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At least 631 records · Page 35

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗

Local prediction of Laser Powder Bed Fusion porosity by short-wave infrared imaging thermal feature porosity probability maps

We report that local thermal history can significantly vary in parts during metal Additive Manufacturing (AM), leading to local defects. However, the sequential layer-by-layer nature of AM facilitates in-situ part voxelmetric observations that can be used to detect and correct these defects for part qualification and quality control. The challenge is to relate this local radiometric data with local defect information to estimate process error likelihood in future builds. This paper uses a Short-Wave Infrared (SWIR) camera to record the temperature history for parts manufactured with Laser Powder Bed Fusion (LPBF) processes. The porosity from a cylindrical specimen is measured by ex-situ micro-computed tomography (μCT). Specimen data from the SWIR camera, combined with the μCT data, are used to generate thermal feature-based porosity probability maps. The porosity predictions made by various SWIR thermal feature-porosity probability maps of a specimen with a complex geometry are scored against the true porosity obtained via μCT. The receiver operating characteristic curves constructed from the predictions for the complex sample demonstrate the porosity probability mapping methodology’s potential for in-situ based porosity detection.

36 MATERIALS SCIENCE↗

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗

Sensor fusion of pyrometry and acoustic measurements for localized keyhole pore identification in laser powder bed fusion

We report in-situ process monitoring as an aid to part qualification for laser powder-bed fusion (L-PBF) technology is a topic of increasing interest to the additive manufacturing community. In this work, airborne acoustic and inline pyrometry measurements were recorded simultaneously with the laser position. X-ray radiography imaging was used to spatio-temporally register keyhole pore locations to the pyrometry and acoustic signals, enabling binary labeling of data partitions based on pore formation. These labeled partitions were subsequently featurized using a highly comparative time-series analysis toolbox. Acoustic data was found to be much more effective than the pyrometry data for keyhole pore identification. However, when the information contained in both sensing modalities was combined in a sensor fusion strategy, the error rates of the top performing models were significantly reduced.

36 MATERIALS SCIENCE↗

Predicting melt pool depth and grain length using multiple signatures from in-situ single camera two-wavelength imaging pyrometry for laser powder bed fusion

In laser powder bed fusion (LPBF), the in-situ process signatures are known to have a direct correlation with the microstructural properties of the solidified melt pool (MP). It is known that the MP cooling and heating rates, and laser processing parameters can critically determine the grain structure and thereby affect the part properties. The objective of this work is to study the feasibility of using in-process, high-speed imaging pyrometry for evaluating the solidified MP properties “below” the surface, such as depth and microstructural properties. To accomplish this, we employ an in-house single camera-based two-wavelength imaging pyrometry (STWIP) system for monitoring the printing of single-scan tracks with Inconel 718 on a commercial LPBF printer (EOS M290). Further, the lab designed STWIP system is a coaxial high-speed (>10,000 fps) imaging system capable of monitoring MP temperature, morphology, and intensity profiles. The temperature measurements from STWIP are emissivity independent. The STWIP measured MP signatures of the printed tracks are correlated with the ex-situ microscopy characterized MP depth and the average grain lengths. From the data analysis, using support vector machine (SVM)-based regression models, we found that the MP temperature signatures are crucial for an accurate prediction of MP depth and the grain length, thus validating the novelty and necessity of the developed in-situ monitoring methods and analysis.

36 MATERIALS SCIENCE↗

Topology-driven compressive behavior of Inconel 718 lattice structures with Z-strut reinforcement fabricated by laser powder bed fusion

This study investigates the compressive deformation behavior and mechanical performance of Inconel 718 lattice structures fabricated by laser powder bed fusion (LPBF). Four unit-cell topologies—BCC, FCC, BCCZ, and FCCZ—were designed with a unit-cell size of 3 mm and fabricated under identical process conditions to isolate the effect of topology. Measured relative densities ranged from 14.65% to 17.72%. Compressive testing showed that Z-strut-reinforced topologies (BCCZ: 54.6 MPa; FCCZ: 80.2 MPa) exhibited higher strength than their unreinforced counterparts, which may be associated with mixed-mode deformation behavior enabled by the vertically aligned Z-struts. Finite element simulations and Digital Image Correlation (DIC) analysis support the observation of a transition from node-dominated deformation in BCC/FCC to mixed-mode deformation in BCCZ/FCCZ. These findings suggest that unit-cell topology is a key design variable for tailoring deformation mechanisms in LPBF lattice structures.

