Metal Additive Manufacturing Technology Research Articles

Enabling the design of surgical instruments for under-resourced patients through metal additive manufacturing: ulnar shortening osteotomy as an example

BackgroundUlnar shortening osteotomy (USO) has demonstrated good outcomes for patients with ulnar impaction syndrome. To minimize complications such as non-union, precise osteotomy and firm fixation are warranted. Despite various ulnar shortening systems have been developed, current technology does not meet all needs. A considerable portion of patients could not afford those designated USO systems. To tackle this challenge, our team reported successful results in standardized free-hand predrilled USO technique. However, it is still technical demanding and requires sufficient experience and confidence to excel. Therefore, our team designed an ulnar shortening system based on our free-hand technique principle, using metal additive manufacturing technology. The goal of this study is to describe the development process and report the performance of the system.MethodsUtilizing metal additive manufacturing technology, our team developed an ulnar shortening system that requires minimal exposure, facilitates precise cutting, and allows for the easy placement of a 3.5 mm dynamic compression plate, available to patients at zero out-of-pocket cost. For performance testing, two surgeons with different levels of experience in ulnar shortening procedures were included: one fellow-trained hand and wrist surgeon and one senior resident. They performed ulnar shortening osteotomy (USO) using both the free-hand technique and the USO system-assisted technique on ulna sawbones, repeating each method three times. The recorded parameters included time-to-complete-osteotomy, total procedure time, chip diameter, shortening length, maximum residual gap, and deviation angle.ResultsFor the hand and wrist fellow, with the USO system, the time-to-complete osteotomy was significantly reduced. (468.7 ± 63.6 to 260.0 ± 5 s, p < 0.05). Despite the preop goal was shortening 3 mm, the average shortening length was significantly larger in the free-hand group (5 ± 0.1; 3.2 ± 0.2 mm, p < 0.05). Both maximum residual gap and deviation angle reported no statistical difference between the two techniques for the hand surgeon. As for the senior resident, the maximum residual gap was significantly reduced, using the USO system (2.9 ± 0.8; 0.4 ± 0.4 mm, p = 0.02). Between two surgeons, significant larger maximum residual gap and deviation angle were noted on the senior resident doctor, in the free-hand technique group, but not in the USO system group.ConclusionThe developed USO system may serve as a valuable tool, aiding in reliable and precise cutting as well as fixation for patients undergoing ulnar shortening osteotomy with a 3.5 mm dynamic compression plate, even for less experienced surgeons. The entire process, from concept generation and sketching to creating the CAD file and final production, serves as a translatable reference for other surgical scenarios.

A surface quality optimization strategy based on a dedicated melt-pool control via the dashed-scan contouring technique in electron beam powder bed fusion

Electron beam powder bed fusion (EB-PBF) is a key metal additive manufacturing (AM) technology known for its high energy absorption and low heat stress. However, the high surface roughness of EB-PBF parts has limited its broader application. To address this issue, this paper proposes a dashed-scan contouring strategy to obtain lower surface roughness in EB-PBF. This strategy involves melting the contour in the form of segmented staggered scans and employing high-frequency jumping of the electron beam (EB) to melt multiple positions synchronously. A comprehensive analysis, combining experimental investigations and multi-physical simulations, elucidates the intrinsic connection between control processes and melt pool stability. Results show that by controlling the length-to-width ratio of the melt pool, regulating overlap distances between melt pools, and fine-tuning cooling times, balling phenomena and Plateau-Rayleigh instabilities can be suppressed. Additionally, these measures effectively mitigate irregularities in track formation when compared to the traditional process. Experimental validation demonstrates the efficacy of the approach, achieving reduced surface roughness (Ra) of thin-walled Ti-6Al-4 V parts from over 25 μm to below 12.6 μm, while enhancing dimensional accuracy and reducing melt anomalies at corners. The proposed dashed-scan contouring strategy opens new avenues for AM of highly reliable and intricate structures, such as lattice sandwich structures, thin walls, and internal flow passages.

