Laser Additive Manufacturing Process Research Articles

In-situ process monitoring and adaptive quality enhancement in laser additive manufacturing: A critical review

Laser Additive Manufacturing (LAM) presents unparalleled opportunities for fabricating complex, high-performance structures and components with unique material properties. Despite these advancements, achieving consistent part quality and process repeatability remains challenging. This paper provides a comprehensive review of various state-of-the-art in-situ process monitoring techniques, including optical-based monitoring, acoustic-based sensing, laser line scanning, and operando X-ray monitoring. These techniques are evaluated for their capabilities and limitations in detecting defects within Laser Powder Bed Fusion (LPBF) and Laser Directed Energy Deposition (LDED) processes. Furthermore, the review discusses emerging multisensor monitoring and machine learning (ML)-assisted defect detection methods, benchmarking ML models tailored for in-situ defect detection. The paper also discusses in-situ adaptive defect remediation strategies that advance LAM towards zero-defect autonomous operations, focusing on real-time closed-loop feedback control and defect correction methods. Research gaps such as the need for standardization, improved reliability and sensitivity, and decision-making strategies beyond early stopping are highlighted. Future directions are proposed, with an emphasis on multimodal sensor fusion for multiscale defect prediction and fault diagnosis, ultimately enabling self-adaptation in LAM processes. This paper aims to equip researchers and industry professionals with a holistic understanding of the current capabilities, limitations, and future directions in in-situ process monitoring and adaptive quality enhancement in LAM.

Effect of laser power on the structure and wear performance of laser additively manufactured Cu45Zr45Al6Ti4 metallic glass coating

Laser powder bed fusion (LPBF) technology presents significant potential for the production of metallic glass (MG) coatings. This work investigated the influence of laser power on the structure and wear performance of a CuZr-based metallic glass coating with composition of Cu45Zr45Al6Ti4 on Ti substrate. It was observed that the melt pool, which serves as the fundamental building block for constructing MG coatings in LPBF, undergoes a transition from conduction mode to keyhole mode, and subsequently to extended mode with increasing laser power. The MG coatings prepared using low power laser (140 W) and medium power laser (240 W) both exhibited a nearly fully amorphous state. However, at a laser power of 360 W, noticeable crystallization occurred in the coating, as evidenced by SEM observation. The wear rate of Cu45Zr45Al6Ti4 MG coating was measured to be 4.67 × 10−6 mm3·N−1·m−1, which is significantly lower than that of the Ti substrate (6.38 × 10−4 mm3·N−1·m−1). This study reveals the relationship between the laser power and morphology of the melt pool, as well as the structure and wear performance of the LPBF-fabricated MG coatings, offering guidance for optimizing the laser additive manufacturing process of wear-resistant MG coatings.

Correlating Laser Additive Manufacturing Process with Heat Source Coefficients by Integrated Experimental and Numerical Models

Correlating Laser Additive Manufacturing Process with Heat Source Coefficients by Integrated Experimental and Numerical Models

Fabrication of crack-free aluminum alloy 6061 parts using laser foil printing process

PurposeThis paper aims to present the fabrication of 6061 aluminum alloy (AA6061) using a promising laser additive manufacturing process, called the laser-foil-printing (LFP) process. The process window of AA6061 in LFP was established to optimize process parameters for the fabrication of high strength, dense and crack-free parts even though AA6061 is challenging for laser additive manufacturing processes due to hot-cracking issues.Design/methodology/approachThe multilayers AA6061 parts were fabricated by LFP to characterize for cracks and porosity. Mechanical properties of the LFP-fabricated AA6061 parts were tested using Vicker’s microhardness and tensile testes. The electron backscattered diffraction (EBSD) technique was used to reveal the grain structure and preferred orientation of AA6061 parts.FindingsThe crack-free AA6061 parts with a high relative density of 99.8% were successfully fabricated using the optimal process parameters in LFP. The LFP-fabricated parts exhibited exceptional tensile strength and comparable ductility compared to AA6061 samples fabricated by conventional laser powder bed fusion (LPBF) processes. The EBSD result shows the formation of cracks was correlated with the cooling rate of the melt pool as cracks tended to develop within finer grain structures, which were formed in a shorter solidification time and higher cooling rate.Originality/valueThis study presents the pioneering achievement of fabricating crack-free AA6061 parts using LFP without the necessity of preheating the substrate or mixing nanoparticles into the melt pool during the laser melting. The study includes a comprehensive examination of both the mechanical properties and grain structures, with comparisons made to parts produced through the traditional LPBF method.

