Bed Fusion Additive Manufacturing Process Research Articles

Simulation Study of Hatch Spacing and Layer Thickness Effects on Microstructure in Laser Powder Bed Fusion Additive Manufacturing using a Texture-Aware Solidification Potts Model

Microstructure control in the laser powder bed fusion additive manufacturing processes is a topic of major interest because of the submillimeter length scale at which the manufacturing process occurs. The ability to control the process at the melt pool scale allows for microstructure control that few other manufacturing techniques can match. The majority of work on microstructure control has focused on altering laser parameters to control solidification conditions (Ref (R.R. Dehoff, M.M. Kirka, W.J. Sames, H. Bilheux, A.S. Tremsin, L.E. Lowe, and S.S. Babu, Site Specific Control of Crystallographic Grain Orientation through Electron Beam Additive Manufacturing, Mater. Sci. Technol., 2014, 31(8), p 931–938. R. Shi, S.A. Khairallah, T.T. Roehling, T.W. Heo, J.T. McKeown, and M.J. Matthews, Microstructural Control in Metal Laser Powder Bed Fusion Additive Manufacturing Using Laser Beam Shaping Strategy, Acta Mater., 2020, 184, p 284–305, https://doi.org/10.1016/j.actamat.2019.11.053.)). Other machine parameters, besides the laser parameters, have also been shown to affect the microstructure of AM parts (Ref (N. Nadammal, S. Cabeza, T. Mishurova, T. Thiede, A. Kromm, C. Seyfert, L. Farahbod, C. Haberland, J.A. Schneider, P.D. Portella, and G. Bruno, Effect of Hatch Length on the Development of Microstructure, Texture and Residual Stresses in Selective Laser Melted Superalloy Inconel 718, Mater. Des., 2017, 134, p 139–150, https://doi.org/10.1016/j.matdes.2017.08.049. F. Geiger, K. Kunze, and T. Etter, Tailoring the Texture of IN738LC Processed by Selective Laser Melting (SLM) by Specific Scanning Strategies, Mater. Sci. Eng. A, 2016, 661, p 240–246, https://doi.org/10.1016/j.msea.2016.03.036.)). We propose an investigation of the effects of hatch spacing and layer thickness on microstructure development in laser powder bed fusion additive manufacturing. A Monte Carlo Potts model with textured solidification capabilities is used to study the effects of these parameters on a unidirectional scan strategy. The simulation results reveal substantial changes in grain morphology as well as texture. Additionally, EVP-FFT crystal plasticity simulations were performed to evaluate the effect of the microstructural shifts on mechanical response. The conclusions from this work elucidate the effects of these parameters on part microstructure as predicted by the texture-aware solidification Potts model and inform understanding of how bulk texture is predicted by the simulation approach.

Measurement Uncertainty of Surface Temperature Distributions for Laser Powder Bed Fusion Processes.

This paper describes advances in measuring the characteristic spatial distribution of surface temperature and emissivity during laser-metal interaction under conditions relevant for laser powder bed fusion (LPBF) additive manufacturing processes. Detailed descriptions of the measurement process, results, and approaches to determining uncertainties are provided. Measurement uncertainties have complex dependencies on multiple process parameters, so the methodology is demonstrated on one set of process parameters and one material. Well-established literature values for high-purity nickel solidification temperature and emissivity at the solidification temperature were used to evaluate the predicted uncertainty of the measurements. The standard temperature measurement uncertainty is found to be approximately 0.9% of the absolute temperature (16 AC), and the standard relative emissivity measurement uncertainty is found to be approximately 8% at the solidification point of high-purity nickel, both of which are satisfactory. This paper also outlines several potential sources of test uncertainties, which may require additional experimental evaluation. The largest of these are the metal vapor and ejecta that are produced as process by-products, which can potentially affect the imaging quality, reflectometry results, and thermal signature of the process, while also affecting the process of laser power delivery. Furthermore, the current paper focuses strictly on the uncertainties of the emissivity and temperature measurement approach and therefore does not detail a variety of uncertainties associated with experimental controls that must be evaluated for future generation of reference data.

