Metal Laser Powder Bed Fusion Research Articles

Prediction of spatter-related defects in metal laser powder bed fusion by analytical and machine learning modelling applied to off-axis long-exposure monitoring

Laser powder bed fusion of metals is increasingly used for fabricating complex parts requiring good mechanical properties. Simultaneously, researchers in the field are intensifying the efforts to reduce defects, such as internal porosities, which hinder a wider industrial adoption of this technology, urging process monitoring to a pivotal role in defect identification and mitigation. Therefore, understanding the correlation between in-process monitoring signals and post-process actual defects is fundamental to taking informed decisions and potential corrective actions during the process.This work focuses on developing models to predict spatter-related defects from specific process signatures detected through off-axis long-exposure imaging. Layer-wise images were properly aligned with corresponding cross-sections from tomographic reconstructions to investigate the relationship between spatter-related signatures and actual defects measured by X-ray computed tomography. This relationship was used as a knowledge basis to develop an analytical image-processing approach and a machine learning-based methodology, which were then compared in terms of their correlation performances. The advantages and limitations of both methods are discussed in the paper.Both approaches led to promising results in the prediction of lack-of-fusion defects caused by spatters, with the machine learning approach showing a prediction accuracy in the order of 90% for defects with equivalent diameter above 90µm, while the analytical model needed equivalent diameters larger than 130µm to reach a prediction accuracy in the order of 80%. Furthermore, the machine learning method led to strong results regarding early defect detection, with most of the investigated defects properly predicted by analysing two consecutive layers after the signature detection.

Exploring spatial beam shaping in laser powder bed fusion: High-fidelity simulation and in-situ monitoring

Laser beam shaping is a novel and relatively unexplored method for controlling the melt pool conditions during metal additive manufacturing (MAM) processes, but even so it still holds good promise for achieving site-specific tailored properties. In this work, a comprehensive numerical and experimental campaign is carried out to explore this subject within metal laser powder bed fusion (LPBF). More specifically, a multiphysics numerical model is implemented for simulating the heat and fluid flow conditions during LPBF of Ti6Al4V using arbitrary circular beam shapes with various power distributions spanning from a pure Gaussian beam to a pure ring beam profile. The model is subsequently coupled with cellular automata to describe the beam shape effects on the microstructure evolution. Model validation is carried out in a two-fold manner. First, we compare the predicted melt pool cross-section with the one from ex-situ single track experiments, and we find a deviation of less than 9 % in melt pool dimensions. Secondly, advanced in-situ X-ray monitoring is carried out to unravel the melt pool dynamics and we find that the predicted morphology closely matches the in-situ X-ray results. Moreover, it is shown that at lower laser power, a bulge of liquid metal forms at the center of the melt pool when employing ring profiles, and this is ascribed to the absence of recoil pressure at the center of the ring beam. Furthermore, increasing the laser power seems to destabilize the melt pool regime, as the central bulge transforms into a liquid metal jet that periodically collapses and breaks up into hot spatter. Based on the results, we believe that our multiphysics modelling methodology, opens up new pathways for predicting how laser beam shaping influences porosity, surface roughness as well as microstructure formation in LPBF processes.

Digital twin–driven optimization of laser powder bed fusion processes: a focus on lack-of-fusion defects

PurposeThe purpose of this research is to enhance the Laser Powder Bed Fusion (LPBF) additive manufacturing technique by addressing its susceptibility to defects, specifically lack of fusion. The primary goal is to optimize the LPBF process using a digital twin (DT) approach, integrating physics-based modeling and machine learning to predict the lack of fusion.Design/methodology/approachThis research uses finite element modeling to simulate the physics of LPBF for an AISI 316L stainless steel alloy. Various process parameters are systematically varied to generate a comprehensive data set that captures the relationship between factors such as power and scan speed and the quality of fusion. A novel DT architecture is proposed, combining a classification model (recurrent neural network) with reinforcement learning. This DT model leverages real-time sensor data to predict the lack of fusion and adjusts process parameters through the reinforcement learning system, ensuring the system remains within a controllable zone.FindingsThis study's findings reveal that the proposed DT approach successfully predicts and mitigates the lack of fusion in the LPBF process. By using a combination of physics-based modeling and machine learning, the research establishes an efficient framework for optimizing fusion in metal LPBF processes. The DT's ability to adapt and control parameters in real time, guided by machine learning predictions, provides a promising solution to the challenges associated with lack of fusion, potentially overcoming the traditional and costly trial-and-error experimental approach.Originality/valueOriginality lies in the development of a novel DT architecture that integrates physics-based modeling with machine learning techniques, specifically a recurrent neural network and reinforcement learning.

