Search Results (111)

Additive manufacturing, or 3D printing, is a method for creating three-dimensional objects layer-by-layer based on a digital model. This article presents the results of research on selective laser melting (SLM) of 316L stainless steel powder. Its aim is to investigate the relation between the mechanical properties of SLM-fabricated 316L steel samples obtained from uniaxial tensile tests and the SLM process parameters including the build-up strategy. Four different configurations of 3D printing orientation relative to the build platform were considered. The variable parameters of the SLM process were laser power and laser scanning speed. The morphology of the external surfaces and the microstructure of the SLM-processed samples were examined. The results show that samples printed in the longitudinal and transverse configurations had the highest tensile strength. Samples printed in the vertical and diagonal configurations had the greatest dispersion of values of mechanical parameters. The main difference in mechanical properties after doubling the SLM process parameters was a decrease in elongation for samples printed in the longitudinal configuration and an increase in this value for samples printed in the transverse configuration. The use of higher laser powers and laser scanning speeds guarantees a more compact, non-porous microstructure of SLM-processed samples. Full article

This paper is the first to reveal that the conventionally built aluminium alloy (AA) 7085-T7452 has mechanical properties, viz: a yield stress, ultimate strength, and an elongation to failure, that are similar to that of laser powder bed fusion (LPBF) built Scalmalloy^®. Following this observation, the growth of cracks that nucleated from corrosion pits in AA7085-T7452 specimens that had been exposed to a 5 wt% NaCl salt fog environment at 35 °C according to ASTM B117-19 standard for fourteen days is then studied. The specimen geometries were chosen to be identical to those associated with a similar study on Boeing Space, Intelligence, and Weapon Systems (BSI&WS) LPBF built Scalmalloy^®. This level of prior exposure led to pits in AA7085-T7452 that were approximately 0.5 mm deep with a surface width/diameter of up to approximately 1.5 mm. These pit sizes are broadly consistent with those leading to fatigue crack growth (FCG) in AA 7050-T7451 structural parts on the RAAF F/A-18 Classic Hornet fleet operating in a highly corrosive environment. Fatigue tests on these AA7085-T7452 specimens, under the same spectrum as used in the BSI&WS LPBF Scalmalloy^® study, reveals that AA7085-T7452 and Scalmalloy^® have similar crack growth histories. This, in turn, leads to the discovery that the growth of naturally occurring three-dimensional (3D) cracks in AA 7085-T7452 could be predicted using the crack growth equation developed for BSI&WS LPBF Scalmalloy^®, albeit with allowance made for their different fracture toughness’s. These findings suggest that Scalmalloy^® may be suitable for printing parts for both current and future attritable aircraft. Full article

In this study, an analytical model was developed to evaluate the influence of laser powder bed fusion (LPBF) process parameters on process-induced porosity during the 3D printing of stainless steel 316L. First, the temperature distribution, governed by a moving point heat source model of the laser, was used to predict the melt pool geometry during the melting stage. This prediction was then refined to account for the formation of the solidified cap. By analyzing the interaction between melt pool size and other process parameters, such as hatch spacing and layer thickness, criteria were established to distinguish between porosity caused by lack of fusion, porosity due to keyhole formation, and defect-free samples. A series of experiments were conducted, and porosity was measured using micro-CT analysis. The results showed that the porosity predicted by the model remained within an acceptable error range compared with the experimental measurements, with errors ranging from 10.5% to 24.78% and a mean error of 16.48%, demonstrating the accuracy of the developed model. Full article

In this paper, the effects of 3D printing parameters on the metallurgical and mechanical properties of 3D-printed 25CrMo4 steel are presented. Using laser-based powder bed fusion of metals (PBF-LB/M), samples were fabricated under varying conditions of laser power, scan speed, and layer thickness. The study examined how variations in volumetric energy density (VED) and linear energy density (LED) influence the material’s performance. The results show a strong correlation between the printing parameters and key properties such as hardness, porosity, bending strength, compressive strength, and tensile strength. Appropriate VED and LED improved density, reduced defects, and enhanced mechanical performance, whereas excessive energy inputs introduced brittleness. These findings support the advancement of additive manufacturing technologies for high-strength steels and broaden their potential applications in the aerospace, automotive, and construction sectors. Full article