Application of Deep Transfer Learning and Uncertainty Quantification for Process Identification in Powder Bed Fusion

Abstract Accurate identification and modeling of process maps in additive manufacturing remains a pertinent challenge. To ensure high quality and reliability of the finished product researchers, rely on models that entail the physics of the process as a computer code or conduct laboratory experiments, which are expensive and oftentimes demand significant logistic and overheads. Physics-based computational modeling has shown promise in alleviating the aforementioned challenge, albeit with limitations like physical approximations, model-form uncertainty, and limited experimental data. This calls for modeling methods that can combine limited experimental and simulation data in a computationally efficient manner, in order to achieve the desired properties in the manufactured parts. In this paper, we focus on demonstrating the impact of probabilistic modeling and uncertainty quantification on powder-bed fusion (PBF) additive manufacturing by focusing on the following three milieu: (a) accelerating the parameter development processes associated with laser powder bed fusion additive manufacturing process of metals, (b) quantifying uncertainty and identifying missing physical correlations in the computational model, and (c) transferring learned process maps from a source to a target process. These tasks demonstrate the application of multifidelity modeling, global sensitivity analysis, intelligent design of experiments, and deep transfer learning for a meso-scale meltpool model of the additive manufacturing process.

Algorithm Development for Generation of Powder Particles for Use in Numerical Simulations of Powder Bed Fusion Additive Manufacturing Processes

This article presents an algorithm development methodology for incorporating the effects of powder quality into numerical simulations of powder bed fusion technologies. The framework leverages x-ray microtomography measurements of samples representative of changes in powder quality with powder reuse. Individual particles are labelled and analysed by postprocessing the three-dimensional data. Included in this data is the particle surface normal and point cloud information which can be used to reconstruct the particle using Poisson Surface Reconstruction in Open3D. This reconstruction can then be exported as a Standard Tessellation Language (STL) file that can be incorporated into discrete element method solvers such as YADE or finite element frameworks such as MOOSE. In this sense, libraries of particles can be generated and used in simulations. To demonstrate the applicability of this method, a publicly available NIST dataset is leveraged. In lieu of experimental data, a second method using Computer-Generated Imagery (CGI) software, Blender, is also presented. The methods are able to replicate powder features, such as satellites and surface irregularity, that are functions of both powder manufacturing methods as well as powder reuse cycles. These particle irregularities have important implications on part quality and manufacturing cost.

A Coupled DEM/SPH Computational Model to Simulate Microstructure Evolution in Ti-6Al-4V Laser Powder Bed Fusion Processes

A new multi-stage three-dimensional transient computational model to simulate powder bed fusion (L-PBF) additive manufacturing (AM) processes is presented. The model uses the discrete element method (DEM) for powder flow simulation, an extended smoothed particle hydrodynamics (SPH) for melt pool dynamics and a semi-empirical microstructure evolution strategy to simulate the evolving temperature and microstructure of non-spherical Ti-6Al-4V powder grains undergoing L-PBF. The highly novel use of both DEM and SPH means that varied physics such as collisions between non-spherical powder grains during the coating process and heat transfer, melting, solidification and microstructure evolution during the laser fusion process can be simulated. The new capability is demonstrated by applying a complex representative laser scan pattern to a single-layer Ti-6Al-4V powder bed. It is found that the fast cooling rate primarily leads to a transition between the β and α martensitic phases. A minimal production of the α Widmanstatten phase at the outer edge of the laser is also noted due to an in situ heat treatment effect of the martensitic grains near the laser. This work demonstrates the potential of the coupled DEM/SPH computational model as a realistic tool to investigate the effect of process parameters such as powder morphology, laser scan speed and power characteristics on the Ti-6Al-4V powder bed microstructure.

