Lack Of Fusion Defects Research Articles

Lack of fusion-induced cracking effect on tensile and fatigue behaviours of laser powder-bed fusion-processed Ti-6Al-4V implant

In the laser powder-bed fusion (L-PBF) of Ti-6Al-4 V (Ti64) alloy, cracking defects often caused by lack-of-fusion (LoF) defects cannot be avoided. These defects strongly impact the structural stability of Ti64 implants. In this work, the influence of LoF defects on the tensile and fatigue behaviours of Ti64 implants at different energy densities is evaluated. Three primary approaches were used to characterise the LoF defects in the 10 mm gauge volume of near-net-shaped produced hourglass samples: Image-J software, scanning electron microscopy (SEM), and X-ray computed tomography (µ-CT). A low-cycle fatigue (LCF) test at a stress ratio of −1 and an extensive fractography study of the fractured Ti64 samples were used to investigate the LoF porosity-induced cracking and fatigue effect. The tensile properties of Ti64 samples processed by the L-PBF are generally more affected by microstructural changes resulting from variations in energy density than by LoF defects. A fine microstructure enhances tensile strength, while a coarser microstructure favours ductility. This is evident in samples LPBF-AD and LPBF-BD1, which demonstrate finer and coarser microstructures but show the lowest (8.31 %) and highest ductility (17.58 %), respectively. The best and worst fatigue performance samples were LPBF-AD (600 MPa) and LPBF-BD2 (200 MPa), respectively, and LoF defects significantly impactedthis finding. Moreover, it has been demonstrated that cracks originate and propagate faster from the surfacethan the internal sites. As a result, the former demonstratesa negative effect on the fatigue life of L-PBF-processed Ti64 samples under cyclic loading. The sub-surface morphologies and pore formation with different energy densities are rationalised by high-fidelity thermal-fluid dynamics simulations.

Effects of defects on the high-temperature performance of selective laser melting K418 superalloys: An in-situ 3D X-ray analysis

Defects are inevitable in selective laser melting process, significantly impacting the mechanical properties of materials and reducing their service life. In this study, the effects of various defects and their distribution on the high-temperature mechanical performance of the selective laser melted K418 superalloys were investigated via an in-situ 3D X-ray analysis and finite element method. The results showed that the selective laser melting process can significantly enhance the strength of the K418 sample, while degrading the fracture elongation. The sphericity and location of defects are the two key parameters influencing the mechanical performance. The defects with low sphericity at the sub-surface resulted in elevated local stress and strain, accounting for the significant degradation in fracture elongation. Locally increased stress and accumulated strain around lack of fusion defects at the sub-surface contribute to the initiation and propagation of crack. This study provides inspiration for understanding the correlation between the defects and mechanical properties.

Fatigue Crack Segmentation and Characterization of Additively Manufactured Ti‐6Al‐4V Using X‐Ray Computed Tomography

ABSTRACTX‐ray computed tomography (XCT) is extremely useful for the non‐destructive analysis of additively manufactured (AM) components. AM components often show manufacturing defects such as lack‐of‐fusion (LoF), which are detrimental to the fatigue life of components. To better understand how cracks initiate and propagate from internal defects, we fabricated Ti‐6Al‐4V samples with an internal cavity using electron beam powder bed fusion. The samples were tested in high‐cycle and very high‐cycle fatigue regimes. XCT was used to locate crack initiation sites and to determine characteristic properties of cracks and defects with the aid of deep learning segmentation. LoF defects exposed to the outer surface of the samples after machining were found to be as detrimental to fatigue life as the internal artificial defects. This work can benefit industries that utilize the AM of high‐strength, lightweight alloys, in the design and manufacturing of components to improve part reliability and fatigue life.