36 MATERIALS SCIENCE↗

Effect of heat treatment on creep behavior of 316 L stainless steel manufactured by laser powder bed fusion

The objective of this study is to understand the thermal stability of microstructure and its effect on the creep behavior of additively-manufactured 316L stainless steel (AM 316L SS). Creep specimens were fabricated from rods printed by a laser powder bed fusion process. Six different heat treatments, namely 650 °C/1 h, 700 °C/1 h, 750 °C/1 h, 800 °C/1 h, 900 °C/1 h and 1050 °C/1 h were applied to the creep specimens. The heat-treated specimens were creep-tested under the same condition, 550 °C/275 MPa to evaluate the effect of post-build heat treatment on the creep behavior of AM 316L SS. In the temperature range of 650-750 °C, dislocation density within cells, and cell size and wall thickness were affected by the heat treatment, while elemental segregation at boundaries remained unchanged and Mn-enriched Si oxide particles remained stable. In the temperature range of 750-900 °C, concurrent changes were observed in dislocation cell structures, elemental segregation and oxide particles. The 1050 °C-heat treatment removed cell structures and boundary solute segregations, leading to formation of equiaxed grains; Mn-enriched Si oxide particles in the as-built specimen were replaced by more stable Mn-enriched Cr oxides. The creep life of AM 316L SS increased after the heat treatment at 650 °C and then decreased with increasing temperature up to 900 °C where cell/subgrain structures still existed. The creep rate and creep elongation followed an opposite trend. The creep rate can be correlated with the structural parameters of cell/subgrain size and cell wall/boundary thickness and can be rationalized by different strengthening mechanisms of dislocation cells and subgrains. The heat treatment affected strongly the primary and secondary creep but had a minimal effect on the tertiary creep of AM 316L SS.

316L stainless steel↗

In situ study on radiation response of tungsten manufactured by laser powder bed fusion

Tungsten (W) produced by laser powder bed fusion (LPBF) was examined by in situ Krypton (Kr) ion irradiation at 400 °C up to 2.52 displacements per atom (dpa) to investigate its radiation response. Dislocation loops with identical Burgers vectors form aligned raft structures, inducing significant grain misorientation accumulation. Defect saturation was observed beyond 0.36 dpa, marked by constant loop density and raft spacing. WO 3 nanoparticles are found in the as-printed matrix and served as efficient defect sinks. Dislocation loops were absorbed at the W/WO 3 interface, facilitating defect annihilation and suppressing defect accumulation. In conclusion, these findings highlight the role of LPBF microstructure and oxide interfaces in mediating radiation-induced defect evolution, offering insights for designing radiation tolerant W-based materials.

Defect sink↗

Effect of homogenization heat treatment on the evolution of carbonitrides in powder bed fusion processed INCONEL 718

Inconel 718 fabricated using laser powder-bed fusion, contains precipitates in the as-built condition that can be coarsened by high-temperature heat treatments. In this study, two homogenization heat treatment regimens were applied to discern the impact of heat treatment conditions on the growth of complex M(C, N) carbonitrides. In the first heat treatment, the samples underwent heat treatment between 1050 °C and 1200 °C for 0.5 h. In the second heat treatment, the samples were held at a constant temperature of 1150 °C, with varied holding times from 0.5 h to 8 h. Heat treatments dissolved the unstable Laves phase, but the carbonitrides persisted in the structure regardless of temperature and duration. Changes in the compositions, lattice parameters, and sizes of M(C, N) carbonitrides were measured using transmission electron microscopy and high-energy synchrotron X-ray diffraction. The results show an Nb enrichment at carbonitrides while Nb loss at the matrix with increased homogenization temperature. The findings suggest the optimum heat treatment conditions to achieve a homogeneous structure and controlled carbonitride size are between 1000 and 1050 °C for up to 2 h.