Physics guided heat source for quantitative prediction of IN718 laser additive manufacturing processes

Challenge 3 of the 2022 NIST additive manufacturing benchmark (AM Bench) experiments asked modelers to submit predictions for solid cooling rate, liquid cooling rate, time above melt, and melt pool geometry for single and multiple track laser powder bed fusion process using moving lasers. An in-house developed Additive Manufacturing Computational Fluid Dynamics code (AM-CFD) combined with a cylindrical heat source is implemented to accurately predict these experiments. Heuristic heat source calibration is proposed relating volumetric energy density (ψ) based on experiments available in the literature. The parameters of the heat source of the computational model are initially calibrated based on a Higher Order Proper Generalized Decomposition- (HOPGD) based surrogate model. The prediction using the calibrated heat source agrees quantitatively with NIST measurements for different process conditions (laser spot diameter, laser power, and scan speed). A scaling law based on keyhole formation is also utilized in calibrating the parameters of the cylindrical heat source and predicting the challenge experiments. In addition, an improvement on the heat source model is proposed to relate the Volumetric Energy Density (VEDσ) to the melt pool aspect ratio. The model shows further improvement in the prediction of the experimental measurements for the melt pool, including cases at higher VEDσ. Overall, it is concluded that the appropriate selection of laser heat source parameterization scheme along with the heat source model is crucial in the accurate prediction of melt pool geometry and thermal measurements while bypassing the expensive computational simulations that consider increased physics equations.

Recent progress in carbide‐based composite materials fabricated by laser additive manufacturing processes

AbstractFabricating and introducing new materials with new features is one of the most important goals for many scientific groups. Today, additive manufacturing (AM) is known as one of the new production methods, which can create an excellent opportunity for achieving this goal. As one of the ongoing production processes, the laser AM (LAM) methods have the proper capacity for producing new advanced materials like carbide, nitride, and boride‐based materials. Hence, this work aims to review carbide‐based materials produced by LAM techniques with the composite viewpoint. These materials can act as a matrix, reinforcement, or tertiary component in advanced composites. With this viewpoint, these composite materials were introduced in eight separate sections, which are tungsten carbide, titanium carbide, silicon carbide, niobium carbide, chrome carbide, vanadium carbide, and boron carbide, as well as high entropy alloy composites.

Microstructure Evolution and Frictional Wear Behavior of Al–18Si–4Mg–2Mn–0.5Fe–xCu Alloys Fabricated by Laser Additive Manufacturing

The microstructure evolution, corrosion resistance, and wear resistance of Al–18Si–4 Mg–2Mn–0.5Fe–xCu (x = 0,1,2,3,4,5 wt%) alloys prepared by laser additive manufacturing (LAM) process are studied. It is found that the addition of Cu not only produces Cu‐rich strengthened phase, but also promotes the precipitation of the second phase. With the addition of Cu, the corrosion resistance of the alloy decreases, which is due to the increase of potential difference caused by the increase of the strengthening phase. The addition of Cu can effectively inhibit corrosion cracking. The hardness and wear resistance of the alloy increase with the increase of Cu content under the synergistic strengthening of the Q‐Al5Cu2Mg8Si6 phase and Al2Cu phase. When the Cu content is 3 wt%, the hardness and wear resistance of the alloy are the best. However, with the increase of Cu content, part of the Q phase is transformed into the Al2Cu phase; this synergistic strengthening effect is weakened, and the hardness and wear resistance of the alloy are reduced, but still higher than that of the alloy without Cu addition, which indicates that the addition of Cu can effectively improve the hardness and wear resistance of the alloy.

