Laser Powder Bed Fusion Machine Research Articles

Properties of a superelastic NiTi shape memory alloy using laser powder bed fusion and adaptive scanning strategies

A NiTi shape memory alloy with the nominal composition Ni50.9Ti49.1 (at%) was processed by laser beam melting/laser powder bed fusion and the process parameters as well as the type of scanning strategy (point-like exposure) were optimized in a first step to obtain delicate lattice structures (strut diameters below 200 µm). In the second step, the lattice structures were analyzed by means of optical and electron microscopy as well as computer tomography to obtain the interrelation between the process parameters, strut diameter and the uniformity of the corresponding struts. The processing, especially the laser power and the type of point-like exposure, has a strong influence on the resulting strut diameter and, therefore, on the haptic stiffness of lattice structures and the mechanical properties (deformability, superelasticity). Unlike other approaches, our findings imply that filigree NiTi lattices with high uniformity can be manufactured on a standard industry laser powder bed fusion machine without modifying its hard- or software configuration.

Influence of sub-cell structure on the mechanical properties of AlSi10Mg manufactured by laser powder bed fusion

AlSi10Mg is one of the most applied alloys for laser powder bed fusion (LPBF) technology, due to its great possibilities for implementing new lightweight concepts such as in automotive industries. For the component design it is necessary to know about the mechanical properties and the mechanical behaviour. The many published strength properties of LPBF processed AlSi10Mg show significant differences up to approximately 225 MPa in ultimate tensile strength (UTS) and 195 MPa in yield strength (YS). To understand these varying properties, a ring trial was carried out manufacturing specimens on 6 LPBF machines with different parameters and build-up strategies. They were studied in the as-built (AB) condition and after heat treatment at 300 °C for 30 min, respectively. For examining the mechanical properties, tensile tests and hardness measurements were carried out. The microstructure was characterized by optical light microscopy (OM), field emission scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD) and electron back-scatter diffraction (EBSD). The identified differences in strength properties were discussed based on the 4 strengthening mechanism known for metallic materials and at the background of material defects. It was found that the size of the typical sub-cell structure of LPBF AlSi10Mg affected substantially the mechanical properties in the AB condition, in which with decreasing sub-cell size strength increased. If heat treatment was applied, the strength properties decreased and did not differ anymore. Since annealing led to coarsened sub-cells, whereas the grains itself did not change in size, the influence of sub-cell structure on strength was further confirmed. In addition, acicular precipitates in the AB condition were observed at specimens from one LPBF machine showing the lowest tensile elongation.

Grain Growth During Keyhole Mode Pulsed Laser Powder Bed Fusion of IN738LC

Minimising hot cracking during laser powder bed fusion (LPBF) of difficult-to-weld alloys is an essential step for LPBF to be applied more widely. In this study, using a pulsed LPBF machine, grain growth during keyhole mode LPBF of IN738LC has been studied. Measurements have shown that the 〈100〉 growth direction can differ significantly from build direction to provide an effect of limiting crack length, depending on the scan direction. Without the change in scan direction after each layer, grains grew in long and lamellar-alternating form of a thin {100} grain and a wide non-{100} grain. Long hot cracks have been found to grow normal to the scan direction, likely relating to the thermal stress developed during solidification of the long melt tracks. The use of a scan strategy of 67° change has been found to disrupt grain growth in lamellar form, and thus has enabled a strong effect on limiting the crack length.

Topology optimisation of an aircraft nose-wheel fork for production in Ti6Al4V by the Aeroswift high-speed laser powder bed fusion machine

Recent levels of structural integrity of components built in the Aeroswift high-speed laser powder bed fusion machine have led to the decision to produce a structural aircraft component through this technology. The Aeroswift machine is capable of building larger Ti6Al4V parts at a more rapid pace than current commercial laser metal powder bed fusion systems. As prototype component, the nose-wheel fork of the AHRLAC aircraft, which was conventionally machined in aluminum alloy 7050, was selected. This paper describes the design, topology optimisation and the manufacturing approach taken in this project. Given the design space, loads, strength requirements and boundary conditions prescribed by the AHRLAC engineers, topology optimisation was performed on the nose-wheel fork to design a lightweight component for production in Ti6Al4V. Different topology optimisation software suites were used, to establish their capabilities and fit-for-purpose features. The optimised design and percentage of weight saving are presented. An assessment based on the experience with the different software suites is offered.