Effect of the build orientation on the mechanical performance of polymeric parts produced by multi jet fusion and selective laser sintering

As the selective laser sintering (SLS), multi jet fusion (MJF) is a powder bed fusion additive manufacturing (AM) process that emerged in the last few years. The possibility to nest parts into the build volume and the absence of support structures make both technologies attractive for the large series production of polymeric components. However, to exploit these process features, it is essential to understand the part orientation's effect on the final material performance. A comparison between polyamide 12 (PA12) parts printed by SLS and MJF was carried out in this work. A design of experiment (DoE) approach is adopted to characterise the tensile strength of specimen printed in different orientations and rotations with respect to the machine reference system. Tomography has been used to characterise the porosities present in the printed sample. The results show that it is not sufficient to define only the orientation of the principal axes of the part because the material proprieties may also vary according to the part rotation with respect to the build direction. MJF technology offers greater breaking strength, while SLS prevails over other calculated features. According to the specimen orientation and printing technology, the levels of porosities and the pores have different morphology and distribution in the specimen. A tight correlation was pointed out between the pores and their descriptors and the samples' mechanical behaviour.

Phase-field modeling of wetting and balling dynamics in powder bed fusion process

In a powder bed fusion additive manufacturing process, the balling effect has a significant impact on the surface quality of the printing parts. Surface wetting helps the bonding between powder and substrate and the inter-particle fusion, whereas the balling effect forms large spheroidal beads around the laser beam and causes voids, discontinuities, and poor surface roughness during the printing process. To better understand the transient dynamics, a theoretical model with a simplified 2D configuration is developed to investigate the underlying fluid flow and heat transfer, phase transition, and interfacial instability along with the laser heating. We demonstrate that the degree of wetting and fast solidification counter-balance the balling effect, and the Rayleigh–Plateau flow instability plays an important role for cases with relatively low substrate wettability and high scanning rate.

Probabilistic Feasibility Design of a Laser Powder Bed Fusion Process Using Integrated First-Order Reliability and Monte Carlo Methods

Abstract Quality inconsistency due to uncertainty hinders the extensive applications of a laser powder bed fusion (L-PBF) additive manufacturing process. To address this issue, this study proposes a new and efficient probabilistic method for the reliability analysis and design of the L-PBF process. The method determines a feasible region of the design space for given design requirements at specified reliability levels. If a design point falls into the feasible region, the design requirement will be satisfied with a probability higher or equal to the specified reliability. Since the problem involves the inverse reliability analysis that requires calling the direct reliability analysis repeatedly, directly using Monte Carlo simulation (MCS) is computationally intractable, especially for a high reliability requirement. In this work, a new algorithm is developed to combine MCS and the first-order reliability method (FORM). The algorithm finds the initial feasible region quickly by FORM and then updates it with higher accuracy by MCS. The method is applied to several case studies, where the normalized enthalpy criterion is used as a design requirement. The feasible regions of the normalized enthalpy criterion are obtained as contours with respect to the laser power and laser scan speed at different reliability levels, accounting for uncertainty in seven processing and material parameters. The results show that the proposed method dramatically alleviates the computational cost while maintaining high accuracy. This work provides a guidance for the process design with required reliability.

Multi-Resolution SPH Simulation of a Laser Powder Bed Fusion Additive Manufacturing Process

This paper presents an efficient mesoscale simulation of a Laser Powder Bed Fusion (LPBF) process using the Smoothed Particle Hydrodynamics (SPH) method. The efficiency lies in reducing the computational effort via spatial adaptivity, for which a dynamic particle refinement pattern with an optimized neighbor-search algorithm is used. The melt pool dynamics is modeled by resolving the thermal, mechanical, and material fields in a single laser track application. After validating the solver by two benchmark tests where analytical and experimental data are available, we simulate a single-track LPBF process by adopting SPH in multi resolutions. The LPBF simulation results show that the proposed adaptive refinement with and without an optimized neighbor-search approach saves almost 50% and 35% of the SPH calculation time, respectively. This achievement enables several opportunities for parametric studies and running high-resolution models with less computational effort.