Review of In Situ Detection and Ex Situ Characterization of Porosity in Laser Powder Bed Fusion Metal Additive Manufacturing

Over the past decade, significant research has focused on detecting abnormalities in metal laser powder bed fusion (L-PBF) additive manufacturing. Effective online monitoring systems are crucial for enhancing process stability, repeatability, and the quality of final components. Therefore, the development of in situ detection mechanisms has become essential for metal L-PBF systems, making efficient closed-loop control strategies to adjust process parameters in real time vital. This paper presents an overview of current in situ monitoring systems used in metal L-PBF, complemented by ex situ characterizations. It discusses in situ techniques employed in L-PBF and evaluates the applicability of commercial systems. The review covers optical, thermal, acoustic, and X-ray in situ methods, along with destructive and non-destructive ex situ methods like optical, Archimedes, and X-ray characterization techniques. Each technique is analyzed based on the sensor used for defect detection and the type or size of defects. Optical in situ monitoring primarily identifies large defects from powder bed abnormalities, while thermal methods detect defects as small as 100 µm and keyholes. Thermal in situ detection techniques are notable for their applicability to commercial devices and efficacy in detecting subsurface defects. Computed tomography scanning excels in locating porosity in 3D space with high accuracy. This study also explores the advantages of multi-sensor in situ techniques, such as combining optical and thermal sensors, and concludes by addressing current research needs and potential applications of multi-sensor systems.

Mechanical response and failure modes of three-dimensional auxetic re-entrant LPBF-manufactured steel truss lattice materials

Abstract Auxetic architected materials present a novel class of damage-tolerant materials with tunable mechanical characteristics and high energy absorption due to their unique ability to laterally contract and densify when subjected to axial compressive loading. The current state of research on negative Poisson's ratio materials mainly focuses on 2D geometries and a few families of 3D geometries with limited experimental comparisons between different architectures and various geometrical features. Furthermore, when manufactured via laser powder bed fusion, the influence of as-built deviations of geometrical and material properties inherently present due to the melt pool solidification process for thin features is relatively unexplored in the case of metal architected materials. The authors aim to study the elastic properties, peak characteristics, and failure modes of steel auxetic truss lattices subjected to axial compression while also addressing the uncertainties inherent to the metal laser powder bed fusion additive manufacturing of architected materials. This work presents an experimental and computational exploration and comparison of two promising three-dimensional auxetic truss lattice families of low relative densities. A comprehensive investigation of metal negative Poisson's ratio mechanical metamaterials is presented, including the selection of the architectures, modeling, laser powder bed fusion additive manufacturing, as-built part characterization, material testing, and mechanical testing under axial compression. The study of such architectures can unlock their potential in making them readily adaptable to a wide variety of engineering applications.

An Interactive Web-Based Platform for Support Generation and Optimisation for Metal Laser Powder Bed Fusion.

Powder bed fusion-laser beam (PBF-LB), a prevalent and rapidly advancing additive manufacturing (AM) technology nowadays, serves the industry by producing thin, complex, and lightweight components for various sectors, including healthcare, automotive, defence, and aerospace. However, this technology encounters challenges related to the construction of critical parts and the high overall process costs. Equally significant is the role of support structures in metal laser powder bed fusion (PBF-LB/M). The absence of supports can lead to defective and collapsed parts, while the incorrect selection of a support type or the addition of unnecessary supports results in increased material usage and additional post-processing efforts. Therefore, there is a pressing need for advanced software capable of generating appropriate support structures and predicting the thermomechanical behaviour of a part under PBF-LB/M printing conditions. Such software would be beneficial for the industry to avoid printing defects caused by high thermal stresses, minimise material usage, reduce printing time, and ensure high-quality prints. In this study, we introduce a web-based support generation and optimisation platform for PBF-LB/M. Through this platform, among other features, users can import three-dimensional (3D) parts and generate block-type support structures with diamond perforations based on the PySLM library, all within a user-friendly web environment. The first release of the platform (v0.6) is fully interactive and accessible online at no cost.