Clamping and substrate plate system for continuous additive build-up and post-processing of metal parts

The manufacturing share of laser powder bed fusion (L-PBF) increases in industrial application, but still many process steps are manually operated. Additionally, it is not possible to achieve tight dimensional tolerances or low surfaces roughness. Hence, a process chain has to be set up to combine additive manufacturing (AM) with further machining technologies. To achieve a continuous workpiece flow as basis for further industrialization of L-PBF, the paper presents a novel substrate system and its application on L-PBF machines and post-processing. The substrate system consists of a zero-point clamping system and a matrix-like interface of contact pins to be substantially connected to the workpiece within the L-PBF process.

Determining the feasible conditions for processing lunar regolith simulant via laser powder bed fusion

Additive manufacturing shows an intrinsic compatibility with building in extra-terrestrial colonization. The use of raw materials found in situ can drastically reduce the complexity of the material supply chain. Laser Powder Bed Fusion (LPBF) is a flexible option for producing components starting from powder feedstock. However, further understanding of the technological capabilities is required to resolve both deposition issues and process applicability in space. This work addresses the processability of lunar highlands regolith simulant NU-LHT-2 M by Laser Powder Bed Fusion on an open prototypal system. The investigation into the influence of process parameters and different base plate materials (carbon steel, self-supporting deposition and refractory clay) was enabled by the in-house developed LPBF machine. The process feasibility window for multi-layer deposition was determined on the refractory clay base plate which ensured stable deposition. Finally, process parameters were studied to produce multi-layer cubical samples which were further analysed for their mechanical properties. Specimens presented compressive yield stress values in excess of 31.4 MPa and micro hardness values in excess of 680 HV, showing the potential of the technology for the deposition of lunar regolith components. The results were also interpreted to assess the technological feasibility of future LPBF machines which may operate in micro gravity conditions.

In Situ Monitoring of Thin-Wall Build Quality in Laser Powder Bed Fusion Using Deep Learning

Abstract The goal of this work is to mitigate flaws in metal parts produced from the laser powder bed fusion (LPBF) additive manufacturing (AM) process. As a step toward this goal, the objective of this work is to predict the build quality of a part as it is being printed via deep learning of in situ layer-wise images acquired using an optical camera instrumented in the LPBF machine. To realize this objective, we designed a set of thin-wall features (fins) from titanium alloy (Ti-6Al-4V) material with a varying length-to-thickness ratio. These thin-wall test parts were printed under three different build orientations, and in situ images of their top surface were acquired during the process. The parts were examined offline using X-ray computed tomography (XCT), and their build quality was quantified in terms of statistical features, such as the thickness and consistency of its edges. Subsequently, a deep learning convolutional neural network (CNN) was trained to predict the XCT-derived statistical quality features using the layer-wise optical images of the thin-wall part as inputs. The statistical correlation between CNN-based predictions and XCT-observed quality measurements exceeds 85 %. This work has two outcomes consequential to the sustainability of AM: (1) it provides practitioners with a guideline for building thin-wall features with minimal defects, and (2) the high correlation between the offline XCT measurements and in situ sensor-based quality metrics substantiates the potential for applying deep learning approaches for the real-time prediction of build flaws in LPBF.

In-process monitoring of porosity in additive manufacturing using optical emission spectroscopy

A key challenge in metal additive manufacturing is the prevalence of defects, such as discontinuities within the part (e.g., porosity). The objective of this work is to monitor porosity in Laser Powder Bed Fusion (L-PBF) additive manufacturing of nickel alloy 718 (popularly called Inconel 718) test parts using in-process optical emission spectroscopy. To realize this objective, cylinder-shaped test parts are built under different processing conditions on a commercial L-PBF machine instrumented with an in-situ multispectral photodetector sensor. Optical emission signatures are captured continuously during the build by the multispectral sensor. Following processing, the porosity-level within each layer of a test part is quantified using X-ray Computed Tomography (CT). The graph Fourier transform coefficients are derived layer-by-layer from signatures acquired from the multispectral photodetector sensor. These graph Fourier transform coefficients are subsequently invoked as input features within various machine learning models to predict the percentage porosity-level in each layer with CT data taken as ground truth. This approach is found to predict the porosity on a layer-by-layer basis with an accuracy of ∼90% (F-score) in a computation time less than 0.5 seconds. In comparison, statistical moments, such as mean, variation, etc., are less accurate (F-score ≈ 80%) and require a computation time exceeding 5 seconds.