Fast additive manufacturing distortion prediction using backward interpolation

Powder Bed Fusion Additive Manufacturing (PBFAM) processes have emerged as important industrial processes that are capable of manufacturing complicated part features, such as hollow designs, lattice structure and other unique design structures. The current state of computing technology requires significant time to predict the part distortion formed during the PBFAM build process. In this paper, a novel Backward Interpolation (BI) model is presented for fast estimation of part distortion based on build process parameters. In the Backward Interpolation approach, we propose the concept of distortion factor that represents the distortion contribution of unit forces on the node to all other nodes that have equal or lower height in the FEM mesh. To start with, the CAD model is meshed in a layer by layer manner and the FEM model is voxelized and sliced for calculating the distortion factor. Next, the as-built distortion before cutoff from the substrate is calculated based on distortion factors and the internal forces generated by the inherent strain of the voxel. Subsequently, the spring back distortion is calculated, and the total part distortion is then finally determined as the summation of part distortion and the spring back distortion. An experimental validation of the methodology was conducted, and the predicted distortion results appeared to agree well with the distortion obtained from the built part. The comparison of distortion obtained from Backward Interpolation and distortion data from published work was further used to validate this algorithm. The computational efficiency of the proposed Backward Interpolation method was evaluated using an example part and demonstrated that the part distortion values were obtained within a few minutes using a desktop computer, confirming the significant decrease in computing time using this approach.

Dependence of mechanical properties on crystallographic orientation in nickel-based superalloy Hastelloy X fabricated by laser powder bed fusion

In the present study, solid solution strengthened Ni-based superalloy Hastelloy X (HX) parts were fabricated using the laser powder bed fusion (LPBF) additive manufacturing process with the intent of developing a strong crystallographic texture. Their tensile properties at room temperature were investigated along the<100>,<110>, and<111>crystallographic orientations. Tensile behavior was found to be highly dependent on the crystallographic orientation and present unique combinations of strength and ductility when compared with other LPBF-HX counterparts. EBSD (Electron backscatter diffraction) analysis after fracture revealed deformation twinning in the<110>and<111>samples, but not in the<100>orientation. It was observed that crystallographic orientation had a great impact on the effective stacking fault energies. Critical stress for deformation twinning was also observed to be crystallographic orientation-dependent. It was close, if not below the yield strength (YS) for<110>and<111>, while it was well above the ultimate tensile strength (UTS) of the<100>orientation. The YS value of<111>(807 ± 28 MPa) was higher than that of<100>(693 ± 8 MPa) and<110>(648 ± 13 MPa). The results suggest that deformation twinning can occur in solid solution strengthened Ni-base superalloys at room temperature, and their formation does not mandatorily require the presence of γ′ precipitates or thermally assisted mechanisms. In contrast to the<100>and<111>orientations, rotation of the lattice after deformation was found for the<110>.

A technical review of the challenges of powder recycling in the laser powder bed fusion additive manufacturing process

Laser powder bed fusion (L-PBF) is one of the most widely used additive manufacturing techniques for fabrication of components with complex geometries for various industrial applications including aerospace, medical and automotive. The unconsumed powder after part manufacturing is often recovered and recycled to improve process efficiency. However, some of the particles in the recycled powder can have different physical and chemical properties from those in the virgin powder owing to their exposure to the complex environment during the manufacturing process. In addition, some contaminants can be introduced in the recycled powder due to poor process control. A number of studies have been published in the past few years revealing the effects of powder recycling on the build properties. The present work aims to highlight the key phenomena during the manufacturing process that caused degradation to the recycled powder. Further to this, some comments, gaps and areas that deserve further detailed studies are also highlighted.

Hatch Pattern Optimization of Powder Bed Fusion Additive Manufacturing Process for Minimizing Flatness error

Although Metal Powder Bed Fusion Additive Manufacturing (PBFAM) process has emerged as an important industrial process, part distortion due to repeated heating and cooling is a major barrier that stands in the way of using this process for mass commercial production. Laser hatch pattern is a critical factor that influences the part distortion and has been widely studied through experimental investigations. In this paper, we describe an approach for hatch pattern optimization to minimize part GD&T errors using Genetic algorithms (GA). A pre-trained Artificial Neural Network (ANN) was adopted to predict the inherent strain of any hatch pattern, while a Backward Interpolation (BI) approach was used to predict the distortion of the sample part based on the inherent strain obtained from ANN. A Genetic Algorithm approach was then used to optimize the hatch angle of each layer to minimize the flatness form error of a flat feature of a sample part. Three types of island strategies were investigated for laying hatch patterns, and the results show that the increased number of scan islands in the hatch pattern results in less distortion and minimization of flatness error. The flatness values of four other benchmark hatch patterns were also investigated and compared with the optimal hatch pattern results. The comparison showed that the flatness of the sample part with the optimized hatch pattern performs better than the benchmark hatch patterns. The overall computational time for hatch pattern optimization was found to be reasonable, considering the large number of distortion simulations performed during the optimization process.