Numerical analysis of machinability and surface alterations in cryogenic machining of additively manufactured Ti6Al4V alloy

Metal additive manufacturing (AM) technology has been utilized in many industries including automotive, aerospace, and medical. AM Ti6Al4V (Ti64) alloy is highly noticed for production of medical instruments such as dental implants and the machining process is mostly needed during the production or post-processing of these components. Numerical model, as a powerful tool, can be efficiently used for analyzing the machining process. A customized model was employed using a user-written subroutine in this work to evaluate machinability and microstructural changes in cryogenic machining of AM Ti64 alloy. For this purpose, the microstructural changes were simulated as the new numerical outputs. The numerical results of cutting forces, temperature, nano-hardness, and alpha lamellae thickness (grain size) were successfully verified by corresponding experiments from literature. Then, the impact of tool geometry (including rake and clearance angles, cutting edge radius, and nose radius) on the machinability performance was examined. It was found that, the variation of clearance and rake angles were more effective on depth of the hardened layer compared to the other parameters. Thickness of alpha lamellae phase near the machined surface and depth of the affected layer by nano-hardness changes were changed from 0.9 to 1.58 µm, and from 18 to 40 µm, respectively. Overall, it was concluded that the variation of insert positioning made by tool holder (change in rake and clearance angles) was an effective parameter on the process outputs when machining AM Ti64 alloy.

Effects of process parameters and geometry on dimensional accuracy and surface quality of thin strut heart valve frames manufactured by laser powder bed fusion

AbstractLaser powder bed fusion (LPBF) is one of the most popular metal additive manufacturing technologies, which has found its applications in high-value sectors such as aerospace and biomedical devices. Some recent studies on the LPBF of stents have demonstrated its feasibility in the fabrication in thin strut structures including heart valve frames, as used in transcatheter aortic valve implantation (TAVI) for the treatment of severe aortic stenosis. The state of the art method of laser cutting TAVI frame limits the scope for novel concepts which are made possible by additive manufacturing. However, the surface quality and dimensional accuracy of LPBF parts are lower than that produced by laser cutting. To start the development of new TAVI concepts, the feasibility of manufacturing thin frames by LPBF has been investigated based on the SAPIEN 3 frame by Edwards Lifesciences. In this study, simplified frames with strut size from 0.3 to 0.5 mm have been successfully manufactured. The effects of strut size, strut angle, laser power and scan speed on the dimensional accuracy and surface quality were systemically studied. In addition, a representative SAPIEN 3 frame was manufactured and assessed with high-resolution X-ray CT scans. Good overall dimensional accuracy and low porosity were obtained for the SAPIEN 3 frame. However, inclined struts were found to have relatively low dimensional accuracy and poor surface quality.

Designing materials by laser powder bed fusion with machine learning-driven bi-objective optimization

To exploit the full industrial potential of additive manufacturing (AM) beyond prototyping, the resource-consuming identification of the optimal processing conditions needs to be minimized. This task becomes more challenging when multiple properties of the part shall be simultaneously optimized. We utilize machine learning (ML) methods in a case study on laser powder bed fusion (LPBF) of a Zr-based glass-forming alloy. Our experiments show that processing parameters affect density and amorphicity opposingly, demonstrating the efficacy of our ML-based approach. We employ multi-objective optimization using Gaussian Process Regression to model and predict target properties and their uncertainties of parts fabricated by LPBF – a widely used metal AM technology. With density and amorphicity as target parameters, we optimize models using the Pareto front facilitated by the Non-Dominated Sorting Genetic Algorithm II. Despite deviations in the amorphicity data, we demonstrate this method to identify the high-performance region of the process parameters and its ability to be iteratively enhanced with additional experimental data. This bi-objective optimization approach provides a robust toolset for navigating LPBF processing. It can be easily extended to a larger set of target properties and transferred to further AM technologies.