Material dependent influence of ring/spot beam profiles in laser powder bed fusion

In recent years, the topic of beam shaping for improved laser material processing has rapidly grown influencing metal laser powder bed fusion (PBF-LB/M). Given the need to reduce the cost and improve control of the PBF-LB/M process to make it more competitive with traditional manufacturing methods, increasing productivity of PBF-LB/M is critical. When research reports a new beam profile (e.g. ring profile) to improve productivity on a specific material, it is often generalised, and assumed to have the capability to improve productivity in PBF-LB/M across the board. In this work, we use both low-fidelity simulations and experimental work to investigate the difference between Gaussian and ring/spot beam profiles on metals with very different thermal properties (a stainless steel and an aluminium alloy). We show that the two materials have opposite responses to the change in beam profile (both in terms of melt pool dimensions and thermal gradients); further, the most beneficial intensity distribution is dependent on the energy input to the material. This exemplifies yet another way in which the PBF-LB/M process is non-linear and contradicts the idea that a ring/spot laser profile is beneficial for all laser processing technologies. This highlights the need for further research into the non-linear effect of varying intensity distributions on laser processing before the benefits of dynamic beam shaping can be truly realised.

New multi-function building plate for improving metal laser powder bed fusion by enhancing the alignment accuracy of in-process monitoring data, computed tomography measurements, and building volume geometry

AbstractLaser-based powder bed fusion of metals (PBF-LB/M) is an additive manufacturing process enabling the fabrication of parts with highly complex and customizable geometries, enhanced strength-to-weight properties, and minimized material waste. Despite its unique capabilities, PBF-LB/M needs research and innovation efforts to enhance process dynamics and product quality, as well as to broaden its adoption in high-value industrial sectors, such as aerospace and biomedical. In this context, in-process monitoring solutions and post-process part quality evaluations are fundamental to improving the process towards sustainable, first-time-right, and zero-defect production. This paper describes a novel building plate concept for metal laser powder fusion, whose characteristics were specifically designed to enable and improve the performances of in-process monitoring and high-resolution X-ray computed tomography (CT) measurements. In particular, the plate features markers for perspective correction in off-axis optical monitoring and dismountable inserts with machined geometrical elements to be used for the precise alignment between high-resolution CT reconstructions, in-process gathered data, and building volume geometry. The plate capabilities were demonstrated through examples related to in-process monitoring and post-process X-ray CT measurements.

MeltpoolGAN: Melt pool prediction from path-level thermal history

In metal laser powder bed fusion, a laser beam rapidly scans through a thin layer of powder. The laser heats up and liquefies the powder forming a melt pool. The melt pool characteristics affect the material property and physical performance of the part. Physical simulations of melt pool dynamics are computationally expensive and are often limited to a short laser scan. Alternatively, Finite Element (FE) simulations for part-scale thermal history are less computationally intensive but do not capture the detailed melt pool temperature profile and geometry in general. Accurate modeling of the high spatial and temporal thermal gradients inside and near the melt pool is essential to many applications of the thermal history including design and optimization of the laser scan path, material microstructure characterization, and deformation prediction.In this work, we developed MeltpoolGAN, the first conditional Generative Adversarial Network (cGAN) to predict the melt pool image based on the simulated thermal history along the laser scan path. The integration of generative deep learning and thermal history simulation achieves melt pool-level accuracy while significantly reducing the physical and computational complexity. The data pair of thermal history and melt pool images for neural network training and validation are obtained through Contact-Aware Path Level (CAPL) thermal simulation and a co-axial melt pool monitoring system developed by NIST, respectively. The predicted melt pool morphology is validated against experimentally acquired melt pool images through geometric characteristics, including the length and width, of the melt pool.