Effective Conductivity of Additive-Manufactured Metals for Microwave Feed Components

This paper characterizes the effective conductivity of lossy metal materials fabricated with additive manufacturing processes at microwave frequencies using a resonant cavity approach. Specifically addressed is the powder bed fusion additive manufacturing process utilizing AlSi10Mg material at Ku-band. The details of the procedure for converting device parameters that characterize the resonant cavity to material properties are given. Trade-offs between the precision of the conductivity and the quality factor of the cavity are discussed relevant to the design of the cavity. A best-fit matching procedure is made between the measured response of the manufactured cavities and the simulated results. The conductivity with statistical deviation for various fabricated cavities from different vendors is reported. Examples of various designs of fabricated prototype waveguide feed components are presented. The predicted and measured performance of each component is compared, validating the process.

Prediction of residual stress and distortion in laser powder bed fusion additive manufacturing process of Inconel 718 alloy

Rapid heating, melting, solidification and cooling cycles generates high residual stress in additively manufactured parts, causes to part distortion. Finite Element Method (FEM) is one of the common and practical ways to predict residual stress and distortion taking place during additive manufacturing. Thus, it is possible to determine appropriate parameters to eliminate such problems. In this study, laser powder bed fusion (LPBF) additive manufacturing (AM) of Inconel 718 alloy is considered for simulation. Case studies on the residual stress and distortion of arch-shaped structure parts were presented through comparing the simulation results in present study and experimental data borrowed from the literature. The influence of laser scanning parameters such as laser power, scanning speed, layer thickness, scanning strategy on residual stress and distortion of the arch-shaped structure was investigated and compared with the borrowed experimental results. Besides, the influence of heat treatment on residual stress and distortion is also simulated and predicted results are presented. This study reveals that the presented FEM based simulation is capable of capturing experimental data reasonably well.

Grain growth prediction in selective electron beam melting of Ti-6Al-4V with a cellular automaton method

An integrated modeling framework coupling the discrete element method for powder spreading, finite volume method for powder bed melting, and an extended cellular automaton method for grain structure evolution during solidification is proposed. In this framework, the initial grain structure of both the substrate and metal powders can be taken into account and used to capture epitaxial and competitive grain growth. The framework is used to provide an in-depth understanding of microstructure development in Ti-6Al-4V during the selective electron beam melting process. The complex process of grain growth during deposition of multiple tracks and multiple layers is modeled through an analysis restarting scheme. The epitaxial growth of grains from pre-existing grains, in particular the grains of partially melted powders, is reproduced. The mechanism of microstructure development within the overlap region of consecutive tracks and layers for various scan strategies is revealed. The simulation results are in qualitative agreement with experimental observation in the literature. The proposed modeling framework is a powerful tool to guide optimal process parameters that lead to designed, site-specific microstructure control and therefore to tailored mechanical properties of parts fabricated by the powder bed fusion additive manufacturing process.

Determining unfused powder threshold for optimal inherent damping with additive manufacturing

The practicality of inherent damping with the Laser Powder Bed Fusion (LPBF) Additive Manufacturing (AM) process is strengthened with the identification of a threshold value for unfused powder volume. This approach provides the ability to design parts with inherent damping that can suppress vibration by 88–95% compared to fully-fused counterparts, and the damping achieved is a product of only 1–4% unfused powder volume. Inherent damping with LPBF has also addressed conventional shortcomings like manufacturing feasibility, high cycle fatigue (HCF) endurance, and a predictive tool that helps optimize damping by configuring unfused powder volumes. Despite the proven capability of the approach, a threshold unfused powder volume for optimizing damping performance and minimizing structural integrity impact has not been identified. The work in this manuscript addresses this gap in the inherent damping with LPBF capability by leveraging damping data from a varied collection of Nickel Alloy 718 and Stainless Steel 316 L specimens and assessing the trend in vibration suppression with respect to unfused powder volume. Results from this study show a trend in the effects of unfused powder volume on inherent damping performance. With the application of regression and probability distribution analyses, a rule-of-thumb comparison between undamped and passively damped systems has allowed for systemic identification of a threshold value for unfused powder volume.

