Bed Fusion Additive Manufacturing Process Research Articles

Digital twins for rapid in-situ qualification of part quality in laser powder bed fusion additive manufacturing

This work concerns the laser powder bed fusion (LPBF) additive manufacturing process. Currently, LPBF parts are inspected post-process using such techniques as X-ray computed tomography, optical and scanning electron microscopy, among others. This empirical build-and-test approach for qualification of part quality is prohibitively expensive and cumbersome. To enable rapid and accurate in-situ qualification of LPBF part quality, in this work, we developed a physics and data-integrated digital twin approach. To demonstrate the approach, Inconel 718 parts of various shapes were manufactured under differing LPBF processing conditions. The process was continuously monitored using in-situ thermal and optical tomography imaging cameras. The part-scale thermal history was predicted using an experimentally validated computational thermal simulation. The simulation-derived thermal history and sensor signatures were used as inputs to a k-nearest neighbor machine learning model. The machine learning model was trained with ground truth porosity and microstructure data obtained from post-process characterization. The approach predicted the onset of porosity, meltpool depth, grain size, and microhardness with an accuracy exceeding 90 % (R2). This work thus takes a critical step towards realizing an in-situ Born Qualified part quality assessment paradigm in LPBF.

Role of gravity magnitude on flowability and powder spreading in the powder bed fusion additive manufacturing process: Towards additive manufacturing in space

Understanding powder spreading under low gravity conditions is essential for optimizing final products using additive manufacturing in space. In this study, we investigated the role of gravity on flowability and spreading mechanisms through combined experimental and discrete element method (DEM) studies. Three powders with different theoretical densities were used to reenact low compressive conditions resembling those in a low-gravity environment. The influence of low compressive conditions on flowability and spreading behavior was examined using the Hall flowmeter, rotating drum, and spreading experiments. In the experimental result, the static flowability was primarily affected by the presence of elongated particles rather than the compressive conditions. The dynamic AoR of TD_4 powder increased compared to that of TD_8 powder, despite the presence of spherical particles with a smooth surface finish. A DEM simulation study was conducted using TD_8 powder to investigate the impact of different gravity levels on dynamic flowability. The DEM studies revealed that the dynamic flowability under rotation was decreased under low gravity owing to the promoted cohesive interactions. The powder spreading experiment was performed using the three powders with different theoretical densities. The in-situ observation with particle image velocimetry analysis revealed that kinetic energy dissipation in the spreading process was accelerated in the TD_8 powder pile, despite its high interparticle friction and cohesive force. The powder spreading simulation was conducted using TD_8 powder to clarify the effect of low gravity on the powder spreading process. In TD_8 powder under 1 G, particle supply was facilitated by a synergistic effect of free-falling and deposited particles. However, increased cohesive interactions under 0.5 G and 0.16 G restricted particle supply via free-falling, consequently reducing the powder bed density by about 2 % and 6.2 %, respectively. These findings prove that the cohesive force predominantly controls dynamic flowability and powder bed quality in the spreading process under low gravity conditions.

A Gaussian Process-Based extended Goldak heat source model for finite element simulation of laser powder bed fusion additive manufacturing process

Laser powder bed fusion (L-PBF) additive manufacturing (AM) is a key enabling technology to manufacture highly complex and integrated metallic structures. In L-PBF AM process, the melting of the metal powders and the layers underneath can be governed by either “conduction mode” or “keyhole mode”, with the keyhole mode reportedly leading to porosity and decreased strength and ductility by many studies. In part scale simulations, finite element (FE) model is often used to study the temperature distribution during printing and to predict the residual stress, where a volumetric heat flux with a Gaussian or a double ellipsoidal (Goldak) distribution is often applied as the laser heat source. However, the above heat source models can only capture the melt pool shape in the conduction mode, and fail to capture the transition to keyhole melting mode when the process parameters change. To overcome this inaccuracy, an extended Goldak heat source model is proposed by introducing a laser penetration term as a function of laser parameters obtained from a Gaussian-Process (GP) model. The model is validated by “2D pad” AlSi10Mg L-PBF experiments under a wide range of laser power, scan speed, and laser focus offset, and the results show the model successfully captures the measured melt pool shape in all conditions.