High precision detection of artificial defects in additively manufactured Ti6Al4V alloy via laser ultrasonic testing

Laser powder bed fusion (LPBF) is a cutting-edge metal additive manufacturing technology with promising applications in aerospace, biomedicine, and industrial automation. Its ability to fabricate intricate geometric shapes, achieve high surface precision, and deliver comprehensive results renders it highly advantageous. In LPBF process, several factors such as the interference of laser processing fluctuations, rapid cooling rate, and environmental gas, contribute to the initiation and expansion of defects including pores and cracks, limiting the application of LPBF components. Laser ultrasonic testing (LUT) is a promising non-destructive evaluation method that can accurately detected defects in LPBF manufactured components by non-contact generation and detection. In this paper, a multi-physical field LUT model for the pores and cracks in LPBF additively manufactured Ti6Al4V alloy is proposed. The interaction of ultrasound with defects produces defect reflection echo wave, diffracted wave, and transmission wave. The transmission and diffraction phenomena occur in the longitudinal sound waves at defects. Furthermore, the echo wave reflected at crack exhibited enhanced prominence and an irregular shape. Clear differences were observed in the effects of laser ultrasonic detection on different defect types, pore depths and sizes. Finally, the LUT technology achieved the detection of 90 μm pore defects in LPBF manufactured Ti6Al4V alloy.

Numerical Simulation of the Evaporation Behavior of Fe-Mn Heterogeneous Powder in Selective Laser Melting Process.

Multi-material additive manufacturing using heterogeneous powders as raw materials is one of the important development directions of metal additive manufacturing technology. The evaporation behavior of heterogeneous powders in the selective laser melting (SLM) process has a significant influence on the accuracy of chemical composition control and the quality of the final product. In this paper, the fusion process of Fe20Mn (80 wt.% Fe and 20 wt.% Mn) heterogeneous powder, Fe and Mn elemental powders, and Fe20Mn pre-alloyed powder is numerically simulated using FLOW-3D® software and partially validated through SLM experimental results. The morphology and the characteristics of the flow field and temperature field in the melt pool for four kinds of powder materials are analyzed. The influence of the elemental evaporation behavior of different powders on the mass loss of the Mn element is discussed. The results show that the excessive accumulation of heat increases the maximum temperature of the melt pool, thus increasing mass loss. The Fe20Mn heterogeneous powder has a wider heat-affected zone and a higher peak value of temperature, nearly 400 K higher than that of the Fe20Mn pre-alloyed powders, which exhibits an intensive evaporation behavior. The mass loss of the Mn element obtained from the SLM experiment for Fe20Mn heterogeneous powders forming parts is more than the Fe20Mn pre-alloyed powders' forming parts for different laser powers, up to 17 wt.% at P = 120 W. This tendency is consistent with the numerical analysis of the effect of evaporation behavior of Fe-Mn heterogeneous powder during the SLM process. This study provides the necessary theoretical reference and process guidance for realizing the precise control of the SLM composition of a heterogeneous powder in multi-material additive manufacturing caused by evaporation behavior.

Melting ceramic Al2O3 powder by electron beam powder bed fusion

AbstractElectron beam powder bed fusion (PBF-EB) is a known metal additive manufacturing (AM) technology. Processing non-conducting powders such as ceramics has so far been considered as not feasible because of the inherent problems with Coulomb repulsion due to insufficient electrical conductivity. In this study, a method for functionalizing ceramic powder is proposed where particles are electroless coated by a ~ 1 µm Ni layer to decrease the surface resistivity. The feasibility of the suggested approach is tested on Al2O3 powder, and the results show that the coated ceramic powder has a decreased surface resistivity, which enables processing by PBF-EB. Heating and melting parameters were investigated and samples were manufactured at ~ 1600 °C. Sintered and melted powders were analyzed by microscopy and micromechanically tested by nanoindentation. Calculations, visual observation and SEM–EDX suggest that the Ni coating is evaporated during the process, which suggests that the process could be feasible for the manufacturing of pure ceramic parts.