Comparison between Virgin and Recycled 316L SS and AlSi10Mg Powders Used for Laser Powder Bed Fusion Additive Manufacturing

In this study, the comparison of properties between fresh (virgin) and used (recycled) 316L stainless steel (316L SS) and AlSi10Mg powders for the laser powder bed fusion additive manufacturing (L-PBF AM) process has been investigated in detail. Scanning electron microscopy (SEM), electron-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD) techniques are used to determine and evaluate the evolution of morphology, particle size distribution (PSD), circularity, chemical composition, and phase (crystal structure) in the virgin and recycled powders of both materials. The results indicate that both recycled powders increase the average particle sizes and shift the PSD to higher values, compared with their virgin powders. The recycled 316L SS powder particles largely retain their spherical and near-spherical morphologies, whereas more irregularly shaped morphologies are observed for the recycled AlSi10Mg counterpart. The average circularity of recycled 316L SS powder only reduces by ~2%, but decreases ~17% for the recycled AlSi10Mg powder. EDX analysis confirms that both recycled powders retain their alloy-specific chemical compositions, but with increased oxygen content. XRD spectra peak analysis suggests that there are no phase change and no presence of any undesired precipitates in both recycled powders. Based on qualitative comparative analysis between the current results and from various available literature, the reuse of both recycled powders is acceptable up to 30 times, but re-evaluation through physical and chemical characterizations of the powders is advised, if they are to be subjected for further reuse.

A Lagrangian meshfree mesoscale simulation of powder bed fusion additive manufacturing of metals

AbstractWe present a powder‐scale computational framework to predict the microstructure evolution of metals in powder bed fusion additive manufacturing (PBF AM) processes based on the hot optimal transportation meshfree (HOTM) method. The powder bed is modeled as discrete and deformable three‐dimensional bodies by integrating statistic information from experiments, including particle size and shape, and powder packing density. Tractions in Lagrangian framework are developed to model the recoil pressure and surface tension. The laser beam is applied to surfaces of particles and substrate dynamically as a heat flux with user‐specified beam size, power, scanning speed, and path. The linear momentum and energy conservation equations are formulated in the Lagrangian configuration and solved simultaneously in a monolithic way by the HOTM method to predict the deformation, temperature, contact mechanisms, and fluid‐structure interactions in the powder bed. The numerical results are validated against single track experiments. Various powder bed configurations, laser powers, and speed are investigated to understand the influence of dynamic contact and inelastic material behavior on the deformation, heat transfer, and phase transition of the powder bed. The formation of defects in the microstructure of 3D printed metals, including pores, partially, and unmelted particles, is predicted by the proposed computational scheme.

Additively manufactured novel Al-Cu-Sc-Zr alloy: Microstructure and mechanical properties

An in-depth understanding of microstructure and resultant properties is paramount in the design of a novel alloy system, especially for additive manufacturing (AM). The present investigation aims to characterize a prototypical AM Al alloy with great potential for structural applications. An Al-1.5Cu-0.8Sc-0.4Zr alloy designed using integrated computational material engineering was printed using the laser powder bed fusion AM process. This novel alloy shows promising combination of strength and ductility in as-built and peak-aged conditions. This improvement in the tensile properties is attributed to the presence of both coherent L12 Al3Sc/Al3(Sc,Zr) precipitates and Cu-rich regions. The microstructures were studied via extensive microscopy at different length scales using X-ray microscopy, scanning electron microscopy, and transmission electron microscopy. Fractography revealed that the columnar grain boundaries in as-built condition allow easy slip transfer as compared to the equiaxed grains, with the apex of the melt pool acting as the crack nucleation site. However, the peak aged condition resulted in improved strength while marginally sacrificing ductility due to precipitates decorating dislocations, grain boundaries and melt pool boundaries thus acting as obstacles to slip transfer.