Dispersoid coarsening and slag formation during melt-based additive manufacturing of MA754

We have assessed the structural evolution and dispersoid coarsening behaviors of the oxide dispersion-strengthened superalloy MA754 during two different melt-based additive manufacturing techniques – metal laser powder bed fusion (PBF-LB/M) and directed energy deposition (DED). The mechanically alloyed MA754 powder posed challenges for both processes due to its irregular flaky morphology and large particle size. Successful consolidation with PBF-LB/M required increasing the layer height, decreasing the scanning speed, and increasing the laser power relative to typical Ni superalloy printing parameters. The resulting materials contained residual porosity and large Y-Al-oxide slag inclusions which formed in situ. The more prolonged thermal excursion during DED resulted in even larger, mm-scale slag inclusions, which spanned several build layers. In both PBF-LB/M and DED, these inclusions grew at the expense of nanoscale dispersoids, depleting the material of this strengthening phase. These observations motivate alternative approaches for preparing dispersion-strengthened powder feedstocks besides mechanical alloying and highlight the deleterious effects of Al microalloying on dispersoid stability and structure.

Creep of IN738LC manufactured with laser powder bed fusion: effect of build orientation and twinning

ABSTRACT The microstructural anisotropy caused by the highly oriented solidification of the metal Laser Powder Bed Fusion (PBF-LB/M) process affects mechanical short- and long-term properties. Component build orientation influences grain morphology and orientation, and thus, mechanical properties. While the creep behaviour of samples manufactured parallel and perpendicular to the build direction are studied intensively, the 45° build orientation remains uncharacterised. In this study, IN738LC creep samples are manufactured via PBF-LB/M in three build orientations (0°, 45° and 90°). While the results of 90° and 0° are as expected, where 90° achieves the longest time to rupture and largest rupture strain, the 45° specimen shows the least fracture time. Differences in microstructure and twinning behaviour are identified as one of the root causes for this unexpected behaviour. This study discusses the correlation between microstructure, twinning and build orientation and their effect on creep behaviour, with special focus on the 45° build orientation.

Micro-Twinning in IN738LC Manufactured with Laser Powder Bed Fusion.

Components manufactured with Metal Laser Powder Bed Fusion (PBF-LB/M) are built in a layerwise fashion. The PBF-LB/M build orientation affects grain morphology and orientation. Depending on the build orientation, microstructures from equiaxed to textured grains can develop. In the case of a textured microstructure, a clear anisotropy of the mechanical properties affecting short- and long-term mechanical properties can be observed, which must be considered in the component design. Within the scope of this study, the IN738LC tensile and creep properties of PBF-LB/M samples manufactured in 0° (perpendicular to build direction), 45° and 90° (parallel to build direction) build orientations were investigated. While the hot tensile results (at 850 °C) are as expected, where the tensile properties of the 45° build orientation lay between those of 0° and 90°, the creep results (performed at 850 °C and 200 MPa) of the 45° build orientation show the least time to rupture. This study discusses the microstructural reasoning behind the peculiar creep behavior of 45° oriented IN738LC samples and correlates the results to heat-treated microstructures and the solidification conditions of the PBF-LB/M process itself.

Numerical investigation of residual stresses in thin-walled additively manufactured structures from selective laser melting

Selective laser melting (SLM), a metal laser powder bed fusion additive manufacturing method, involves several cycles of very high temperature gradient heating and cooling during the solidification of each layer, which can cause the accumulation of detrimental residual stresses in the 3D printed structure. This work uses a thermo-mechanical computational modeling approach to investigate the formation of residual stresses in thin-walled structures and also investigates the effects of varying taper on the evolution of residual stress profiles of the build. Three material grades; namely, Titanium alloy (Ti64), Stainless steel (SS316L) and Inconel (IN718) have been used for this study. The results show that varying taper thickness up to a certain value has a considerable effect on residual stress evolutions in thin-wall structures, however, beyond a certain value of the taper level, the residual stresses are observed to converge. Also, it is observed that the tensile stresses at the edges of the wall are almost equal or exceed the yield stress of the materials. Among the three material grades considered, the magnitude of residual stress was higher in Ti64 and the stresses are dominant in the build direction. The simulation framework is also applied to analyze the effect of residual stresses on the mechanical properties of complex thin-wall structures such as TPMS (Triply Periodic Minimum Surfaces) lattice structure, using Schwarz Primitive (SP) as a case study. It is observed that the residual stresses lower the effective elastic properties of the lattice structures by 6% ∼ 10% for the three material grades but has no effect on the effective plastic behavior of the material.