디지털 적층 제조 장비의 사용자 중심 HMI 디자인 가이드 제안

With the advancement of metal additive manufacturing technology and the digitization of equipment, the need for user-centered design in HMI (Human-Machine Interface) has become increasingly apparent. However, research on design guides and usability test for industrial equipment has been lacking. Therefore, this study applied user-centered design principles to design and manufacture a prototype HMI for metal additive manufacturing equipment, followed by a usability test of the HMI prototype. Based on usability testing and in-depth interview analysis, this study proposes UX/UI design guidelines for user-centered industrial equipment HMI. The usability evaluation highlighted the need to improve the visibility of the system's real-time status, enhance interface intuitiveness for error prevention, and address emergency situations. It is crucial that the interface reflects both the visible and invisible states of the equipment, considering that the operation targets are mechanical equipment but the operating devices are HMI screens. Furthermore, for industrial equipment with numerous complex functions, it is essential to restrict or guide user actions through permission settings. Through the industrial PBF (Powder Bed Fusion) method metal additive manufacturing equipment HMI design guides proposed by this study, we anticipate the development of user-friendly and productivity-enhancing HMI designs.

Reuse of Smoulder in Laser Powder-Bed Fusion of AlSi10Mg—Powder Characterization and Sample Analysis

Metal additive manufacturing technologies, such as Laser Powder-Bed Fusion, often rate as sustainable due to their high material efficiency. However, there are several drawbacks that reduce the overall sustainability and offer potential for improvement. One such drawback is waste emerging from the process. These smoulder particles form when the laser hits the powder-bed surface, are blown away from the part by the shielding gas stream and accumulate on the edge of the build chamber. Usually, smoulder does not contribute to the circular reuse of powder that was part of the powder-bed but was not integrated into a part. Instead, it marks an end-of-life state of powder. Significant amounts of smoulder accumulate depending on the irradiated area or the build volume in one job, respectively. This results in the waste of powder that was produced with low energy efficiency. This study investigates the question of whether smoulder can transform from waste to resource via common powder characterization methods and first build jobs using processed smoulder. The investigation of process-relevant powder properties like apparent density and flowability showed no significant difference between virgin powder and smoulder. Sample characterization indicated that neither porosity, surface quality nor mechanical properties deteriorate when samples contain about 50% smoulder. This allows for the reuse of smoulder in terms of powder characterization and part quality.

GUIDELINES FOR AUTOMOTIVE COMPONENT REPAIR USING ADDITIVE MANUFACTURING IN INDUSTRY 4.0: DESIGN AND PROCESS PERSPECTIVE

The advancement of Industry 4.0 technology requires industries to continuously compete in applying these technologies practically within existing processes. The remanufacturing process as one of the recovery approaches under Circular Economy strategy, is currently thriving on improvement by leveraging Industry 4.0 technology. The application of automated repair through additive manufacturing (AM) is one such opportunity to enhance remanufacturing capabilities with a variety of design options and alternative repair methods. However, AM’s potential as a repair option will be hindered due to challenges in terms of the geometric complexities, process requirements, material compatibilities and process accuracy. Hence, this study focuses on the development of guideline for repair of automotive component through AM process. The development of guideline is crucial to provide newly information and steps involved when conducting the repair using AM technology. The study is mainly focusing on remanufacturable of piston part in a crankshaft component as the case exemplary and Powder Based Fusion (PBF) of metal AM technology is used for verification purposes through experimental works. In overall, this study provides a design guideline involving repair process by using the AM process. The guideline would be useful for the designers, industries and remanufacturers to enhance the implementation of repair and remanufacturing process by adopting AM technology.