A single-sensor multi-scale quality monitoring methodology for laser-directed energy deposition: Example with height instability and porosity monitoring in additive manufacturing of ceramic thin-walled parts

Laser Additive Manufacturing (LAM) faces various technical challenges, encompassing issues with dimensional accuracy, mechanical properties, and processing-related defects, such as surface roughness, cracking, and residual porosity. Currently, the quality of safety-critical parts produced by LAM processes, which is still improved through trial-and-error adjustments of multiple process variables, have limited real-time monitoring capabilities. This study introduces an innovative method for real-time quality assessment of laser-directed energy deposition (LDED) procedures across multiple scales (macroscale, mesoscale, and microscale) utilizing a single sensor. This approach is founded on two fundamental components: the single-sensor system for data acquisition and the algorithm for simultaneous multi-scale quality monitoring. For the data acquisition system aspect, a single-sensor, high dynamic range (HDR), multi-scale information acquisition system has been developed to mitigate intense radiation, eliminate plume disturbances, and rectifies backlight shadows, facilitating clearer images of deposition contours and the molten pool region. In the realm of data monitoring algorithms, a physics model-driven supervisory algorithm is employed to enable monitoring of contour height instability, while a convolutional neural network (CNN), driven by image data, is utilized for porosity prediction. Then, this algorithm adeptly tackles the challenge of simultaneously monitoring macroscopic contour and mesoscale porosity. Regarding the validation of the method, the outcomes of single-sensor multi-scale quality monitoring in additive manufacturing of ceramic thin-wall parts indicate a 100% recognition rate for deposition contour and molten pools, contour feature recognition with a relative error of under 0.05%, porosity prediction accuracy surpassing 99%, and a monitoring time of 80.4 ms per frame. Single-sensor multi-scale real-time quality monitoring can serve as a methodological support for future real-time quality control in LDED.

Listening for defects in laser additive manufacturing in real time

Researchers from Switzerland's Ecole Polytechnique Fédérale de Lausanne (EPFL) have developed a pioneering approach to defect detection in laser additive manufacturing processes.

Using artificial neural networks to model single bead geometries processed by laser-wire direct energy deposition

Wire-feed laser additive manufacturing processes have gained researchers’ attention because of their potential to reduce material waste, guarantee accuracy, increase material quality and density, and produce a wide dimensional range of final products. Nevertheless, printing materials with desired geometrical properties of the beads is still challenging in such processes. This might be attributed to the need for more sufficient experimental data and precise modeling approaches. In this study, an architecture based on Artificial Neural Networks (ANNs) is developed to model the bead geometries (width, height, and area), considering the wire feed rate, laser power, and travel speed as process parameters. A design-of-experiment based on full factorial design is considered for processing single beads with a Fraunhofer coaxial wire-feed laser system. Inconel 625 wire with a diameter of 1.14 mm and stainless steel substrate are utilized as the experimental materials. Geometrical data is obtained using a laser scanner model RA-7525 SE with 0.026mm volumetric accuracy. The beads’ geometrical details are provided as the feeding data for the proposed ANN. For each bead, a length of 10 mm is considered to calculate the average geometrical parameters, which increases the accuracy of the dataset in comparison to the values acquired via a macroscopic picture of the cross-section of each weld bead. A variety of hyperparameters are chosen and compared regarding precision criteria, including Mean Square Error (MSE), to increase the model‘s accuracy. A train-test separation strategy is considered to evaluate the model‘s accuracy on independent data points. The outcome of this research is an ANN-based geometry prediction model that can be utilized to enhance the development of offline path planners and optimize process parameter selection for a precise geometry toward process control.