A novel titanium alloy for load-bearing biomedical implants: Evaluating the antibacterial and biocompatibility of Ti536 produced via electron beam powder bed fusion additive manufacturing process

Additive manufacturing (AM) of Ti-based biomedical implants is a pivotal research topic because of its ability to produce implants with complicated geometries. Despite desirable mechanical properties and biocompatibility of Ti alloys, one major drawback is their lack of inherent antibacterial properties, increasing the risk of postoperative infections. Hence, this research focuses on the Ti536 (Ti5Al3V6Cu) alloy, developed through Electron Beam Powder Bed Fusion (EB-PBF), exploring bio-corrosion, antibacterial features, and cell biocompatibility. The microstructural characterization revealed grain refinement and the formation of Ti2Cu precipitates with different morphologies and sizes in the Ti matrix. Electrochemical tests showed that Cu content minimally influenced the corrosion current density, while it slightly affected the stability, defect density, and chemical composition of the passive film. According to the findings, the Ti536 alloy demonstrated enhanced antibacterial properties without compromising its cell biocompatibility and corrosion behavior, thanks to Ti2Cu precipitates. This can be attributed to both the release of Cu ions and the Ti2Cu precipitates. The current study suggests that the EB-PBF fabricated Ti536 sample is well-suited for use in load-bearing applications within the medical industry. This research also offers an alloy design roadmap for novel biomedical Ti-based alloys with superior biological performance using AM methods.

Effects of Low-Temperature Heat Treatment on Mechanical and Thermophysical Properties of Cu-10Sn Alloys Fabricated by Laser Powder Bed Fusion.

This study investigated the impact of low-temperature heat treatments on the mechanical and thermophysical properties of Cu-10Sn alloys fabricated by a laser powder bed fusion (LPBF) additive manufacturing (AM) process. The microstructure, phase structure, and mechanical and thermal properties of the LPBF Cu-10Sn samples were comparatively investigated under both the as-fabricated (AF) condition and after low-temperature heat treatments at 140, 180, 220, 260, and 300 °C. The results showed that the low-temperature heat treatments did not significantly affect the phase and grain structures of the Cu-10Sn alloys. Both pre- and post-treatment samples displayed consistent grain sizes, with no obvious X-ray diffraction angle shift for the α phase, indicating that atom diffusion of the Sn element is beyond the detection resolution of X-ray diffractometers (XRD). However, the 180 °C heat-treated sample exhibited the highest hardness, while the AF samples had the lowest hardness, which was most likely due to the generation of precipitates according to thermodynamics modeling. Heat-treated samples also displayed higher thermal diffusivity values than their AF counterpart. The AF sample had the longest lifetime of ~0.19 nanoseconds (ns) in the positron annihilation lifetime spectroscopy (PALS) test, indicating the presence of the most atomic-level defects.

Exploring Piezoelectric Actuation towards Its Applications in Laser Powder Bed Fusion Additive Manufacturing.

Piezoelectric materials, which exhibit a charge distribution across the surfaces in reaction to mechanical strain, find significant utility in actuation and sensing applications. Apart from actuation applications like acoustic devices, motors, and vibration damping, an emerging domain for ultrasonic actuators lies in additive manufacturing processes. Ultrasonic waves applied during solidification aim to modulate grain structure and minimize defects. This research focuses on a fixture designed to facilitate and optimize ultrasonic wave propagation through the build plate in laser powder bed fusion additive manufacturing by utilizing a piezoelectric transducer. Three implementations of piezoelectric transducers were evaluated based on their out-of-plane ultrasonic velocity transmissions. It was determined that a thin plate adhered to the surface of the piezoelectric transducer yielded the most favorable outcomes for implementation, achieving 100% transmission of velocity and energy. Preliminary analysis of melt pool morphology and defects in single-track laser scanning experiments demonstrated the impact of ultrasound on solidification, hinting at a novel approach to enhancing the printability of alloys in laser powder bed fusion additive manufacturing processes. The optimal fixture and the explored transducing efficiency could further guide advanced ultrasound testing to enable in situ defect and texture detection during the additive manufacturing processes.