IN178↗

Cooling dynamics of two titanium alloys during laser powder bed fusion probed with in situ X-ray imaging and diffraction

Metal parts produced by laser powder bed fusion (LPBF) additive manufacturing exhibit characteristic microstructures comparable to those observed in laser welding. The primary cause of this characteristic microstructure is rapid, localized heating and cooling cycles, which result in extreme thermal gradients where material solidification is followed by fast cooling in the solid state. The final microstructure and mechanical performance are also influenced by pore formation caused by melt pool fluid dynamics. Here, we use high speed, in situ X-ray diffraction to probe the kinetics of cooling and solid-solid phase transitions after laser melting in two aerospace titanium alloys: Ti-6Al-4V, an α + β alloy; and Ti-5Al-5V-5Mo-3Cr, a near-β alloy. We complement these diffraction studies with in situ X-ray imaging to probe melt pool dynamics and pore formation. From these two complementary probes, we quantify pore formation during melting and the subsequent microstructural evolution as the material rapidly cools after solidification. These results are critical for understanding defect formation and residual stress development in different titanium alloys under LPBF conditions and can help inform process models to predict final part performance.

36 MATERIALS SCIENCE↗

Multi phenomena melt pool sensor data fusion for enhanced process monitoring of laser powder bed fusion additive manufacturing

Finding actionable trends in laser-based metal additive manufacturing process monitoring data is challenging owing to the diversity and complexity of the underlying physical interactions. A single monitoring solution that captures a particular process phenomenon, such as a photodiode that tracks melt pool intensity, is not alone capable of evaluating process stability or detecting flaw formation with sufficient precision for routine application in industry. In this work, to improve flaw detection performance, we adopted a data fusion approach that captures multiple process phenomena. To demonstrate this, we acquired data from laser powder bed fusion (LPBF) builds of cylindrical specimens produced with different laser spot sizes, emulating defocusing due to process faults such as thermal lensing. The resulting specimens had porosity of varying types and severity, quantified by post-build non-destructive X-ray computed tomography, Archimedes density measurements, and destructive metallographic characterization. During the build, the melt pool state was monitored with two coaxial high-speed video cameras and a temperature field imaging system. Physically intuitive low-level melt pool signatures, such as melt pool temperature, shape and size, and spatter intensity were extracted from this high-dimensional, image-based sensor data. These process signatures were subsequently used as input features in relatively simple machine learning models, such as a support vector machine, which were trained to detect laser defocusing, and in addition, predict porosity type and severity. The results show that the data fusion approach significantly enhanced system performance by reducing the overall false positive rate from ~ 0.1 to ~ 0.001 without sacrificing the true positive rate (~0.90). These results were at par with a black-box, deep machine learning approach (convolutional neural network).

36 MATERIALS SCIENCE↗

Multimodal and multiscale strengthening mechanisms in Al-Ni-Zr-Ti-Mn alloy processed by laser powder bed fusion additive manufacturing

The unique thermokinetics of laser-powder bed fusion additive manufacturing (L-PBFAM) has been exploited for development of a novel high-strength Al-Ni-Ti-Zr-Mn alloy. The addition of 0.5 wt% Mn leads to extraordinary improvement in ultimate tensile strength (502 MPa) and work hardening due to the activation of two Mn-induced strengthening mechanisms. First, by a bimodal particle strengthening effect due to Al 31 Mn 6 Ni 12 nano-quasi-crystal particles rejected in inter-dendritic spaces and fibrous Al 3 Ni eutectic dendritic channels, which predominately contributes to the strength improvement, and second by solid solution strengthening from remaining Mn entrapped in Al. These mechanisms supplement the particle strengthening effect imparted by coherent and incoherent Al 3 (Ti,Zr) co-precipitates present at melt pool boundaries, dislocation strengthening due to solidification induced strain, and Hall-Petch and backstress strengthening effect due to heterogenous grain size distribution occurring at various length scales. In conclusion, the solidification dynamics and hierarchical heat distribution that are associated with L-PBFAM resulted in complex spatial variations in these strengthening phenomena and were investigated via a high-throughput multiscale structure–property correlation that involved thermokinetic simulation, X-ray diffraction, high-resolution nanoindentation mapping, and site-specific transmission electron microscopy of the alloy.