Enabling Invar to Ti6Al4V transitions through copper in functionally graded laser powder bed fused components

This study examines the microstructural evolution, elemental distribution, phase composition, and hardness variations in multi-material samples fabricated using Laser Powder Bed Fusion (LPBF) with Invar and Ti6Al4V with compositional gradients mediated by copper. A range of compositional transitions from Invar to Ti6Al4V with different copper fractions are reported. Defects such as gas and keyhole pores were detected in well-deep keyhole mode areas, while lack of fusion defects were observed in samples with pure Cu interlayers due to poor wettability and processing parameter variations. Crack formation between interlayer gradient zones and Invar regions was linked to FeNi and CuNi intermetallic phases. Intermetallic compounds (e.g., FeNi, CuNi, TiFe, TiNi) significantly influenced the microstructure and mechanical performance. Vickers hardness testing shows varying hardness across different builds, with the highest hardness being observed in the gradient zone enabled by pure copper (approximately 620 HV). This study also underscores the need for tailored component design linking build processing parameters and compositional transitions in multi-material LPBF to achieve desired properties and component structural behaviour.

Very high cycle fatigue characteristics of laser beam powder bed fused AlSi10Mg: A systematic evaluation of part geometry

This study explores the influence of geometry and part size on defect distribution, melt pool size, and mechanical characteristics in laser beam powder bed fused (LB-PBF) AlSi10Mg. Five distinct geometries—hourglass, small rod, small block, large block, and large rod—were fabricated under identical process parameters. Fully reversed ultrasonic fatigue testing, operating at a frequency of 20 kHz, was conducted to assess the very high cycle fatigue properties. The findings indicated that part geometry had a major impact on the fatigue properties of the material in the very high cycle fatigue regime. Specimens machined from large rods and large blocks had the lowest porosity and highest fatigue resistance. Microstructural analysis indicated that hourglass, small rod, and small block specimens had shallower melt pools and overlap depths compared to other geometries. This observation suggests a higher cooling rate in specimens with smaller cross-sectional areas, leading to the increased presence of entrapped gas pores and a lack of fusion defects. Understanding the relationship between part geometry and fatigue properties in LB-PBF components offers insights for optimizing design and manufacturing processes in additive manufacturing applications.

Investigations of particle-process-part quality relationships in electron beam melting

Electron beam melting is a powder bed fusion process capable of manufacturing parts from a variety of high-temperature alloys. Given that the process relies on feedstock recycling for process economics, understanding process-part quality relationships is critical. This work investigates process-part quality relationships in terms of the internal and external defects and component microstructure relative to a feedstock subjected to 33 build cycles without replacement. To accomplish this, a volume of fluid mesoscale model consisting of three different powder distributions were considered: (1) Monomodal; (2) As-measured; and (3) Irregular. Particle morphology was characterized using shape factors examined via optical microscopy. To approximate the particle shapes in three-dimensions, a method is presented that utilizes a binarized domain to define low frequency, macroscale particle “base” shapes implicitly and is thus not restricted to starlike particles. The discrete element method was also used to investigate velocity distributions and packing densities of the as-measured and irregular particles with respect to deviations in the nominal layer thickness of 50 μm. In general, beam power and scan speed were found to have an appreciable effect on microstructure formation and surface roughness. Finally, correlations were found between specific classifications of irregular particles and lack of fusion defect formation.Graphical abstractOverview of the discrete element method simulation domain for the electron beam melting powder bed fusion process

Unveiling the layer-wise dynamics of defect evolution in laser powder bed fusion: Insights for in-situ monitoring and control

Lack of fusion (LOF) defects can significantly affect the mechanical properties of components manufactured by laser powder bed fusion (LPBF). The layer-wise evolution of LOF defects is complex and not yet thoroughly understood. This work explores the spatiotemporal variations of LOF defects under various conditions using in-situ monitoring, ex-situ surface topography and μ-CT porosity characterization, and high-fidelity multi-physics numerical simulation. The results show that LOF defects could exhibit typical self-healing characteristics for over five printing layers. The specific self-healing behaviors depend on the initial sizes of the defects and the LPBF process conditions. The evolution of LOF defects can be detected by in-situ monitoring using light intensity. However, the in-situ monitoring may miss detecting LOF defects buried below the healed layers, which were alternatively observed via μ-CT. For the defective area with a depth of 150 μm, the relative density increased from 61.7 % to 95.7 % for the first to the fifth printing layer. The optimization of process parameters demonstrated that the application of a 45° scanning angle could significantly enhance surface flatness and repair internal pores to a minimum of 36.0 μm. The findings highlight the ability of in-situ monitoring in detecting LOF defects and the potential of the controlled printing process to accelerate defect repair. These outcomes offer valuable insights for the industrial applications of in-situ monitoring and control during LPBF.