Investigation on the elastic flexural stiffness of dot-by-dot wire-and-arc additively manufactured stainless steel bars

Among different metal additive manufacturing (AM) technologies, arc-based Directed Energy Deposition, also known as Wire-and-Arc Additive Manufacturing (WAAM), is considered the most suitable for large-scale structural components production. In particular, the WAAM printing strategy referred to as “dot-by-dot” allows the realization of complex 3D lattice forms at the scale of structural steel parts, composed of unitary cells made of slender bars. Nonetheless, the outcomes of this process are still to be properly investigated in terms of their mechanical behavior under various loading conditions. To assess the buckling behavior of WAAM-produced slender bars, extensive effort is requested to properly characterize the main driving aspects, namely the flexural stiffness possibly influenced by mechanical anisotropy induced by the printing process and the influence of the geometrical imperfections. The present work reports the first results of experimental bending tests conducted on vertically printed (i.e. with a fixed build angle equal to 0°) straight dot-by-dot WAAM stainless steel bars, as an initial investigation towards a more comprehensive analysis of the buckling behavior of WAAM slender elements. The results are then interpreted by introducing three approaches of increasing complexity, including two analytical approaches based on a simplified idealization of the real geometry of the bar, and a third approach based on the reconstruction of the real geometry of the bar using advanced numerical simulations and 3D scanning. The three approaches lead to a different appraisal of the influence of the geometrical irregularities on the flexural stiffness of the specimens. The main results of the present study could be utilized to interpret the results of future experimental compressive tests on WAAM slender elements and to develop ad-hoc buckling curves for structural design purposes.

Cryogenic Tensile Behavior of Ferrous Medium-entropy Alloy Additively Manufactured by Laser Powder Bed Fusion

The emergence of ferrous-medium entropy alloys (FeMEAs) with excellent tensile properties represents a potential direction for designing alloys based on metastable engineering. In this study, an FeMEA is successfully fabricated using laser powder bed fusion (LPBF), a metal additive manufacturing technology. Tensile tests are conducted on the LPBF-processed FeMEA at room temperature and cryogenic temperatures (77 K). At 77 K, the LPBF-processed FeMEA exhibits high yield strength and excellent ultimate tensile strength through active deformation-induced martensitic transformation. Furthermore, due to the low stability of the face-centered cubic (FCC) phase of the LPBF-processed FeMEA based on nano-scale solute heterogeneity, stress-induced martensitic transformation occurs, accompanied by the appearance of a yield point phenomenon during cryogenic tensile deformation. This study elucidates the origin of the yield point phenomenon and deformation behavior of the FeMEA at 77 K.

Comparison of CFD-DEM and MP-PIC in the Simulation of Metal Powder Conveying for Laser Metal Deposition

Pneumatic conveying of fine powders is essential for many industrial processes, including Laser Metal Deposition (LMD), a Direct Metal Additive Manufacturing (DMAM) technology that builds solid objects layer-by-layer using a laser to melt metal powder. To optimize the process, it is necessary to have a correct understanding of the powder’s behaviour under the process condition. The coupled Computational Fluid Dynamics - Discrete Element Modelling (CFD-DEM) and MultiPhase - Particle In Cell (MP-PIC) are two popular Eulerian-Lagrangian models to simulate particle laden flows. This study compares them to analyse powder behaviour in a small channel of LMD machines. Results from the two methods differ significantly, with CFD-DEM offering a more accurate representation of the physical reality, while MP-PIC is more computationally efficient. The study finds that the CFD-DEM method produces higher fluctuations in the solids flow rate due to the formation of particle clusters, while MP-PIC displays a smooth and essentially uniform flow. The results suggest that CFD-DEM should be used for more accurate and detailed studies of solids flow rate in pneumatic conveying systems, while MP-PIC can be used for preliminary studies and design optimization.

PBF-LB fabrication of microgrooves for induction of osteogenic differentiation of human mesenchymal stem cells