On the Use of Metal Sinter Powder in Laser Powder Bed Fusion Processing (PBF-LB/M).

Metal Laser Powder Bed Fusion (PBF-LB/M Powder Bed Fusion, Laser-Based/Metal) offers decisive advantages over conventional manufacturing processes. Complex geometries can be produced that cannot, or only to a limited extent, be manufactured with conventional manufacturing processes. One of the main disadvantages of the process are high investment and operating costs. In order to make the PBF-LB/M process accessible to new research areas, the costs need to be reduced. Therefore, this work investigates whether laser beam sources and motion systems in currently established PBF-LB/M systems can be replaced by more cost-effective components. To reduce the operating costs for PBF-LB/M, the studies are carried out based on previous work with water-atomized, process-foreign sinter powder instead of gas-atomized, spherical PBF-LB/M powders. A cost-efficient, low-alloyed powder is selected (Höganäs HP1) and processed on two different PBF-LB/M machines with a restricted process window using process parameter values that current low-cost machines can achieve. The results show that a multimode fiber laser leads to a more stable process and wider melt pools compared to a single mode fiber laser. In addition, a lower sensitivity of the process with respect to modified process parameters is observed for the multimode laser, resulting in a wider range of stable process windows. A Cartesian motion system (gantry) is suitable for use in PBF-LB/M despite lower scan speeds compared to galvanometer scanners. Beam guidance in the XY-plane offers new possibilities for machine and process design that are not possible with usual scanner systems.

Influence of build orientation on the creep behavior of IN738LC manufactured with laser powder bed fusion

While metal Laser Powder Bed Fusion (PBF-LB/M) offers many advantages, such as increased design freedom, it is yet to be accepted as a reliable manufacturing route. Due to the highly oriented solidification of the PBF-LB/M process, the microstructural anisotropy significantly affects mechanical short- and long-term properties. Component build orientation directly influences grain morphology and orientation and thus mechanical properties.In this study, IN738LC creep samples are manufactured in three build orientations (0°, 45° and 90°) using PBF-LB/M. Creep tests are carried out at 750 °C and 850 °C with applied stresses up to 350 MPa. While the results of 90° and 0° agree with the creep results of other Ni-superalloys manufactured with PBF-LB/M, where the 90° specimen achieves the longest time to rupture and largest creep strain, the 45° specimen shows differing creep results compared to other Ni-superalloys with the least time to fracture. This study discusses the correlation between microstructure and build direction and their effect on creep behavior, especially on the 45° specimen.

Production of the cylinder head and crankcase of a small internal combustion engine using metal laser powder bed fusion

This effort investigates the use of metal additive manufacturing, specifically laser powder bed fusion (LPBF) for the automotive and defense industries by demonstrating its feasibility to produce working internal combustion (IC) engine components. Through reverse engineering, model modifications, parameter selection, build layout optimization, and support structure design, the production of a titanium crankcase and aluminum cylinder head for a small IC engine was made possible. Computed tomography (CT) scans were subsequently used to quantify whether defects such as cracks, geometric deviations, and porosity were present or critical. Once viability of the parts was established, machining and other post-possessing were completed to create functional parts. Final X-ray CT and micro-CT results showed all critical features fell within ±0.127 mm of the original equipment manufacturer (OEM) parts. This allowed reassembly of the engine without any issues hindering later successful operation. Furthermore, the LPBF parts had significantly reduced porosity percentages, potentially making them more robust than their cast counterparts.