36 MATERIALS SCIENCE↗

Quantification of solution annealing effects on microstructure and property in a laser powder bed fusion 316H stainless steel

Solution annealing (SA) is an effective way to mitigate microstructural heterogeneity and to optimize mechanical performance of alloys manufactured by laser powder bed fusion (LPBF). In this study, a comprehensive and quantitative understanding of the recovery and recrystallization processes in the SA temperature range of LPBF 316H stainless steel is provided using results from analytical electron microscopy and in-situ high-energy synchrotron x-ray scattering. The profound effect of dislocation structures and secondary phase particles on mechanical performance, particularly under tension and creep conditions, is rationalized using deformation models that incorporate microstructural inputs. This study, for the first time, quantifies the broad effect of nano oxide inclusions on dislocation recovery kinetics, on grain growth and recrystallization kinetics, and on tension strength and creep resistance. The fundamental differences between the LPBF and the conventional wrought materials are revealed. The findings address critical questions in post-build processing of AM materials and pave the way for their rapid qualification for high temperature applications.

In-situ X-ray diffraction↗

Comparison of powder bed fusion and directed energy deposition for tailoring mechanical properties of traditionally brittle alloys

The mechanical performance of an Fe-Co intermetallic alloy processed by laser powder bed fusion (L-PBF) and laser directed energy deposition (L-DED) additive manufacturing is compared. L-PBF material was characterized by high strength (500–550 MPa) and high ductility (35%) in tension, corresponding to a ~250% increase in strength and an order-of-magnitude improvement in ductility relative to conventional material. Conversely, L-DED material exhibited similarly poor tensile properties to the conventional wrought alloy, with low strength (200–300 MPa) and low ductility (0–2.7%). Finally, the disparity in properties between L-PBF and L-DED material is discussed in the context of the fundamental differences between manufacturing methods.

36 MATERIALS SCIENCE↗

Plasticity and fracture behavior of Inconel 625 manufactured by laser powder bed fusion: Comparison between as-built and stress relieved conditions

In this work, the influence of stress relief on the plasticity and fracture behavior of Inconel 625 fabricated through laser powder bed fusion additive manufacturing (AM) was investigated. The as-built versus stress relieved microstructures were compared, showing similar grain structures but the presence of ~10 vol % δ phase in the stress relieved condition, and no δ phase in the as-built condition. Mechanical tests under plane strain tension were performed on the stress relieved samples, and an anisotropic plasticity model was calibrated and validated using finite element simulations. Uniaxial and notched tension tests were performed on both as-built and stress relieved samples to probe the effect of stress relief on stress state- and direction-dependent fracture behavior. It was found that on average, the fracture strain of the stress relieved samples along the build direction was 30% higher than that along the perpendicular build direction in the stress state range studied, and the stress relief heat treatment resulted in a 45% decrease in fracture strain. The fracture strain in stress relieved samples was more strongly dependent on stress state than in as-built samples.

