A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe[sbnd]Cr alloy

Metal Additive Manufacturing (MAM) has significantly simplified the design and production of complex components. However, achieving high-quality surface finishes remains a major challenge, particularly in Directed Energy Deposition (DED) technologies such as Laser Wire, Wire Arc, and Laser Powder Additive Manufacturing. To ensure parts are suitable for practical applications, post-processing is often required to enhance surface quality. This study presents a comprehensive evaluation of the surface topography and characteristics of stainless steel 316L parts fabricated using metal laser additive manufacturing techniques, including Wire Laser Directed Energy Deposition (WLDED) and Powder Laser Directed Energy Deposition (PLDED). Surface properties such as average roughness (Ra) and root mean square roughness (Rq) were measured using a surface roughness tester. The analyzed skewness (Rsk) and kurtosis (Rku) of the surfaces provided insights into the shape of roughness. To achieve improved surface quality, the ideal setting of process parameters, including laser power, scan speed, and feed rate, not just varies with the process used but also depends on which roughness parameter is prioritized. For example, PLDED at 600 W, 5-7.5 mm/s scan speed, and 4 g/min feed rate gives the best surface smoothness (Ra and Rq), but achieves minimum Rz at 500-600 W, 5 mm/s, and 4 g/min. Whereas, WLDED performed best in terms of Ra, Rq, and Rz at 1025 W, 8 mm/s, and 10 mm/s. This work highlights how surface topography varies across different AM processes in their optimized states, offering valuable guidance for selecting the most suitable AM technique based on surface finish requirements and application priorities. By addressing the critical challenge of roughness, the study bridges the gap between current manufacturing limitations and the growing demand for high-precision, application-ready parts. This research seeks to guide the advancement of enhanced AM processes, promoting innovation in industries such as aerospace, medical implants, and automotive engineering, where superior surface quality is essential. The findings help manufacturers refine their methods, reducing the need for extensive postprocessing while maintaining functional integrity.

Additive manufacturing of metal alloys via laser Directed Energy Deposition (L-DED) has been gaining popularity due to its potential to repair and create new features/components, enabling new applications for built parts. The success of L-DED operations hinges on the precise control of printing parameters, including laser power, scanning speed, and powder feed rate. These parameters significantly influence heat distribution during printing, directly impacting the quality of the resulting parts. Thus, defining an efficient methodology to find a good correlation between these parameters for the printing process is crucial to boost part production, as it reduces the time-consuming trial-and-error parameter tuning process. In this context, our study introduces an analytical model that predicts printing parameters based on the deposited material volume along track lines. Deposition was carried in stainless steel 316L with different values for laser power (ranging from 500 to 750W with 50W increments), scanning speed (from 400 to 700mm/min with 100mm/min increments), and powder feed rate (6.4,8.0 and 10.0g/min). The experimental data verified the effectiveness of the proposed model, demonstrating its potential to standardize the first step of printing process and expedite the initial search for optimal printing parameters in L-DED. The model provided accurate initial estimates of laser power, with a maximum relative error of 12%, particularly for the optimum mass flow rate (ṁ) of 8.0g/min. Beyond its benefits to the L-DED process, this analytical solution contributes to experimental practices by offering an efficient method for predicting material deposition volume during printing. Thus, our work underscores the significance of optimizing printing parameters to achieve high-quality parts and provides a valuable reference for future research and studies in the field of L-DED.

Microtexture in additively manufactured Ti-6Al-4V fabricated using directed energy deposition

The Direct Energy Deposition (DED) process is a metal additive manufacturing (AM) technique that uses high-energy heat sources, such as lasers, to melt metal materials, enabling the production of three-dimensional (3D) structures. Due to its highly flexible deposition head, this process is primarily used for part repairs, allowing localized repair of damaged areas without replacing entire components. These advantages make DED particularly valuable in high-value industries such as aerospace and automotive. Given these applications, the DED process must ensure precise and rapid handling of targeted areas. However, this process, which is performed by melting and solidifying metal, may result in quality differences due to the influence of external factors such as temperature and humidity and process parameters such as laser power and material feed density. Additionally, since the process is layered, the initial unevenness may accumulate, degrading the overall structure’s geometrical quality. This geometrical irregularity can further exacerbate instability in heat and material supply, potentially leading to internal defects like pores or lack of fusion. These defects can critically impact part quality in high-value industries, which operate in high-temperature and high-pressure environments, weakening mechanical properties and compromising both safety and performance. Therefore, real-time geometry monitoring is essential to ensure the stability and reliability of the DED process. This enables rapid detection and correction of irregularities, supporting economical, high-quality additive manufacturing. To establish such a geometry monitoring system, this study developed an artificial intelligence (AI)-based height prediction model using image and temperature data of the melt pool acquired during the process. First, laser power and scanning speed, the parameters most influential to process quality, were selected as key process parameters, and a full factorial design with 2 factors and 3 levels was applied for experiments. Under these conditions, the melt-pool multi-sensor data were collected through non-contact sensors such as CCD and IR cameras, and the line scanner captured additional geometric information of the deposited structure. Collected data were pre-processed for noise removal and target information filtering. Following this, features related to the size, brightness, position, shape, and temperature of the melt-pool were extracted, with a subset of statistically significant features chosen for model training. In this experiment, various time sequences and data lengths appeared due to differences in tool path or process conditions. To solve this, data transformation techniques were proposed, and as a result, data could be learned under various conditions in a single model. This technique involved time-sequential alignment for each track and interpolation to match the data point lengths. Finally, several AI models were constructed for the height prediction using the melt-pool multi-sensor data. Among them, the one-dimensional convolutional neural network (1D-CNN) model, which showed the best mean absolute percentage error (MAPE) performance, selected as the final height prediction model. This foundation enables real-time geometric prediction and monitoring and can contribute to maintaining optimal quality throughout the DED process.