On the use of X-ray computed tomography for the improvement of metal laser powder bed fusion process monitoring

Laser-powder bed fusion (LPBF) is increasingly used as a successful metal additive manufacturing technology in different industrial sectors, such as biomedical and aerospace, especially for the production of parts with high geometrical complexity. However, LPBF is still affected by repeatability issues and the presence of several defects within the fabricated components. This aspect is therefore a hindrance in the spreading of this prospective technology, which in several cases is still not able to meet the stringent quality requirements imposed by such industries. In order to overcome these issues, X-ray computed tomography (CT) acquires a fundamental role in the understanding of critical aspects and for process development and optimization. Also considering the growing interest regarding the development of LPBF process monitoring systems, which seek to identify and possibly correct defects during fabrication, CT is very much needed for the generation of reference data concerning actual geometry and internal defects. Nevertheless, this implies the need for an accurate comparison between datasets obtained by in-process acquisitions and post-process measurements, with the aim of successfully correlating process events to actual defects. However, to enhance the comparison accuracy, deformations occurring during and after manufacturing need to be considered when performing in- and post-process data registration, given that this aspect is greatly affecting the outcome of correlations. This work studies a sample geometry that is specifically developed for enhancing data registration accuracy, along with the related alignment procedure. The methodology has also the advantage to be applicable to any kind of in-process monitoring data, despite this paper uses optical imaging for the acquisition of long-exposure digital images, which proved to be suited for detecting spatter particles. Post-process datasets were obtained through metrological X-ray computed tomography, which provides detailed information regarding internal defects.

Multi-Response Optimization of Ti6Al4V Support Structures for Laser Powder Bed Fusion Systems

Laser Powder Bed Fusion (LPBF) is one of the most commonly used and rapidly developing metal Additive Manufacturing (AM) technologies for producing optimized geometries, complex features, and lightweight components, in contrast to traditional manufacturing, which limits those characteristics. However, this technology faces difficulties with regard to the construction of overhang structures and warping deformation caused by thermal stresses. Producing overhangs without support structures results in collapsed parts, while adding unnecessary supports increases the material required and post-processing. The purpose of this study was to evaluate the various support and process parameters for metal LPBF, and propose optimized support structures to minimize Support Volume, Support Removal Effort, and Warping Deformation. The optimization approach was based on the Design of Experiments (DOE) methodology and multi-response optimization, by 3D printing and studying overhang geometries from 0° to 45°. For this purpose, EOS Titanium Ti64 Grade 5 powder was used, a Ti6Al4V alloy commonly employed in LPBF. For 0° overhangs, the optimum solution was characterized by an average Tooth Height, large Tooth Top Length, low X, Y Hatching, and high Laser Speed, while for 22.5° and 45° overhangs, it was characterized by large Tooth Height, low Tooth Top Length, high X, Y Hatching, and high Laser Speed.

Fatigue prediction and life assessment method for metal laser powder bed fusion parts

In this paper, an industry-accepted fatigue model based on generalized stress-life (S–N) curves is adapted for metal parts fabricated by laser powder bed fusion (LPBF). Initial defects inherent to the fabrication process, such as part porosity, are related to fatigue life performance. Hereto, additively manufactured test specimens are fatigue tested and used to formulate a function to predict fatigue life based on the size of initial defects. The predictions correlate well with experimental results and provide a quality measure to expel outliers. The method can be used to predict the life expectancy of LPBF parts based on a priori detected defect sizes.

MONITORING FOR CRACKS IN METAL L-PBF USING GAS-BORNE ACOUSTIC EMISSION

Delaminations and cracks are detrimental phenomena that hinder the quality of the final product in metal additive manufacturing. The effective use of other online monitoring systems that can detect these deformations and delaminations during the manufacturing process is currently being developed and implemented in practice. In this paper, gas-borne acoustic emission is used to show that cracks/delaminations that occur during the metal laser powder bed fusion build process can be detected and distinguished from other machine noise. The peaks in the amplitude of the signal emitted in the time domain could be used to indicate the occurrence of cracks during the build process. The frequency characteristics of the signal could also clearly indicate the occurrence of the macro cracks and differentiate between the signals from the cracks and the machine noise.