36 MATERIALS SCIENCE↗

Optimization of direct aging temperature of Ti free grade 300 maraging steel manufactured using laser powder bed fusion (LPBF)

Maraging steels are of interest to the tool and die industry owing to their high strength, toughness and machinability. Additive manufacturing technologies like laser powder bed fusion (LPBF) can result in a paradigm shift in the design of maraging steel tools. Here, the lack of precipitates, in combination with solute segregation and non-equilibrium microstructure in Grade 300 maraging steel fabricated via LPBF makes the steel amenable to strengthening via direct aging post fabrication instead of the conventional solution treatment and aging. In this study we have focused on optimizing the direct aging temperature for a Ti-free Grade 300 maraging steel fabricated via LPBF for two different aging times. Through strain hardening analysis and detailed microstructural characterization, we show that direct aging at a temperature of 440 °C for 6 h resulted in the best strength-ductility combination. Aging samples at a lower temperature or shorter time resulted in no strain hardening prior to necking as a result of lower fraction of reverted austenite, whereas aging samples at a higher temperature resulted in extensive recrystallization of martensite, coarsening of precipitates, and extensive austenite reversion, resulting in softening of the fabricated parts.

36 MATERIALS SCIENCE↗

On the thermal coarsening and transformation of nanoscale oxide inclusions in 316L stainless steel manufactured by laser powder bed fusion and its influence on impact toughness

The thermal evolution of nanoscale oxide inclusions in 316L stainless steel (SS) manufactured by laser powder bed fusion additive manufacturing (AM) was explored. The size, chemical composition, morphology, and distribution of the oxides were characterized as the function of heat treatment conditions. The study revealed the mechanistic driving force of the rapid oxide coarsening during recrystallization. Ostwald ripening governs oxide coarsening. The active grain boundary-oxide interaction at the early stage of recrystallization accelerated oxide coarsening via enhanced solute diffusion along grain boundaries. Pipe diffusion along dislocation cellular boundaries has a negligible contribution to oxide coarsening. At high temperatures (T> 1065 °C), although lattice diffusion primarily controlled the oxide growth, the contribution from the grain-boundary diffusion was necessary. The transformation from MnSiO 3 to CrMn 2 O 4 took place in the un-recrystallized grains but was not observed when recrystallization started. The interaction of grain boundary and oxides during recrystallization resulted in a high fraction of oxides accumulated at grain boundaries. While oxide coarsening does not significantly alter the toughness value, grain-boundary oxides promote microvoid formation and intergranular fracture under Charpy impact in the recrystallized AM 316L SS.

36 MATERIALS SCIENCE↗

A lightweight Fe–Mn–Al–C austenitic steel with ultra-high strength and ductility fabricated via laser powder bed fusion

Lightweight Fe–Mn–Al–C steels have become a topic of significant interest for the defense and automotive industries. These alloys can maintain high strength and ductility while also reducing weight in structural applications. Conventionally processed Fe–Mn–Al–C austenitic steels with high Al content (~9 wt%) demonstrate greater than 1.5 GPa strength with 35% elongation. Several recent studies have demonstrated success in fabricating steel parts using laser powder bed fusion (L-PBF) additive manufacturing (AM), which can generate near-net-shape components with complex geometries and is capable of local microstructural control. However, studies on L-PBF processing of Fe–Mn–Al–C alloys have focused on low Al content (<5 wt%) compositional regimes representing alloys that undergo transformation-induced plasticity (TRIP) and twinning-induced plasticity (TWIP). Here, in this study, we present the effects of L-PBF processing on the microstructure and mechanical properties of an Fe–30Mn–9Al–1Si-0.5Mo-0.9C austenitic steel. A process optimization framework is employed to determine an ideal L-PBF processing space that will result in >99% density parts. Implementing this framework resulted in near-fully dense specimens fabricated over a broad range of process parameters. Additionally, two bi-directional scan rotation strategies (90° and 67°) were applied to understand their effects on texture and anisotropy in this material. As-printed specimens displayed considerable work-hardening characteristics with average strengths of up to 1.3 GPa and 36% elongation in the build direction. However, solidification microcracks oriented in the build direction resulted in anisotropy in tensile strength and ductility resulting in average strengths of 1.1 GPa and 20% elongation perpendicular to the build direction. The successful L-PBF fabrication of Fe–30Mn–9Al–1Si-0.5Mo-0.9C presented here is expected to open new avenues for weight reduction in structural applications with a high degree of control over part topology.

36 MATERIALS SCIENCE↗