The kinetics of pitting corrosion in a defect-contained Hastelloy X alloy fabricated by laser powder bed fusion

The kinetics of pitting corrosion for Hastelloy X alloys fabricated by laser powder bed fusion (LPBF) were investigated in chloride-containing solutions and critical pitting temperature (CPT) was clarified via electrochemical tests and long-term quasi-in-situ monitoring. A decrease in CPT was verified for LPBF Hastelloy X alloys with an increased defect density in 1 M NaCl solution. Lack of fusion (LOF) defects were more susceptible to metastable pitting nucleation than gas pores, and the corrosion pits nucleated at the LOF defects grow in both pit volume and surface area, leading to a rapid corrosion propagation channel formed along the LOF structure.

A modified SWT model for very high cycle fatigue life prediction of L-PBF Ti-6Al-4V alloy based on Single Defect: Effect of building orientation

The ultrasonic fatigue tests on laser-powder bed fused (L-PBF) Ti-6Al-4V specimens manufactured at 0°, 45°, and 90° building orientations were conducted. It is found that the very high cycle fatigue (VHCF) lives decrease with the building orientation from 0°, 45°, to 90°. All the fatigue cracks initiate from internal pores or Lack of Fusion defects. Mode Ι cracks grow perpendicular to the direction of the maximum opening stress, regardless of the building orientation. The maximum prospective defect evaluated by the extreme value statistics (EVS) method is used as the typical defect for VHCF life prediction. A modified Smith-Waston-Topper (SWT) model was proposed and combined with the Critical Distance Method to predict ultra-high cycle fatigue life. The life prediction accuracy was validated by using both experimental data obtained from the experiments conducted in this paper and experimental data taken from the literature. The results show that 84% of the predicted fatigue lives are within a scatter band of 2 standard deviation, and 16% of the predicted lives are outside a scatter band of 2 standard deviation and within a scatter band of 3 standard deviation.

Influence of powder particle size distribution on the creep performance of Ti-48Al-2Cr-2Nb alloy fabricated via electron beam-powder bed fusion

The effects of particle size distributions (PSDs) on the microstructure and creep behavior of Ti-48Al-2Cr-2 Nb fabricated via electron beam-powder bed fusion (EB-PBF) were investigated. Three PSDs of 45–150 (PSD-A), 38–150 (PSD-B), and 38–180 µm (PSD-C) were used as powder feedstock. Widening the PSD range decreased the relative density of fabricated parts and promoted the formation of banding microstructure. Moreover, samples fabricated with wider PSDs had a higher volume of lack-of-fusion (LoF) defects; however, the content of gas pores decreased significantly in PSD-C, which was related to the presence of coarse powder particles. The volume of the LoF defects in PSD-C was approximately 2.8 times of the same defects in PSD-A, which influenced the creep performance (at 750℃) and failure mechanism of Ti-48Al-2Cr-2 Nb. A longer steady-state creep period at different stress levels was identified for the samples fabricated with the narrowest PSD (45–150 µm). Widening the PSD span also caused weakness in the creep properties and data scattering at higher stress levels of 300 and 350 MPa. The LoF defects and coarse grains accelerated the crack initiation and propagation in Ti-48Al-2Cr-2 Nb during creep. This study represents the first report on the impact of PSD on the creep properties of TiAl alloys fabricated via EB-PBF, which offers new insights and enhances understanding of the powder-process-microstructure-property relationship.