Over the last decade, laser powder bed fusion (LPBF) received increased attention as a method of producing complex-shaped products from various materials. Recent results indicate the potential of this technology for the production of intermetallic NiTi alloys with shape memory. Several studies have demonstrated a strong influence of the LPBF process conditions on the resulting material properties, i.e., the martensitic phase transformation temperatures, reversible/irreversible strain after cyclic loading, phase composition, chemical composition, etc. However, the mechanisms of functional properties altering during LPBF consolidation remain unexplored in the present state-of-the-art. This study aims to advance the knowledge about tailoring material properties of NiTi under laser influence. In this work, thin-walled samples were manufactured from pre-alloyed NiTi powder via LPBF in a wide window of laser power and scanning speed, excluding hatch spacing by employing a single track-based scanning strategy to reveal the pure effect of the laser’s influence. NiTi samples were characterized by various methods such as differential scanning calorimetry, X-ray diffraction, and mechanical tests. Established relationships between NiTi properties and the LPBF process conditions provide the basis for the development of NiTi production protocols with controlled functional properties. Full article

In situ process monitoring systems (IPMSs) are rapidly gaining importance in quality assurance of laser powder bed fusion (L-PBF) parts, yet standardized methods for their objective evaluation are lacking. This study introduces a novel, system-independent assessment method for IPMSs based on a specially designed Energy Step Cube (ESC) test specimen. The ESC enables systematic variation in volumetric energy density (VED) by adjusting laser scan speed, without disclosing complete process parameters. Two industrially relevant IPMSs—PrintRite3D by Divergent and Trumpf’s integrated system—were evaluated using the ESC approach with AlSi10Mg as the test material. System performance was assessed based on sensitivity to VED changes and correlation with actual porosity, determined by metallographic analysis. Results revealed significant differences in sensitivity and effective observation windows between the systems. PrintRite3D demonstrated higher sensitivity to small VED changes, while the Trumpf system showed a broader stable observation range. The study highlights the challenges in establishing relationships between IPMS signals and resulting part properties, currently restricting their standalone use for quality assurance. This work establishes a foundation for standardized IPMS evaluation in additive manufacturing, offering valuable insights for technology advancement and enabling objective comparisons between various IPMSs, thereby promoting innovation in this field. Full article

Companies are increasingly turning to additive manufacturing as the demand for one-off 3D-printed metal parts rises. The differences in available additive manufacturing technologies necessitate considering both cost and externalities to select the most suitable alternative. This study compares some of the most prevalent metal additive manufacturing technologies through a shop floor-level operational analysis. A steel robotic gripper is considered as a case study, based on which of the complex, interconnected operational factors that influence costs over time are analyzed. The developed cost model facilitates the estimation of costs, identification of cost drivers, and analysis of the impact of various operations management decisions on overall costs. We found that cost performance across Powder-Bed Fusion (PBF), Wire Arc Additive Manufacturing (WAAM), and CNC machining is determined by part design, quantity, and machine utilization. Although producing parts with complex internal features favors additive manufacturing, CNC outperforms in terms of economy of scale. While PBF offers excellent design freedom and parallel production, it incurs high fixed costs per build in under-utilized situations. A rough but fast method, such as Directed-Energy Deposition (DED)-based additive manufacturing, is believed to be more cost-efficient for large, simple shapes, but is not suitable when fine details are required. Laser-based DED approaches address this limitation of WAAM. Full article

This study introduces the Gyroid structure, a type of triply periodic minimal surface (TPMS), for enhanced effusion cooling performance. Conjugate heat transfer simulations are used to compare the flow behavior, pressure loss, and overall cooling effectiveness of single- and double-wall Gyroid configurations against a baseline film hole model at blowing ratios of 0.5–2.0. Results show that the Gyroid design eliminates jet lift-off and counter-rotating vortex pairs, ensuring full coolant coverage and a thicker coolant layer than the baseline. The double-wall configuration further improves cooling with jet impingement, yielding higher average Nusselt numbers than the single-wall design. At equal pressure loss, the impingement/Gyroid model outperforms the baseline by 102.7% in cooling effectiveness. To assess manufacturability, a high-resolution CT scan is used to validate a laser powder bed fusion-printed Gyroid sample at gas turbine blade scale, confirming feasibility for industrial application. These findings highlight the superior thermal performance and manufacturability of the 3D-printed Gyroid structure, offering a promising cooling solution for next-generation turbine blades. Full article