Efficient Simulation of the Laser-Based Powder Bed Fusion Process Demonstrated on Open Lattice Materials Fabrication

Strut-based or open lattice materials are a category of advanced materials used in medical and aerospace applications due to their properties, such as high strength-to-weight ratio and energy absorption capability. The most prominent method for the fabrication of lattice materials is the Laser-based Powder Bed Fusion (L-PBF) additive manufacturing (AM) process, due to its ability to produce parts of complex geometries. The current work presents an efficient meso-scale finite element (FE) modeling methodology of the L-PBF process demonstrated in the fabrication of body-centered cubic (BCC) lattice materials. The modeling efficiency is gained through an adaptive mesh refinement technique, which results in accurate and efficient prediction of the temperature field during the process evolution. To examine the efficiency of the modeling method, the computational time is compared with that of a conventional FE simulation, based on the element and birth technique. The temperature history difference between the two approaches is minor but the adaptive mesh modeling requires only a small portion of the simulation time of the conventional model. In addition, the computational results present a good correlation with the available experimental measurements for various process parameters validating the presented efficient method.

Solidification of Ni-Mn-Ga magnetic shape memory alloy built via laser powder bed fusion on a single crystal substrate

Ni-Mn-Ga-based magnetic shape memory (MSM) alloys have significant potential as fast actuation materials due to their ability to undergo large magnetic-field-induced strains in an external applied magnetic field. This study explored the manufacture of Ni-Mn-Ga via the laser powder bed fusion (PBF-LB/M) additive manufacturing process, aiming to determine the parameter combinations that enhance the development of a crystallographically oriented coarse grain structure. In the first part of the study, the single tracks were melted on pre-heated single-crystalline Ni-Mn-Ga substrates by varying the applied laser power and scanning speed. This experiment revealed the existence of a parameter window where epitaxial solidification of the single-track can be achieved. Additionally, the results demonstrated that preheating prevents cracking of the single-crystal substrate. Subsequent experiments using a thin-walled 3D geometry demonstrated that this epitaxial structure was replicated across multiple layers, with the built samples exhibiting crystallographically oriented oligocrystalline structures following a high-temperature homogenization treatment. PBF-LB/M shows high potential for facilitating the additive manufacturing of oriented coarse grain oligocrystals for the production of microscale actuators.

A comparative study of porosity rate measurement methods and influence of energy density in Inconel 718 produced by laser powder bed fusion additive manufacturing process

A comparative study of porosity rate measurement methods and influence of energy density in Inconel 718 produced by laser powder bed fusion additive manufacturing process

Recovery of residual polyamide (PA12) from polymer powder bed fusion additive manufacturing process through a binder jetting process

PurposeThis study aims to propose the reuse of PA12 (powder) in another AM process, binder jettiinng, which is less sensitive to the chemical and mechanical degradation of the powder after multiple cycles in the laser system.Design/methodology/approachThe experimental process for evaluating the reuse of SLS powders in a subsequent binder jetting process consists of four phases: powder characterization, bonding analysis, mixture testing and mixture characteristics. Analyses were carried out using techniques such as Fourier Transform Infrared Spectroscopy, scanning electron microscopy, thermogravimetric analysis and stress–strain tests for tension and compression. The surface roughness, color, hardness and density of the new mixture were also determined to find physical characteristics. A Taguchi design L8 was used to search for a mixture with the best mechanical strength.FindingsThe results indicated that the integration of waste powder PA12 with calcium sulfate hemihydrate (CSH) generates appropriate particle distribution with rounded particles of PA12 that improve powder flowability. The micropores observed with less than 60 µm, facilitated binder and infiltrant penetration on 3D parts. The 60/40 (CSH-PA12) mixture with epoxy resin postprocessing was found to be the best-bonded mixture in mechanical testing, rugosity and hardness results. The new CSH-PA12 mixture resulted lighter and stronger than the CSH powder commonly used in binder jetting technology.Originality/valueThis study adds value to the polymer powder bed fusion process by using its waste in a circular process. The novel reuse of PA12 waste in an established process was achieved in an accessible and economical manner.