Assessment of structural defects and mechanical characteristics of IN718/St6 functionally graded material produced by direct laser deposition

Functionally graded materials (FGM) do not show special processing in the composite structure due to the combination of mechanical, thermal, magnetic and stress gradient properties. The aim of this study is to produce IN718/St6 FGM samples by direct laser deposition method. The product of this model should enable the development of mechanical products. Best of all, this can be done without significant reduction in texture and case to residual stress that are a consequence of rapid changes in mechanical and thermal properties in non-FGM samples. To fabricate part, direct laser deposition system equipped with a 1 kW continuous fiber laser is used, SEM/EDS analysis and microhardness testing to measure porosity, chemical composition, and quantify gradient mechanical properties is used. In this study, the cladding composition is selected from 100% IN718 to 100% St6 with a 25% change in St6 composition. To prevent the formation of defects, both single-parameter modes and individual layering are examined, considering the diverse nature of the combination. The result shows that using an individual layering structure, reduces 100% Lack of fusion defects in the IN718/St6 structure. EDS analysis confirmed that the St6 content gradually increased from the first to the fifth layer. The substrate hardness gradually increases from 200 Vickers hardness to 550 Vickers hardness, showing an almost linear trend. Moreover, by using individual layering, the coaxial structure is reduced by 55% and the relative orientation of the vertical line is reduced by 18° compared to using the St6 directly (non-FGM).

Crystal plasticity enhanced direct cyclic analysis of cyclic behaviour of LPBF-manufactured AISI 316L

The fatigue performance of Laser Powder Bed Fusion manufactured 316L stainless steel is critical for cyclic loading applications. Additive manufacturing of 316L produces a characteristic microstructure consisting of grains with a fine cellular structure within. This microstructure shows a comparatively high fatigue strength combined with a high defect tolerance. The purpose of this paper is to numerically analyse the local response of this microstructure to cyclic loading and, in particular, the joint action between lack of fusion defects and the surrounding grain structure. The traditional incremental analysis method for polycrystalline alloys is computationally expensive. Therefore, a direct cyclic analysis combined with a phenomenological crystal plasticity model is used in this work to predict the stable cyclic response of the material, resulting in a much lower computational cost. Three statistically equivalent representative volume elements are generated. The considered crystal plasticity parameters are calibrated using experimental tensile stress–strain curves. The comparison with incremental analysis demonstrates the accuracy and efficiency of the proposed method. The shakedown limit, based on the maximum load that allows the convergent cyclic response, significantly depends on the local grain orientation around lack of fusion defects, revealing a reason for the large scatter in the fatigue strength.

Exploring How LPBF process parameters impact the interface characteristics of LPBF Inconel 718 deposited on Inconel 718 wrought substrates

This work investigates the interface properties of LPBF Inconel 718 deposited on Inconel 718 wrought substrates fabricated using the laser powder bed fusion (LPBF) technique. The as-printed (S1, S2, S3, and S4) samples were characterized using optical microscopy (OM),scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and micro-hardness techniques.The samples showed the development of a melted interface zone (MIZ) at the wrought substrate-deposition interface for all processing conditions. The developed interface showed a dendritic grain structure, signifying the remelting of the wrought substrate followed by rapid solidification. The MIZ thickness increased with an increase in laser power and scan speed (28.5 % increase in the MIZ thickness with a ∼ 12 % increase in normalized enthalpy). The assessment of the MIZ showed a high-quality interface. However, with an increase in scanning speed, the density of the MIZ decreases owing to increased porosity and lack-of-fusion (LOF) defects. The S1 condition (250 W and 850 mm/s) resulted in a highly dense part with no visible porosity, LOF defects, and a high relative density (∼99.9 %) in the MIZ region. The S4 condition showed the presence of large porosities and LOF defects at the deposition-MIZ interface, signifying an inferior bond between the deposition and substrate. The microstructural characterization of the LPBF-processed and MIZ region showed an increase in the primary dendritic arm spacing (PDAS) with increasing laser power due to a reduced cooling rate. The micro-hardness characterization of the sample shows a decrease in the hardness of the MIZ attributed to the dissolution of strengthening phases due to remelting. The present work outcome demonstrates the effectiveness of the proposed methodology for manufacturing high-quality parts using LPBF technology.