Two ways of anodizing 3D-printed AlSi10Mg alloy were characterized, and then their fatigue properties were evaluated. Test specimens were fabricated via a laser-powder bed fusion (L-PBF) process followed by machining. Normal and hard anodizing were both conducted in a sulfuric acid bath. The anodized layer was observed using FE-SEM/EDS. Fine Si particles dispersed in the matrix showing web-like patterns were incorporated in the anodized layer. By etching the Si particles away with Keller’s reagent, a characteristic maze-like 3D structure of anodized Al was observed. Then, rotating bending fatigue tests were carried out to evaluate the fatigue strength at 10⁷ cycles. The fatigue strength of the as-machined, normal-anodized and hard-anodized specimens was 106, 100 and 95 MPa, respectively. The fatigue limits were proportional to the surface roughness with higher linearity. By reducing the surface roughness, the fatigue strength of the hard-anodized specimen was improved. This result demonstrates the possibility of improving the fatigue properties of anodized components by reducing their surface roughness. Lastly, a CASS (copper-accelerated acetic acid salt spray) test was conducted, and superior corrosion resistance of the normal- and hard-anodized layers was verified. Full article

Laser Powder Bed Fusion (LPBF) has emerged as a leading additive manufacturing (AM) process for producing complex metal components. Despite its advantages, the inherent LPBF process complexity leads to challenges in achieving consistent quality and repeatability. To address these concerns, recent research efforts have focused on sensor fusion techniques for process monitoring, and on developing more elaborate control strategies. Sensor fusion combines information from multiple in situ sensors to provide more comprehensive insights into process characteristics such as melt pool behavior, spatter formation, and layer integrity. By leveraging multimodal data sources, sensor fusion enhances the detection and diagnosis of process anomalies in real-time. Closed-loop control systems may utilize this fused information to adjust key process parameters–such as laser power, focal depth, and scanning speed–to mitigate defect formation during the build process. This review focuses on the current state-of-the-art in sensor fusion monitoring and control strategies for LPBF. In terms of sensor fusion, recent advances extend beyond CNN-based approaches to include graph-based, attention, and transformer architectures. Among these, feature-level integration has shown the best balance between accuracy and computational cost. However, the limited volume of available experimental data, class-imbalance issues and lack of standardization still hinder further progress. In terms of control, a trend away from purely physics-based towards Machine Learning (ML)-assisted and hybrid strategies can be observed. These strategies show promise for more adaptive and effective quality enhancement. The biggest challenge is the broader validation on more complex part geometries and under realistic conditions using commercial LPBF systems. Full article

Research and development in the field of glass-based laser additive manufacturing continues to receive significant interest within scientific and industrial contexts. In particular, powder bed fusion by laser radiation (PBF-LB) enables the additive manufacturing of porous and vitrified, complex three-dimensional components. The present study investigates the glass morphology that can be achieved using PBF-LB for components made from alkali borosilicate glass. The investigations focus on the comprehensive analysis of the entire process window, including the characterisation of porous and molten glass morphology. In particular, the influence of different laser-beam diameters, which are achieved through defocusing, and the variation in volume energy density are examined in detail and compared with conventional shaping. It was determined that the process of mechanically stable shaping is constrained to temperatures above the softening temperature and relative component densities within the range of ρrel = 37.8…94.2%. Furthermore, it has been demonstrated that the process-related line-like energy input results in the formation of characteristic vitrification strands. This research contributes to the overall understanding of the producible glass morphology and the process limitations of the PBF-LB process. In addition, the entire range of glass morphologies, ranging from open-pored to closed-melt configurations, could be analysed for the first time. Full article