Insights into the applicability of laser energy density in directly preparing Al2O3-based eutectic ceramics by laser additive manufacturing

Laser additive manufacturing (LAM) has become a promising technique to directly fabricate high-performance Al2O3-based eutectic ceramics, but the applicability of laser energy density (LED), a comprehensive index commonly used to regulate the LAM process of metallic parts, in preparing brittle ceramic samples with narrower laser processing windows is not clear yet. In this paper, Al2O3/GAP/ZrO2 eutectic ceramics are prepared by LAM to investigate the effects of LED on forming quality and melting dimensions of the as-deposited eutectic samples. The results indicate that the reliability of using LED as a design parameter depends on the way how it is changed. There is a response relationship between the LED and experimental results when individually adjusting laser power P or scanning speed v, but abnormal phenomena are detected when simultaneously changing P and v. It is found that the melting dimensions obtained under higher LED can be unexpectedly smaller. Moreover, there is a significant difference in the melting dimensions despite using the same LED. In addition, 50 layers thin-wall structured Al2O3/GAP/ZrO2 eutectic specimens prepared under a constant LED present significant differences in the forming quality. It is revealed that the contribution of P to LED is much greater than that of v, which is not consistent with the same influence degree reflected in the calculation formula. Thus, there are significant limitations to utilizing LED to regulate the LAM process of brittle ceramics in consideration of the sensitivity of their forming quality to changes in laser parameters.

Effect of Combined Direct Current Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

Effect of Combined Direct Current Electric Field and Pulsed Magnetic Field on the Transient Melt Pool in Laser Additive Manufacturing Process

Online monitoring of local defects in robotic laser additive manufacturing process based on a dynamic mapping strategy and multibranch fusion convolutional neural network

Online monitoring is essential for laser additive manufacturing (AM) to improve in-process quality control. Currently, accurate monitoring of local defects in the laser AM process remains a challenge. This paper proposes a method for predicting local defects in the laser AM process based on a dynamic mapping strategy and the multibranch fusion convolutional neural network (MBFCNN). In-situ sensing of the laser-material interaction zone is achieved using a camera integrated coaxially with the printing system. Experiment-based datasets are constructed, in which the in-process images were sampled and matched to the extracted local defect information based on their temporal-spatial correspondence. A dynamic mapping strategy using a sliding sampling window is introduced to achieve continuous monitoring. Considering the cyclic and layer-by-layer processing principle of laser AM, we propose MBFCNN to map the in-process images to local defect information. A multibranch feature extraction module is designed based on the deposited layers of the target region to be monitored, in which each branch extracts high-dimensional representations from in-process images corresponding to a certain layer. We further introduce an attention mechanism to distinguish the importance of each branch and a feature fusion module to fuse the high-level information. Experimental results and comparison with traditional convolutional neural networks demonstrate the effectiveness of our method.

Fabricating Inner Channels in Laser Additive Manufacturing Process via Thin-Plate-Preplacing Method.

This paper presents a hybrid manufacturing process for the preparation of complex cavity structure parts with high surface quality. Firstly, laser precision packaging technology is utilized to accurately connect a thin plate to a substrate with microchannel. Secondly, Direct Metal Laser-Sintering (DMLS) technology is utilized to completely shape the part. The morphology and microstructure of laser encapsulated specimens and DMLS molded parts were investigated. The results show that the thin plate and the substrate can form a good metallurgical bond. The lowest surface roughness of the DMLS molded parts was 1.18 μm. The perpendicularity between the top of the microchannel and the side wall was optimal when the laser power was 240 W. Consequently, the hybrid manufacturing process effectively solves the problems of poor surface quality and powder sticking of closed inner cavities. The method effectively eliminates the defects of adhesive powder in the inner cavity of the DMLS microchannel, improves the finish, and solves the problem that mechanical tools cannot be processed inside the microchannel, which lays the foundation for the research of DMLS high-quality microchannel process.

Microstructure and mechanical properties of 2319 aluminum alloy deposited by laser and cold metal transfer hybrid additive manufacturing