Effect of quenching and tempering treatments on microstructure and mechanical properties of 300M ultra-high strength steel fabricated by laser powder bed fusion

To achieve high-performance 300 M steel parts through the Laser Powder Bed Fusion (LPBF) additive manufacturing process, post-heat treatments are indispensable. Herein, the effects of quenching and tempering treatments on the microstructure and mechanical properties of LPBF-fabricated 300M ultra-high strength steel were investigated, and the relevant strengthening and toughening mechanisms were analyzed. The microstructure of quenched samples primarily consisted of quenched martensite with minor amounts of bainite and some grain boundary allotriomorphic ferrite. The quenched samples presented significantly higher strength than the 300M forgings, primarily attributed to the contributions of solid solution strengthening, grain boundary strengthening and dislocation strengthening. After following tempering treatment, the microstructure of LPBF-fabricated samples mainly consisted of tempered martensite with minor amounts of bainite and residual austenite. Compared to the quenched samples, the tempered samples exhibited a decrease in strength while demonstrating a significant increase in ductility. The samples treated with the optimal heat treatment process (900 °C/1 h/Oil Cooling for quenching + two times of 300 °C/2 h/Air Cooling for tempering) demonstrated a remarkable strength–ductility balance, with a yield strength (YS) of 1834 MPa, an ultimate tensile strength (UTS) of 2099 MPa, and an elongation (EL) of 10.2%, which are all beyond or comparable to those of 300M forgings.

L-PBF AM process failures causal chain: an FMEA-based monitoring approach for process control

ABSTRACT The laser powder bed fusion (L-PBF) additive manufacturing process offers many advantages. However, its industrial integration still needs to be improved due to the certification constraints of the produced parts. Thus, this paper proposes a phenomenological causal chain of process failures to ensure the control of the L-PBF process and further certify the quality of the parts produced. Consequences of unsuitable thermal regimes are analysed using a failure mode and effects analysis (FMEA) approach, allowing a more global understanding of all the causal chain-related data. The proposed approach is based on standard acquisition equipment available on industrial machines and proves relevant for identifying process failures. Experimental validation of the proposed monitoring method is implemented on a use case using dedicated software. Finally, it is shown that the method is relevant in this confrontation and compatible with the time scale of the process for future NC integration and real-time monitoring.

Laser additive manufacturing of TiB2-modified Cu15Ni8Sn/GH3230 heterogeneous materials: Processability, interfacial microstructure and mechanical performance

Cu/Ni heterogeneous materials integrate excellent thermal conductivity and high-temperature mechanical properties, enabling them to be widely used in the aerospace domain. Differences in the thermal and physical properties of the Cu and Ni materials, however, make them difficult to be processed using the laser powder bed fusion (LPBF) additive manufacturing process. This study systematically examines the effects of various LPBF process parameters on microstructure, element diffusion, bonding strength and microhardness at the Cu/Ni interface, as well as investigating the mechanisms of defect formation within Cu/Ni heterogeneous materials. The results indicate that a reasonable control of laser energy input (<100 J/mm3) facilitates the Cu/Ni components through strong interfacial metallurgical bonding without pore defect formation. Compared to single-material Cu alloy, the ultimate tensile strength (UTS) of the horizontally bonded Cu/Ni specimen increased by 55.25 %, without significant reductions in elongation. The vertically bonded Cu/Ni tensile specimen fractured in the middle of the Cu region rather than the interfacial region, indicating superb interfacial bonding strength. Another advantage lies in the enhancement of thermophysical properties, with a 109.5 % increase in thermal conductivity achieved in the LPBF-fabricated Cu/Ni heterogeneous materials compared to the single-material Ni alloy. Quasi-static compression experiments indicated that the Cu/Ni lattice structure could absorb more energy when compressed parallel to the build direction (BD), compared to being perpendicular to the BD. This study provides guidance for the design and manufacture of high-performance Cu/Ni heterogeneous components via LPBF.