Camera signal dependencies within coaxial melt pool monitoring in laser powder bed fusion

PurposeThe purpose of this paper is to analyse the signal dependency of the camera-based coaxial monitoring system QMMeltpool 3D (Concept Laser GmbH, Lichtenfels, Germany) for laser powder bed fusion (LPBF) under the variation of process parameters, position, direction and layer thickness to determine the capability of the system. Because such and similar monitoring systems are designed and presented for quality assurance in series production, it is important to present the dominant signal influences and limitations.Design/methodology/approachHardware of the commercially available coaxial monitoring QMMeltpool 3D is used to investigate the thermal emission of the interaction zone during LPBF. The raw images of the camera are analysed by means of image processing to bypass the software of QMMeltpool 3D and to gain a high level of signal understanding. Laser power, scan speed, laser spot diameter and powder layer thickness were varied for single-melt tracks to determine the influence of a parameter variation on the measured sensory signals. The effects of the scan direction and position were also analysed in detail. The influence of surface roughness on the detected sensory signals was simulated by a machined substrate plate.FindingsParameter variations are confirmed to be detectable. Because of strong directional and positional dependencies of the melt-pool monitoring signal a calibration algorithm is necessary. A decreasing signal is detected for increasing layer thickness. Surface roughness is identified as a dominating factor with major influence on the melt-pool monitoring signal exceeding other process flaws.Research limitations/implicationsThis work was performed with the hardware of a commercially available QMMeltpool 3D system of an LPBF machine M2 of the company Concept Laser GmbH. The results are relevant for all melt-pool monitoring research activities connected to LPBF, as well as for end users and serial production.Originality/valueSurface roughness has not yet been revealed as being one of the most important origins for signal deviations in coaxial melt-pool monitoring. To the best of the authors’ knowledge, the direct comparison of influences because of parameters and environment has not been published to this extent. The detection, evaluation and remelting of surface roughness constitute a plausible workflow for closed-loop control in LPBF.

Electrical resistivity of pure copper processed by medium-powered laser powder bed fusion additive manufacturing for use in electromagnetic applications

Pure copper is an excellent thermal and electrical conductor, however, attempts to process it with additive manufacturing (AM) technologies have seen various levels of success. While electron beam melting (EBM) has successfully processed pure copper to high densities, laser powder bed fusion (LPBF) has had difficulties achieving the same results without the use of very high power lasers. This requirement has hampered the exploration of using LPBF with pure copper as most machines are equipped with lasers that have low to medium laser power densities. In this work, experiments were conducted to process pure copper with a 200 W LPBF machine with a small laser spot diameter resulting in an above average laser power density in order to maximise density and achieve low electrical resistivity. The effects of initial build orientation and post heat treatment were also investigated to explore their influence on electrical resistivity. It was found that despite issues with high porosity, heat treated specimens had a lower electrical resistivity than other common AM materials such as the aluminium alloy AlSi10Mg. By conducting these tests, it was found that despite having approximately double the resistivity of commercially pure copper, the resistivity was sufficiently low enough to demonstrate the potential to use AM to process copper suitable for electrical applications.