This work presents a multiscale, microstructure-aware framework for predicting fatigue strength distributions in additively manufactured (AM) alloys—specifically, laser powder bed fusion (L-PBF) AlSi10Mg and Ti-6Al-4V—by integrating density functional theory (DFT), instrumented indentation, and Bayesian inference. The methodology leverages principles common to all 3D printing (additive manufacturing) processes: layer-wise material deposition, process-induced defect formation (such as porosity and residual stress), and microstructural tailoring through parameter control, which collectively differentiate AM from conventional manufacturing. By linking DFT-derived cohesive energies with indentation-based modulus measurements and a MAP-based statistical model, we quantify the effect of additive-manufactured microstructural heterogeneity on fatigue performance. Quantitative validation demonstrates that the predicted fatigue strength distributions agree with experimental high-cycle and very-high-cycle fatigue (HCF/VHCF) data, with posterior modes and 95 % credible intervals of ${\widehat{\sigma }}_f^{\mathrm{AlSi}10\mathrm{Mg}}={86}_{-7}^{+8}\mathrm{MPa}$ and ${\widehat{\sigma }}_f^{\mathrm{Ti}–6\mathrm{Al}–4\mathrm{V}}={115}_{-9}^{+10}\mathrm{MPa}$, respectively. The resulting Woehler (S–N) curves and Paris crack-growth parameters envelop more than 92 % of the measured coupon data, confirming both accuracy and robustness. Furthermore, global sensitivity analysis reveals that volumetric porosity and residual stress account for over 70 % of the fatigue strength variance, highlighting the central role of process–structure relationships unique to AM. The presented framework thus provides a predictive, physically interpretable, and data-efficient pathway for microstructure-informed fatigue design in additively manufactured metals, and is readily extensible to other AM alloys and process variants. Full article

Additive manufacturing is one of the foundational pillars of Industry 4.0, which is rooted in the integration of intelligent digital technologies, manufacturing, and industrial processes. Machine learning techniques are resources used to support Design for Additive Manufacturing, particularly in design phases and process analysis. Neural Networks are suited to manage complex and non-linear datasets. The article proposes a methodology for the time and cost assessment of the Laser-Powder Bed Fusion 3D printing process using a Neural Network-based approach. The methodology analyzes the main geometrical features of STL files to train Neural Network Machine Learning models. The methodology has been tested on a preliminary dataset that includes a set of parametric CAD models and their corresponding Additive Manufacturing simulations. The trained models achieve an R² value greater than 0.97. A web-service platform has been implemented to provide a valuable tool for users, transforming a research-grade model into a production-grade online endpoint. Full article

This study focuses on the energy absorption and wearer comfort attributes of regular lattice structures fabricated by laser powder bed fusion from two elastomeric materials, namely TPU1301 and TPE300, for use in personal protective equipment (PPE). This study compares Body-Centered Cubic (BCC), Face-Centered Cubic (FCC) and Kelvin (KE) lattice structures with density varying from 0.15 to 0.25 g/cm³, cell size varying from 10 to 14 mm and feature size varying from 1 to 3 mm. Quasi-static and dynamic compression testing confirmed that among the studied geometries, KE structures printed with TPE300 powders provide the best combination of reduced peak acceleration and increased compliance, thereby improving both safety and comfort. Using the protection–comfort maps built on the basis of this study enables the design of lightweight and compact protective structures. For example, if a safety layer protecting a 100 mm² surface area can be manufactured from either TPE300 or TPU1100 powders using either KE or FCC structures, the KE TPE300 layer will be 1.5 times thinner and 2.5 times lighter than its FCC TPU1301 equivalent. The results of this study thus provide a basis for the optimization of lattice structures in 3D-printed PPE to meet both service and manufacturing requirements. Full article

In recent years, significant effort was made to make the 3D printing of fully dense rare-earth permanent magnets a reality. Since suitable Nd₂Fe₁₄B-based initial powder material became available, additive manufacturing implementation spread widely, which led to many studies being focused on using this material in 3D printing. This study shows the principal possibilities of the synthesis of Nd-Fe-B magnets by means of the laser powder bed fusion technique; moreover, this study shows significant progress in increasing their magnetic properties. This progress was made possible by different approaches, such as 3D-printing process optimization, the addition of a second phase (a low-melting eutectic) into the initial powder, the tuning of the main phase’s composition, and exploring different scanning strategies. However, the current level of material magnetic properties obtained via laser powder bed fusion is still far from that of magnets produced by using conventional powder metallurgy methods. The present review aims to capture the current state-of-the-art trials and highlight the main challenges. Full article