely applied additive manufacturing technique. Thus, PBF-LB/M represents a potential candidate for the processing of quenched and tempered (Q&T) steels such as 42CrMo4 (AISI 4140), as these steels are often considered as the material of choice for complex components, e.g., in the toolmaking industry. However, due to the presence of process-induced defects, achieving a high quality of the resulting parts remains challenging in PBF-LB/M. Therefore, an extensive quality inspection, e.g., using process monitoring systems or downstream by destructive or non-destructive testing (NDT) methods, is essential. Since conventionally used downstream methods, e.g., X-ray computed tomography, are time-consuming and cost-intensive, micromagnetic NDT measurements represent an alternative for ferromagnetic materials such as 42CrMo4. In this context, 42CrMo4 samples were manufactured by PBF-LB/M with different process parameters and analyzed using a widely established micromagnetic measurement system in order to investigate potential relations between micromagnetic properties and porosity. Using multiple regression modeling, relations between the PBF-LB/M process parameters and six selected micromagnetic variables and relations between the process parameters and the porosity were assessed. The results presented reveal first insights into the use of micromagnetic NDT measurements for porosity assessment and process parameter optimization in PBF-LB/M-processed components.

Investigation on surface characteristics of wall structures out of stainless steel 316L manufactured by laser powder bed fusion

Pressure equipment poses a high risk of harming people and the environment in case of failure. They are, therefore, highly regulated by the Pressure Equipment Directive. To enable laser powder bed fusion of metals (PBF-LB/M) for the manufacturing of such components, component appearance and quality need to be characterized and qualified for each specific system. In this study, the surface roughness of wall structures out of austenitic stainless steel (316L) is investigated. Wall structure specimens were produced by four manufacturing systems on different PBF-LB/M machines and with different powder materials. Surface roughness of specimens are compared in the upskin and downskin areas in relation to different slope angles and wall thicknesses. Although different process setups, parameters and powder feedstocks have been used, similarities in the dependency of the surface roughness related to the slope angle and wall thickness can be observed. This work furthermore presents a mechanism-based analytical approach to predict system-specific surface roughness. Particularly, the analytical approach on the influence of slope angle on the surface roughness of the downskin areas has not been covered in publications about PBF-LB/M before. The results of this work enable the prediction of system-specific surface roughness, which is especially important for parts with downskin areas and hidden surfaces without the possibility of additional surface treatment.

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle θs is defined based on melt pool overlap geometry, and the range of θs over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. These results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.