Stem cell differentiation has important implications for biomedical device design and tissue engineering. Recently, inherent material properties, including surface chemistry, stiffness, and topography, have been found to influence stem cell fate. Among these, surface topography is a key regulator of stem cells in contact with materials. The most important aspect of ideal bone tissue engineering is to control the organization of the bone extracellular matrix with fully differentiated osteoblasts. Here, we found that laser powder bed fusion (PBF-LB)-fabricated grooved surface inspired by the microstructure of bone, which induced human mesenchymal stem cell (hMSC) differentiation into the osteogenic lineage without any differentiation supplements. The periodic grooved structure was fabricated by PBF-LB which induced cell elongation facilitated by cytoskeletal tension along the grooves. This resulted in the upregulation of osteogenesis via Runx2 expression. The aligned hMSCs successfully differentiated into osteoblasts and further organized the bone mimetic-oriented extracellular matrix microstructure. Our results indicate that metal additive manufacturing technology has a great advantage in controlling stem cell fate into the osteogenic lineage, and in the construction of bone-mimetic microstructural organization. Our findings on material-induced stem cell differentiation under standard cell culture conditions open new avenues for the development of medical devices that realize the desired tissue regeneration mediated by regulated stem cell functions.

Development of 1D-convolutional Neural Network-based Height Profile Prediction Model in Directed Energy Deposition Process Using Melt-pool Image Data

Directed energy deposition (DED) process is a representative metal additive manufacturing technology that uses a flexible deposition head mainly used for repairs in space and marine industries. The DED process saves time and money as it repairs only damaged parts and components. Therefore, a geometric control is important to fill the volume of the target damaged area economically and accurately. However, efficiency depends on process parameters such as laser power, scanning speed. This study proposes a one-dimensional convolutional neural network (1D-CNN) model to predict the height profile of the DED parts utilizing melt-pool image data. First, DED experiments were performed for a total of nine cases considering laser power and scanning speed as parameters. The collected melt-pool image data was pre-processed and only those related to the regions of interest were extracted. Initially, a total of 15 features were extracted from size, shape, location, and brightness from the melt-pool images. Then, 10 critical ones, selected through a permutation feature importance evaluation method, were input to the 1D-CNN algorithm to predict height profiles of the deposited layers. In testing phase, a mean absolute percentage error (MAPE) of 9.55% was achieved, and thus, applicability of the proposed model was verified.

Solid-State VS. Fusion-Based Metal Additive Manufacturing Technologies

Metal eklemeli imalat (MEİ) süreçleri sektörde hala alışılmışın dışında görülüyor ve seri üretimden ziyade niş uygulamalar için değerlendiriliyor. Sektörde süreç seçiminde en önemli belirleyici unsurlar üretim süresi ve birim maliyettir. Döküm, metal şekillendirme ve talaşlı imalat süreçlerinin çoğu, düşük ve orta maliyetli seri üretim için olgunlaştırılmış ve optimize edilmiştir; ancak imalatın büyük bir kısmı özelleştirmeyi içermektedir ve MEİ süreçlerinin geleneksel imalata iyi bir alternatif olabileceği tek veya çok küçük adetlerde üretilen birçok ürün de mevcuttur. MEİ'in güçlü ve zayıf yönlerini anlamak, teknik ve ekonomik açıdan en uygun seçeneğin seçilmesinde kritik öneme sahiptir. MEİ işlemlerini füzyon tabanlı ve katı hal olarak sınıflandırmak, her kategorinin sağladığı malzeme özelliklerinde ve geometrik hassasiyette önemli farklılıklar olması açısından anlamlıdır. Genel olarak füzyon tabanlı teknolojiler, döküme yakın malzeme özelliklerine sahip net şekilli parçalar üretir. Öte yandan, katı hal süreçleri "net şekle yakın" geometriler üretir; ancak malzeme özellikleri daha üstün olabilir. Bununla birlikte, neredeyse her durumda, ikincil veya tamamlayıcı yüzey işlemleri de gereklidir.

Shrinkage evaluation and geometric accuracy assessment on 17–4 PH samples made by material extrusion additive manufacturing