Experimental characterisation of the spreading of polymeric powders in powder bed fusion additive manufacturing process at changing temperature conditions

This study investigates the spreadability behaviour of four different polymeric materials, namely Polyamide 6, Polyamide 6 Black, Polypropylene, and Thermoplastic Polyurethane, under different spreading speeds (30 and 3 mm/s) and powder bed temperatures (25, 80, 110 °C) using a purposely developed experimental apparatus. Macroscopic and microscopic images of the powder layer were taken after completing the powder spreading step. A thresholding-based image processing method was utilised to evaluate the fraction of the bed area not covered by particles (NCF), and the standard deviation of pixel intensities in grayscale images (SDG) was calculated to evaluate powder layer quality in macroscopic images. NCF and SDG can provide quantitative evaluation of the quality of the spread layer, NCF in a logarithmic scale ranking and SDG in a linear scale ranking. A wavelet analysis technique was developed on microscopic panorama images obtained with grazing light to characterise the surface roughness of the layer. Results indicate that the spreadability generally worsens much more significantly than powder flow properties at increasing temperatures and, remarkably, that flowability and spreadability are unrelated. As expected, the temperature effect on powder spreading changes for the different powders are mostly governed by the approach to the powder melting temperature. Minor effects on the final layer quality were also observed at changing spreading speed.

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.

A new variant of the inherent strain method for the prediction of distortion in powder bed fusion additive manufacturing processes

A new variant of the inherent strain (IS) method is proposed to predict component distortion in powder bed fusion additive manufacturing (AM) that addresses some of the shortcomings of the previous work by accounting for both the compressive plastic strain formed adjacent to the melt pool and the thermal strain associated with the changing macroscale thermal field in the component during fabrication. A 3D thermomechanical finite element (FE) model using the new approach is presented and applied to predict the distortion of a component fabricated in an electron beam powder bed fusion (EB-PBF) machine. To improve computational efficiency, each computational layer is comprised of six powder layers. A time-averaged volumetric heat input based on beam voltage and current data obtained from the EB-PBF system was calculated and applied to each computational layer, consistent with the process timing. The inherent strains were applied per computational layer as an initial anisotropic contribution to the thermal strain at the time of activation of each computational layer, resulting in the sequential establishment of static equilibrium during component fabrication, which accounts for the variation in the local macroscale thermal field. The thermal field and distortion predicted by the thermomechanical model were verified using experimentally derived data. The model predicts in-plane compressive strains in the order of 10−3. Differences in the inherent strain were found at different locations in the component, consistent with differences in the macroscale thermal field. The proposed method is general and may also be applied to the laser powder bed fusion (L-PBF) process.