Size effect on fatigue performance of SLM-ed AlSi10Mg alloy: Role of defect size distribution

The size effect on high-cycle fatigue performance of SLM-ed AlSi10Mg alloy was studied with three different highly stressed areas. It shows clear that small size specimens present higher S-N data and small fatigue initiator sizes compared to large specimens. Fatigue cracks were initiated from either lack of fusion (LOF) pores or gas pores. The sizes of fatigue initiators were analyzed based on Gumbel distribution and Frechet distribution, respectively. The LOF defects were equivalent to small cracks and Paris equation was used to reveal the relationship between the fatigue life, applied stress and fatigue initiator size. P-S-N curves were obtained by combining the fatigue initiator size distributions with crack propagation formula. According to the weak-link theory, P-S-N curves of other sizes could be predicted and it was found that Frechet approach could give a better prediction.

Accelerating phase-field simulation of three-dimensional microstructure evolution in laser powder bed fusion with composable machine learning predictions

Phase-field (PF) modeling is a versatile physics-based computational method that has been used to simulate the evolution of microstructures. The PF method can produce accurate microstructures but suffers from a high computational cost, limiting its use in length scales relevant to additive manufacturing. Using small-scale PF simulations as training data, we trained a surrogate machine learning (ML) model as a computationally cheaper alternative. We use a three-dimensional (3D) U-Net convolutional neural network and learn microstructure evolution in a supervised fashion. With initial microstructure and thermal history as inputs, the ML model can predict the resulting grain orientations at a high accuracy compared to the PF model. Computationally, the ML model is orders of magnitudes faster than the direct PF simulation in a GPU implementation, and scales favorably with increasing number of cells. By spatio-temporally composing multiple ML model predictions at the small-scale, we demonstrate a large-scale 64-layer simulation of a 2 mm × 2 mm × 2 mm cube for a powder bed fusion additive manufacturing process. The ML results revealed a mixture of equiaxed, columnar, and curved grains, comparable to experimental observations. Microstructures resulting from different toolpath strategies, and lack of fusion defects are also demonstrated. This approach paves the way for microstructure-driven process design.

Role of defects and microstructure on the fatigue durability of Inconel 718 obtained by additive layer manufacturing route

AbstractA Laser Powder Bed Fusion Inconel 718 produced with intentionally non‐optimized parameters is investigated to understand the role of defects and microstructure on the high‐cycle fatigue life. Samples from three built directions and three heat treatments were used for fatigue tests at room and 650°C under . Printing orientation has a minor effect on fatigue life at both temperatures. Most samples failed from lack of fusion defects, carefully analyzed by scanning electron microscope (SEM) observations. Surface defect leads to transgranular fracture surface, while subsurface initiation leads to crystallographic fracture surface. curves related to hot isostatic pressure condition shown that defects have higher influence at than at 650°C. Kitagawa diagrams are plotted for both temperatures to quantify the influence of defect size on fatigue limit. Natural cracks are observed at the surface in order to discuss the relative part of initiation life in the whole fatigue life.

A Random Forest Classifier for Anomaly Detection in Laser-Powder Bed Fusion Using Optical Monitoring.

Metal additive manufacturing (AM) is a disruptive production technology, widely adopted in innovative industries that revolutionizes design and manufacturing. The interest in quality control of AM systems has grown substantially over the last decade, driven by AM's appeal for intricate, high-value, and low-volume production components. Geometry-dependent process conditions in AM yield unique challenges, especially regarding quality assurance. This study contributes to the development of machine learning models to enhance in-process monitoring and control technology, which is a critical step in cost reduction in metal AM. As the part is built layer upon layer, the features of each layer have an influence on the quality of the final part. Layer-wise in-process sensing can be used to retrieve condition-related features and help detect defects caused by improper process conditions. In this work, layer-wise monitoring using optical tomography (OT) imaging was employed as a data source, and a machine-learning (ML) technique was utilized to detect anomalies that can lead to defects. The major defects analyzed in this experiment were gas pores and lack of fusion defects. The Random Forest Classifier ML algorithm is employed to segment anomalies from optical images, which are then validated by correlating them with defects from computerized tomography (CT) data. Further, 3D mapping of defects from CT data onto the OT dataset is carried out using the affine transformation technique. The developed anomaly detection model's performance is evaluated using several metrics such as confusion matrix, dice coefficient, accuracy, precision, recall, and intersection-over-union (IOU). The k-fold cross-validation technique was utilized to ensure robustness and generalization of the model's performance. The best detection accuracy of the developed anomaly detection model is 99.98%. Around 79.40% of defects from CT data correlated with the anomalies detected from the OT data.