Material Extrusion Additive Manufacturing (MEX) is one of the most common Additive Manufacturing (AM) technology. The possibility to realize metal parts using this technology has several advantages and generates great costs reduction with respect to other metal Additive Manufacturing technologies. However, there are some disadvantages related to the design and production of these extrusion-based metal parts, especially when considering the fabrication of complex geometries. One of the main problems is related to the oversizing of the parts due to the shrinkage phenomenon occurring after the debinding and sintering steps.In this work, a comprehensive study about the shrinkage phenomenon was conducted on 17–4 PH stainless steel parts realized via MEX, analyzing the influence of printing and sintering orientation, infill strategy and aspect ratio. With this aim, by using the Design of Experiment approach, samples were analyzed in both as-printed and as-sintered conditions. Shrinkage percentage values, geometric accuracy and density were the main investigated outputs. A commercial 3D structured-light scanner was used to collect the dimensional and geometric data.Results showed a strong shrinkage anisotropy, more relevant for samples with different orientation during the printing and the sintering phase. Geometric accuracy, in terms of flatness, was also assessed comparing green and sintered parts.

Deep reinforcement learning based toolpath generation for thermal uniformity in laser powder bed fusion process

Laser powder bed fusion (LPBF) is a widely used metal additive manufacturing technology. However, the accumulation of internal residual stress during printing can cause significant distortion and potential failure. Although various scan patterns have been studied to reduce possible accumulated stress, such as zigzag scanning vectors with changing directions or a chessboard-based scan pattern with divided small islands, most conventional scan patterns cannot significantly reduce residual stress. The proposed adaptive toolpath generation (ATG) algorithms, aiming to minimize the thermal gradients, may result in extremely accumulated temperature fields in some cases. To address these issues, we developed a deep reinforcement learning (DRL)-based toolpath generation framework, with the goal of achieving uniformly distributed heat and avoiding extremely thermal accumulation regions during the LPBF process. We first developed an overall pipeline for the DRL-based toolpath generation framework, which includes uniformly sampling, agent moving and environment observation, action selection, moving constraints, rewards calculation, and the training process. To accelerate the training process, we simplified the data-intensive numerical model by considering the turning angles on the toolpath. We designed the action spaces with three options, including the minimum temperature value, the smoothest path, and the second smoothest path. The reward function was designed to minimize energy density to ensure the temperature field remains relatively stable. To verify the effectiveness of the proposed DRL-based toolpath generation framework, we performed numerical simulations of polygon shape printing domains. In addition, four groups of thin plate samples with different scan patterns were compared using the LPBF process. The results indicated that using our proposed DRL algorithms for toolpath generation reduced the maximum distortion of the sample by approximate 47% compared to Zigzag patterns, 29% compared to Chessboard patterns, and 17% compared to ATG patterns. Our work demonstrated the effectiveness of implementing machine learning algorithms in the toolpath generation of the LPBF process.

High-speed direct energy deposition as a high-throughput design tool for laser-based additive manufacturing

A wide range of additive manufacturing (AM) processing conditions can be rapidly realized within a single specimen via high-speed direct energy deposition laser based (DED-LB), due to a variety of cooling conditions and in-situ powder mixing. Since existing approaches are inefficient in exploring the vast material and process design space in AM, high-speed DED-LB can be employed as a novel technology for high-throughput alloy design tool. However, an evaluation of the process transferability of the high-speed DED-LB process with respect to the currently dominating metal AM technologies, namely laser powder bed fusion (PBF LB/M) and conventional DED-LB, is required. In this study, high-speed DED-LB is applied for the high-throughput sample production, using the nickel alloy IN718 as reference material as well as the AM processes PBF LB/M and DED-LB as reference processes. The resulting microstructures are characterized and compared using optical microscopy and large-area scanning electron microscopy (SEM) analysis combined with energy-dispersive X-ray spectroscopy (EDS). Furthermore, a model for calculation of the volumetric energy density is developed to compare the applied AM processes. The significant influence of the processing conditions on the solidification behavior of the investigated material allows for efficient exploration of the microstructure and phase composition. Specific high-speed DED-LB-process conditions achieved the average solidification cell size and laves phase content as observed in the PBF LB/M- and DED-LB -produced counterparts. The applicability of the high-speed DED-LB process for rapid alloy and process development, i.e., process transferability, is critically evaluated. The results show that high-speed DED-LB can be used to emulate cooling conditions of PBF-LB/M and DED-LB and, therefore, be used as tool for rapid alloy development.