Wire and arc additively manufactured aluminum alloys are prone to porosity, leading to poor mechanical properties in samples, which hinders their broad industrial application. Laser and arc hybrid processes have garnered increasing attention for their potential to reduce porosity, stabilize the arc, and enhance deposition efficiency. This paper investigates the porosity, element distribution, microstructure evolution, and mechanical properties of 2319 aluminum alloy produced through the laser and cold metal transfer (laser-CMT) hybrid additive manufacturing process. In comparison with the as-deposited samples, the laser-CMT hybrid process decreases porosity, enhances element distribution, mitigates Cu element segregation, and results in increased θ′′ phase precipitation. Following T6 heat treatment, the ultimate tensile strength (UTS), yield strength (YS), and elongation of the x-direction specimens from the laser-CMT hybrid process are 450.0 MPa, 318.1 MPa, and 10.0%, respectively. These values are 11.27%, 7.03%, and 36.65% higher than those of the as-deposited samples. To validate the findings, a large-scale load-carrying frame for a commercial aircraft was fabricated, demonstrating the efficacy of the process. The paper also presents a detailed analysis of the strengthening mechanism. Samples deposited using the laser-CMT method exhibit reduced porosity and excellent mechanical properties, making this process promising for a wide range of applications.

Influence of intrinsic manufacturing defects on corrosion behavior of AISI 420 stainless steel fabricated by laser powder bed fusion

In this study, 420 stainless steel (SS) was fabricated by L-PBF with specific processing parameters: 140 W laser power, 550 mm/s scanning speed, 80 μm spot size, and 50 μm layer thickness. The resulting specimens exhibited 0.42% porosity and an average size of 18 μm for Lack-of-fusion (LOF) pores, with elemental C and Cr ablation at approximately 35.9% and 18.0%, respectively. A comparative analysis between the corrosion resistance of L-PBF specimens and cast 420 SS was conducted. Despite exhibiting extraordinary mechanical properties, L-PBF specimen displayed lower corrosion resistance and failed to produce a passive region. LOF pores and elemental ablation from intrinsic laser additive manufacturing process were the primary reasons for this outcome. Two distinct corrosion mechanisms were observed in the study. The LOF pores exhibited a higher susceptibility to pitting corrosion, leading to the formation of larger pitting pits with an approximate size of 100 μm. Conversely, the LOF-free areas displayed the presence of smaller pitting nucleation, measuring < 2 μm. This observation was attributed to the ablation of C element, leading to a 28% increase in the Cr/C content. The higher Cr/C in the LOF-free areas offered enhanced protection, thus preventing the formation of larger pitting pits in these regions.

A state-of-the-art digital factory integrating digital twin for laser additive and subtractive manufacturing processes

PurposeThis study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.Design/methodology/approachThis study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.FindingsA comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.Originality/valueBased on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

Layered and subregional control strategy based on model-free adaptive iterative learning for laser additive manufacturing process

Improving stability in process and the quality of manufactured parts is critical to laser additive manufacturing (LAM). Developing appropriate control methods is essential for this purpose. Layered control approaches are commonly utilized in current research on LAM process control, with a primary focus on the pattern of layer-by-layer deposition. However, these strategies might neglect the dynamic and evolving characteristics of the process along the scanning direction. Due to the complex nature of the LAM process, such layered control approaches could be inadequate in addressing intra-layer instability, potentially resulting in metallurgical defects. To overcome these limitations, we propose a layered-and-subregional model-free adaptive iterative learning control (LS-MFAILC) method. Considering the cyclic and the layer-by-layer processing principle of LAM, we develop a subregional control strategy and integrate it with a layered control framework. In addition, the model-free adaptive iterative learning control (MFAILC) algorithm is utilized as the controller due to its ability to control complex and time-varying systems with repetitive running characteristics. In the proposed method, each target layer to be printed in process is divided into multiple non-overlapping regions along the scanning direction, and the process parameters for each region are adaptively controlled based on historical information acquired from previous layers during the process. The temperature information of the melt pool is captured and extracted using a thermal imager integrated with the printing system. Experimental results and comparison with the layered control approach demonstrate the effectiveness and superiority of our method.