Defect Classification for Additive Manufacturing with Machine Learning.

Additive manufacturing offers significant design freedom and the ability to selectively influence material properties. However, conventional processes like laser powder bed fusion for metals may result in internal defects, such as pores, which profoundly affect the mechanical characteristics of the components. The extent of this influence varies depending on the specific defect type, its size, and morphology. Furthermore, a single component may exhibit various defect types due to the manufacturing process. To investigate these occurrences with regard to other target variables, this study presents a random forest tree model capable of classifying defects in binary images derived from micrographs. Our approach demonstrates a classification accuracy of approximately 95% when distinguishing between keyhole and lack of fusion defects, as well as process pores. In contrast, unsupervised models yielded prediction accuracies below 60%. The model's accuracy in differentiating between lack of fusion and keyhole defects varies based on the manufacturing process's parameters, primarily due to the irregular shapes of keyhole defects. We provide the model alongside this paper, which can be utilized on a standard computer without the need for in situ monitoring systems during the additive manufacturing process.

Experimental scatter of the fatigue response of additively manufactured components: a statistical method based on the Profile Likelihood

The fatigue response of additively manufactured (AM) specimens is mainly driven by manufacturing defects, like pores and lack of fusion defects, which are mainly responsible for the large variability of fatigue data in the S–N plot. The analysis of the results of AM tests can be therefore complex: for example, the influence of a specific factor, e.g. the building direction, can be concealed by the experimental variability. Accordingly, appropriate statistical methodologies should be employed to safely and properly analyze the results of fatigue tests on AM specimens. In the present paper, a statistical methodology for the analysis of the AM fatigue test results is proposed. The approach is based on shifting the experimental failures to a reference number of cycles starting from the estimated P–S–N curves. The experimental variability of the fatigue strength at the reference number of cycles is also considered by estimating the profile likelihood function. This methodology has been validated with literature datasets and has proven its effectiveness in dealing with the experimental scatter typical of AM fatigue test results.

Elucidating the role of pulse shaping on defects formation in aluminum alloys fabricated by powder bed fusion

The Powder Bed Fusion (PBF) additive manufacturing technique, although widely studied and implemented in the industry, still presents issues of porosity and lack of fusion even when optimal processing parameters are used. The benefits and drawbacks of PBF utilizing pulsed lasers are both consequences of the transient temperature field induced by laser-matter interaction. During laser processing with nanosecond pulse durations, intense heating and cooling rates are induced, setting the melt pool dimensions, which are directly related to the occurrence of lack of fusion, and ablation of the processed material, leading to recoil pressure that induces the keyhole effect, increasing the occurrence of porosity. Consequently, controlling the transient temperature field is a major challenge in incorporating pulsed wave laser technology into PBF to minimize porosity and lack of fusion defects. In this study, to reduce porosity and lack of fusion, a smooth heating rate able to sinter powder grains is designed to facilitate heat flow through the heat affected zone, followed by a sharper heating rate that generates a fully molten region while reducing ablation at the same time. This work represents the first attempt to control the transient temperature field, by shaping a nanosecond laser pulse in the time domain, thereby affecting the formation of defects. The effects of the pulse shape on build quality quantified by lack of fusion and high-energy spherical pores were investigated using X-ray microtomography, molecular dynamics (MD), X-ray diffraction (XRD), Electron Backscatter Diffraction (EBSD), and finite element simulations. The variation of porosity and lack of fusion within manufactured samples were revealed by the high-resolution 3D X-ray micro computed tomography. The differences in the transient temperature field, resulting residual stresses, and microstructure are attributed to the differences in the energy delivery rates within the time domain shaped laser pulses. Laser pulse shaping is an additional parameter that plays an important role in optimizing the PBF as-processed part's production opening a new research niche.