Properties of soft magnetic Fe-Co-V alloy produced by laser powder bed fusion

Purpose The purpose of this paper is to report on the developments in manufacturing soft magnetic materials using laser powder bed fusion (L-PBF). Design/methodology/approach Ternary soft magnetic Fe-49Co-2V powder was produced by gas atomization and used in an L-PBF machine to produce samples for material characterization. The L-PBF process parameters were optimized for the material, using a design of experiments approach. The printed samples were exposed to different heat treatment cycles to improve the magnetic properties. The magnetic properties were measured with quasi-static direct current and alternating current measurements at different frequencies and magnetic flux densities. The mechanical properties were characterized with tensile tests. Electrical resistivity of the material was measured. Findings The optimized L-PBF process parameters resulted in very low porosity. The magnetic properties improved greatly after the heat treatments because of changes in microstructure. Based on the quasi-static DC measurement results, one of the heat treatment cycles led to magnetic saturation, permeability and coercivity values comparable to a commercial Fe-Co-V alloy. The other heat treatments resulted in abnormal grain growth and poor magnetic performance. The AC measurement results showed that the magnetic losses were relatively high in the samples owing to formation of eddy currents. Research limitations/implications The influence of L-PBF process parameters on the microstructure was not investigated; hence, understanding the relationship between process parameters, heat treatments and magnetic properties would require more research. Originality/value The relationship between microstructure, chemical composition, heat treatments, resistivity and magnetic/mechanical properties of L-PBF processed Fe-Co-V alloy has not been reported previously.

Exploring the Correlation between Subsurface Residual Stresses and Manufacturing Parameters in Laser Powder Bed Fused Ti-6Al-4V

Subsurface residual stresses (RS) were investigated in Ti-6Al-4V cuboid samples by means of X-ray synchrotron diffraction. The samples were manufactured by laser powder bed fusion (LPBF) applying different processing parameters, not commonly considered in open literature, in order to assess their influence on RS state. While investigating the effect of process parameters used for the calculation of volumetric energy density (such as laser velocity, laser power and hatch distance), we observed that an increase of energy density led to a decrease of RS, although not to the same extent for every parameter variation. Additionally, the effect of support structure, sample roughness and LPBF machine effects potentially coming from Ar flow were studied. We observed no influence of support structure on subsurface RS while the orientation with respect to Ar flow showed to have an impact on RS. We conclude recommending monitoring such parameters to improve part reliability and reproducibility.

Effect of process parameters on the formation of single track in pulsed laser powder bed fusion

There has been increasing interest in Laser Powder Bed Fusion (L-PBF) of metallic materials as a promising manufacturing technology. Although most L-PBF systems utilize laser beams with continuous wave emission (L-PBF(CW)), the possibility of using pulsed lasers (L-PBF(P)) has become available in some industrial L-PBF machines over the past few years. Previous studies suggest that the use of pulsed lasers could enable larger control of heat input and melt pool formation during the process, and could thus enable improvement of spatial resolution and feature sizes in L-PBF. In this study, the experiments were implemented using a pulsed laser in combination with continuous scanning movement instead of the ‘point-and-shoot’ method typically used by industrial L-PBF(P) machines of today. The experiments were executed using a trial L-PBF system (IPG ytterbium fiber laser, wavelength 1075 nm) for gas-atomized stainless steel 316L powder on compositionally similar substrates. Single tracks were melted with three different pulse lengths (50, 100, and 200 µs) by using a constant layer thickness of 50 µm, while varying pulse repetition rate, scanning speed and laser power based on six preset values of volume energy density (VED) of 36-120 J/mm3. In order to allow a comparison to be made, additional samples were manufactured by using the CW emission of the same laser. It was observed that the L-PBF(P) samples yielded narrower tracks in comparison to the samples manufactured using CW emission. In addition, the results of the experiments show that, while maintaining constant VED values, decreasing the pulse length or scanning speed decreased the widths of the tracks and their penetration into the substrate. Consequently, it was noticed that shorter pulse lengths require more overlap between consecutive pulses in order to produce continuous tracks. Pulsed emission shows potential for improving the spatial resolution of the L-PBF process.

Axiomatic Design of Test Artifact for Laser Powder Bed Fusion Machine Capability Assessment

Additive Manufacturing is increasingly growing in importance in the manufacturing environment, allowing to realize very complex product designs. Identifying the real machine capability is becoming fundamental as additive manufacturing technologies are starting to substitute conventional manufacturing processes. This aspect holds particularly true in the case of Laser Powder Bed Fusion technology. In this case, the method to investigate and determine the actual machine capabilities still represents an open point. In this paper, we propose an analysis of a well-known test artifact from an Axiomatic Design standpoint; based on the results and the review of the Customer Needs, we develop an improved design which is able to ensure a robust analysis for a reliable machine performance check.