Strong resistance to Zn-assisted liquid metal embrittlement of austenitic-TWIP/martensitic-HSLA multi-layered steel sheets additively manufactured by laser cladding

As a novel design idea to overcome a shortcoming of liquid metal embrittlement (LME) occurred frequently in twinning-induced plasticity (TWIP) steel, multi-layered steel (MLS) sheets consisting of austenitic TWIP and high-strength low-alloy (HSLA) steel grades have been suggested. Two- and four-time clad MLS sheets (C2 and C4) were fabricated by a powder-fed laser additive manufacturing (AM) process using HSLA powders on the TWIP surface, and the LME was investigated in various resistance-spot-welding-time stages. The C2 and C4 sheets consisted of the austenitic TWIP substrate and tempered-martensitic HSLA-clad layer, and the HSLA layer had two or four sublayers having different C and Mn contents reduced step-wise from the TWIP/HSLA interface. LME cracks formed in the C2 spot-welded for 240 or 380 ms, whereas they did not form at all in the C4 spot-welded for 380 ms. This different LME susceptibility depended mainly on the HSLA-sublayer microstructures beneath the Zn coating after their high-temperature exposure during the spot welding. Since LME cracks propagated mainly along prior austenite grain boundaries, the whole austenite existed in the austenite range played a key role in determining whether the LME cracking occurred or not. The total volume fraction of reverted austenite (appeared as fresh martensite at room temperature) and retained austenite was very high at about 68% in the C2 welded for 240 ms, thereby leading to the LME cracking. It was lower than 20% in the C4 even under the severe welding condition of 380 ms, which provided the reason for no LME cracking.

Optimizing laser additive manufacturing process for Fe-based nano-crystalline magnetic materials

Fe-based amorphous magnetic alloys offer new opportunities for magnetic sensors, actuators and magnetostrictive transducers due to their high saturation magnetostriction (λs = 20–40 ppm) compared with that of amorphous Co-based alloys (λs = −3 to −5 ppm). Due to the conventional production limitations of Fe-based glassy alloys, including dimensional limitations and poor mechanical properties, this has led to a search for novel fabrication techniques. Recently, the laser powder bed fusion (LPBF) technique has attracted attention for the production of Fe-based magnetic bulk metallic glasses (BMGs) as it provides high densification, which brings about excellent mechanical properties, and high cooling rate during the process. Optimization of process parameters in the LPBF technique have been studied using the volumetric energy input (E), which includes the major build parameters; laser power (P), scan speed (v), layer thickness (t) and hatch spacing (h). This study investigates how the major process parameters influence the physical and magnetic properties of LPBF-processed Fe-based amorphous/nanocrystalline composites ((Fe87.38Si6.85B2.54Cr2.46C0.77 (mass %)). Various process parameter combinations with P (90, 100, 120 and 150 W) and v (700, 1000 and 1300 mm/s) were applied with t of 30, 50 and 70 µm and h of 20, 30, 40, 50 and 60 µm. It was found that bulk density improves as P and t increases, v and h decreases, i.e., high E is necessary, however, 99.45% of bulk density was achieved with E of 61.22 J/mm3 (P = 150 W, v=700 mm/s, h=50 µm and t = 70 µm), which indicates the importance of understanding how parameters affect the specific materials. In addition, the magnetic properties differ significantly due to the nanocrystalline phases present in the microstructure, with their size depending on the process parameters considerably. Owing to the laser scanning nature, the microstructure evolves as molten pools (MP) and heat affected zones (HAZ) due to the high thermal gradient that occurred between laser tracks. MP form around the scans, containing α-Fe(Si) nanograins mainly, whereas HAZ generally contains Fe2B and Fe3Si nanocrystalline clusters. The size and quantities of those nanocrystallites determine the magnetic properties. With the same E (60 J/mm3), v (1000 mm/s) and t (50 µm), only changing P and h caused samples to have different saturation magnetization; 206 emu/gr (P: 90 W and h: 30 µm) and 150 emu/gr (P: 150 W and h: 50 µm). In general, the saturation magnetisation, Ms of LPBF-processed samples changes between 130 and 206 emu/gr, which is much higher than that of feedstock powder (102 emu/gr) due to their nanocrystalline structures. The coercivity (Hc) is in the range of 14.55 and 34.68 Oe, which is considered high for soft-magnetic behaviour (Hc ≤ 12.5 Oe), resulting from the larger crystallite size and the presence of defects (pores and cracks) in the microstructure.