Investigating the effect of temperature on powder spreading behaviour in powder bed fusion additive manufacturing process by Discrete Element Method

In this study, a Discrete Element Method (DEM)-based model was developed to simulate the powder spreading process in Powder bed Fusion (PBF) for Polyamide 6 (PA6) powder, which considered the spreading speed (3 mm/s and 30 mm/s) and temperature (25 °C and 110 °C) as parameters affecting the final spreading powder layer quality. The particle horizontal and vertical velocities were analysed in regions near the spreading blade, where at the lower spreading speed, particle velocities are far less compared to the higher spreading speed. The lower particle velocities lead to gently settling down and rearranging particles during spreading on the bed, allowing a uniform powder layer to form. Increasing the spreading speed led to an increase in shear stress and inertia number. At higher temperatures, shear stresses also rise while the inertia number is slightly reduced due to the greater cohesion between particles. The generated powder layer by the DEM model was analysed using the wavelet analysis technique and compared to experiments. The spreadability index of experiments can be estimated with less than 5% error using DEM simulations, though in an approximately consistent manner that captures the experimental trends of spreading speed and temperature. The packing fraction of simulated powder layers was investigated in the spreading direction. The DEM simulations show that packing fraction decreases as temperature or spreading speed are increased, with its variation across the bed increasing for higher spreading speeds. Increasing the spreading speed leads to greater motion and inertia number of particles and, consequently, it intensifies the particle ejection and results in many unfilled areas in the spread powder layer. Increasing temperature leads to an increase in cohesivity between particles, resulting in aggregates forming on the spread powder layer.

Understanding Melt Pool Behavior of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing.

In the laser powder bed fusion additive manufacturing process, the quality of fabrications is intricately tied to the laser-matter interaction, specifically the formation of the melt pool. This study experimentally examined the intricacies of melt pool characteristics and surface topography across diverse laser powers and speeds via single-track laser scanning on a bare plate and powder bed for 316L stainless steel. The results reveal that the presence of a powder layer amplifies melt pool instability and worsens irregularities due to increased laser absorption and the introduction of uneven mass from the powder. To provide a comprehensive understanding of melt pool dynamics, a high-fidelity computational model encompassing fluid dynamics, heat transfer, vaporization, and solidification was developed. It was validated against the measured melt pool dimensions and morphology, effectively predicting conduction and keyholing modes with irregular surface features. Particularly, the model explained the forming mechanisms of a defective morphology, termed swell-undercut, at high power and speed conditions, detailing the roles of recoil pressure and liquid refilling. As an application, multiple-track simulations replicate the surface features on cubic samples under two distinct process conditions, showcasing the potential of the laser-matter interaction model for process optimization.

Prediction of Compressive Behavior of Laser-Powder-Bed Fusion-Processed TPMS Lattices by Regression Analysis

Triply periodic minimal surface (TPMS) structures offer lightweight and high-stiffness solutions to different industrial applications. However, testing of these structures to calculate their mechanical properties is expensive. Therefore, it is important to predict the mechanical properties of these structures effectively. This study focuses on the effectiveness of using regression analysis and equations based on experimental results to predict the mechanical properties of diamond, gyroid, and primitive TPMS structures with different volume fractions and build orientations. Gyroid, diamond, and primitive specimens with three different volume fractions (0.2, 0.3, and 0.4) were manufactured using a laser powder bed fusion (LPBF) additive manufacturing process using three different build orientations (45°, 60°, and 90°) in the present study. Experimental and statistical results revealed that regression analysis and related equations can be used to predict the mass, yield stress, elastic modulus, specific energy absorption, and onset of densification values of TPMS structures with an intermediate volume fraction value and specified build orientation with an error range less than 1.4%, 7.1%, 19.04%, 21.6%, and 13.4%, respectively.

Effect of parameters on quality of IN718 parts using laser additive manufacturing

The objective of this study is to determine the effect of process parameters such as laser power, scanning speed and layer thickness on the mechanical properties, microstructure and fracture mechanism of Inconel 718 using laser powder bed fusion additive manufacturing process. Full factorial design, regression modelling and response surface methodology are used to optimise the process parameters. The highest tensile strength occurs at 350 W laser power, 1300 mm/s scanning speed and 30 µm layer thickness. The optimal parameters for multi-objective optimisation are identical to those used for single-objective optimisation for tensile strength. The difference between the predicted and actual tensile strength is 0.33%. This work shows a successful methodology using IN718 superalloy for various applications in aerospace industry.