From Design Complexity to Build Quality in Additive Manufacturing—A Sensor-Based Perspective

Additive manufacturing (AM) provides a greater level of flexibility to build parts with complex structures than the traditional subtractive manufacturing. However, the more complex the engineering design is, the greater challenge is posed on the AM machine. To cope with such complexity, advanced imaging is increasingly invested to increase the information visibility. There is an urgent need to leverage the available imaging data to investigate the interrelationships between design complexity and quality characteristics of AM builds. This article presents a design of experiments on the laser powder bed fusion machine to investigate how design parameters (i.e., recoating orientation, hatching pattern, width, and height) influence edge roughness in thin-wall structures of the final builds. First, we perform the postbuild inspection of final builds and collect large amounts of X-ray computed tomography (XCT) images. Second, we integrate the computer-aided designs with XCT images for image registration and then characterize the edge roughness of each layer in a thin wall of the AM build. Finally, we perform an analysis of variance with respect to design parameters and develop a regression model to predict how build design impacts the edge roughness in each layer of the thin-wall structures. Experimental results show that edge roughness is sensitive to recoating orientations, width, and hatching patterns. This article sheds insights on the optimization of engineering design to improve the quality of AM builds.

Visualization of the shielding gas flow in SLM machines by space-resolved thermal anemometry

PurposeThe purpose of this paper is to introduce an approach in measuring the shielding gas flow within laser powder bed fusion (L-PBF) machines under near-process conditions (regarding oxygen content and shielding gas flow).Design/methodology/approachThe measurements are made sequentially using a hot-wire anemometer. After a short introduction into the measurement technique, the system which places the measurement probe within the machine is described. Finally, the measured shielding gas flow of a commercial L-PBF machine is presented.FindingsAn approach to measure the shielding gas flow within SLM machines has been developed and successfully tested. The use of a thermal anemometer along with an automated probe-placement system enables the space-resolved measurement of the flow speed and its turbulence.Research limitations/implicationsThe used single-normal (SN) hot-wire anemometer does not provide the flow vectors’ orientation. Using a probe with two or three hot-films and an improved placement system will provide more information about the flow and less disturbance to it.Originality/valueA measurement system which allows the measurement of the shielding gas flow within commercial L-PBF machines is presented. This enables the correlation of the shielding gas flow with the resulting parts’ quality.

Process Mapping and In-Process Monitoring of Porosity in Laser Powder Bed Fusion Using Layerwise Optical Imaging

The goal of this work is to understand the effect of process conditions on lack of fusion porosity in parts made using laser powder bed fusion (LPBF) additive manufacturing (AM) process, and subsequently, to detect the onset of process conditions that lead to lack of fusion-related porosity from in-process sensor data. In pursuit of this goal, the objectives of this work are twofold: (1) quantify the count (number), size and location of pores as a function of three LPBF process parameters, namely, the hatch spacing (H), laser velocity (V), and laser power (P); and (2) monitor and identify process conditions that are liable to cause porosity through analysis of in-process layer-by-layer optical images of the build invoking multifractal and spectral graph theoretic features. These objectives are important because porosity has a significant impact on the functional integrity of LPBF parts, such as fatigue life. Furthermore, linking process conditions to defects via sensor signatures is the first step toward in-process quality assurance in LPBF. To achieve the first objective, titanium alloy (Ti–6Al–4V) test cylinders of 10 mm diameter × 25 mm height were built under differing H, V, and P settings on a commercial LPBF machine (EOS M280). The effect of these process parameters on count, size, and location of pores was quantified based on X-ray computed tomography (XCT) images. To achieve the second objective, layerwise optical images of the powder bed were acquired as the parts were being built. Spectral graph theoretic and multifractal features were extracted from the layer-by-layer images for each test part. Subsequently, these features were linked to the process parameters using machine learning approaches. Through these image-based features, process conditions under which the parts were built were identified with the statistical fidelity over 80% (F-score).

Integrated Control of Melt Pool Geometry and Microstructure in Laser Powder Bed Fusion of AlSi10Mg

Solidification microstructure control via melt pool geometry control is investigated in detail for the AlSi10Mg alloy in a laser melting process. Relationships between cell spacing and melting process parameters—beam power and velocity, are investigated. Single beads and multi-layer pad experiments are performed and analyzed for melt pool geometry and microstructure. Information from these experiments is used to achieve location-specific control of cell spacing in a single part using an EOS laser powder bed fusion machine. Along with experiments, thermal modeling is used to map the effect of melting parameters on solidification conditions. Optical microscopy and scanning electron microscopy are used to determine the melt pool dimensions and cell spacing, respectively. Results from the model and experiments show that cell spacing can be varied by controlling the cooling rate of the melt pool via beam power and travel speed for both single bead and multi-layer pad experiments. In addition, the relationship between melt pool area and cooling rate is used to demonstrate integrated melt pool geometry and microstructure control. This is also critical for process qualification using simple observable metrics such as melt pool size. This relationship is then used to demonstrate location-specific control of cell spacing in a single component.

Sensor-Based Build Condition Monitoring in Laser Powder Bed Fusion Additive Manufacturing Process Using a Spectral Graph Theoretic Approach

The goal of this work is to monitor the laser powder bed fusion (LPBF) process using an array of sensors so that a record may be made of those temporal and spatial build locations where there is a high probability of defect formation. In pursuit of this goal, a commercial LPBF machine at the National Institute of Standards and Technology (NIST) was integrated with three types of sensors, namely, a photodetector, high-speed visible camera, and short wave infrared (SWIR) thermal camera with the following objectives: (1) to develop and apply a spectral graph theoretic approach to monitor the LPBF build condition from the data acquired by the three sensors; (2) to compare results from the three different sensors in terms of their statistical fidelity in distinguishing between different build conditions. The first objective will lead to early identification of incipient defects from in-process sensor data. The second objective will ascertain the monitoring fidelity tradeoff involved in replacing an expensive sensor, such as a thermal camera, with a relatively inexpensive, low resolution sensor, e.g., a photodetector. As a first-step toward detection of defects and process irregularities that occur in practical LPBF scenarios, this work focuses on capturing and differentiating the distinctive thermal signatures that manifest in parts with overhang features. Overhang features can significantly decrease the ability of laser heat to diffuse from the heat source. This constrained heat flux may lead to issues such as poor surface finish, distortion, and microstructure inhomogeneity. In this work, experimental sensor data are acquired during LPBF of a simple test part having an overhang angle of 40.5 deg. Extracting and detecting the difference in sensor signatures for such a simple case is the first-step toward in situ defect detection in additive manufacturing (AM). The proposed approach uses the Eigen spectrum of the spectral graph Laplacian matrix as a derived signature from the three different sensors to discriminate the thermal history of overhang features from that of the bulk areas of the part. The statistical accuracy for isolating the thermal patterns belonging to bulk and overhang features in terms of the F-score is as follows: (a) F-score of 95% from the SWIR thermal camera signatures; (b) 83% with the high-speed visible camera; (c) 79% with the photodetector. In comparison, conventional signal analysis techniques—e.g., neural networks, support vector machines, linear discriminant analysis were evaluated with F-score in the range of 40–60%.

In situ measurements of layer roughness during laser powder bed fusion additive manufacturing using low coherence scanning interferometry

Layer-to-layer height measurements of additively manufactured 316L stainless steel using high speed spectral-domain optical coherence tomography (SD-OCT) are presented. Layers are built up using an open architecture laser powder bed fusion machine while height measurements are made in-line along the process laser path following each layer print. Printed cubes, with and without an internal ‘overhang’ channel, were built to investigate the effect of scanning parameters on surface structure. Layer-to-layer scan rotation strategy significantly impacts surface roughness between layers which in turn can influence porosity. Spatter particles, which have been correlated with numerous defect modalities, generate high points in the powder bed and can persist on a melted surface for many layers. Laser power significantly affects overhang morphology, as measured by SD-OCT. Large dross occurs in the high energy density regime, while balling and a capillary-driven coalescence of unstable melt pools perpendicular to the scanning direction occurs in the low energy density regime. High fidelity powder-scale simulations of deep powder layers were used to further elucidate the underlying physics revealed by SD-OCT measurements and high speed imaging, yielding insight to defect formation mechanisms which can lead to improved process parameters.