Non-dimensional process maps for residual stress in laser directed energy deposition

In order to capitalize on the cost-effectiveness of additive manufacturing (AM), it is critical to understand how to build components with consistency and high quality. Directed energy deposition (DED) is an AM method for creating parts layer by layer through the use of a moving heat source and powder material inserted into the melt pool generated on the substrate. DED, like most AM processes, is highly complex due to the rapid thermal gradients experienced during processing. These thermal gradients are determined by a variety of processing parameters, which include laser power, powder feed rate, travel speed, layer height hatch spacing, etc. A lot of effort has been carried out in the additive manufacturing community to understand what these critical parameters are and how they influence the thermal gradients. Despite all these efforts, AM industries rely on a trial-and-error-based approach to find the right set of parameters to produce a quality part. This is time-consuming and not a cost-effective use of AM technology. The aim of our research is to reduce the amount of experimental data in combination with numerical analysis to optimize this relationship. Physics-based two-dimensional melt-pool modeling and experimental results from an OPTOMEC 850M LENS will be utilized to investigate the effects of processing parameters on melt-pool geometry, and the results from this study will provide key processing guidelines to achieve desirable clad geometry and powder efficiency for the DED method.

Aluminum-magnesium-scandium-zirconium (AlMgScZr) alloys need to be rapidly cooled from the liquid state to obtain a high degree of solute supersaturation that helps to exploit the precipitation hardening potential of the material. While AlMgScZr alloys have been successfully used in laser powder bed fusion (LPBF) processes, there has been little research in the field of laser directed energy deposition (DED) of the material. The limited previous studies have shown that the performance of AlMgScZr parts fabricated with DED only reached about 60% of that of the parts fabricated with LPBF. In view of breaking through the limitation associated with the process conditions of conventional DED, this work demonstrates the DED of AlMgScZr alloys in high-speed process regimes and elucidates the mechanism of enhancing the hardness and tensile strength of AlMgScZr alloys by increasing the cooling rate by one to two orders of magnitudes, as well as reducing the track overlapping and the porosity of the specimens during the process. A maximum average hardness of nearly 150 HV0.1 and a max. tensile strength of 407 MPa are obtained by using an energy per unit length of 5400 J/m and a powder feed rate per unit length of 0.25 g/m.

In the aerospace industry, regular maintenance and repair consume maximum cost and time. Direct energy deposition is an effective cutting edge repairing technology used in aircraft parts. This paper projected direct energy deposition as an important cladding technology. And as a cladding material, the acceptability of 15Cr5Ni precipitation-hardened steel is evaluated through single-layer deposition over 304 L stainless steel via direct energy deposition. 15Cr5Ni steel is a high-strength alloy mainly used for jigs, fasteners, and landing gears in the aerospace industry. Optimization of process parameters, that is, laser power, scan speed, and powder feed rate, is performed using response surface methodology through a prediction model along with a validation test. The microstructural investigation of clad cross-section and surface morphology followed by four-dimensional X-ray microscopy reveals an improved clad quality with minimized porosity and defects. A relative error of less than 5% has been found between the prediction model and experimental values, which validate the significance of optimized process parameters toward improving the clad quality for aircraft part repairing purposes.

Recently, laser deposition technologies have made significant advancements in their ability to manufacture high temperature metals and ceramics. One of these technologies, known as Direct Energy Deposition (DED), has the potential to deposit a wide range of materials from polymers to refractory materials, ceramics and functionally graded materials. This study evaluates major microstructural characteristics of WC-Co additively manufactured by DED technology. This material is commonly used for deposition of protective coatings due to its high hardness and excellent wear resistance. To this end, hardness and wear resistance of the DED processed samples were also investigated in this study. WC-Co coatings are generally deposited using various thermal spray technologies. However, it is speculated that DED deposited WC-Co could provide superior properties such as higher hardness and wear resistance. A DED manufactured WC-Co sample was examined by Optical Microscopy (OM), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and X-ray Diffraction (XRD). Those studies could provide information about important microstructural features, chemical compositions and phase distribution. All the tests were also repeated on High-Velocity Oxygen Fuel (HVOF) deposited WC-Co with the same composition. Both DED and HVOF produced WC-Co coatings experience decomposition of the carbides into compound phases; however, the DED deposited sample displays unique dendritic and eutectic structures that improve the hardness and wear properties compared to the homogenous HVOF coating. In addition, DED produced samples show higher hardness and relatively better wear resistance compared to the HVOF deposited ones. The obtained results could establish a relationship between microstructural characteristics with hardness and wear properties of both samples.

Towards a digital twin framework in additive manufacturing: Machine learning and bayesian optimization for time series process optimization

The present paper assesses the applicability of laser powder direct energy deposition for welding of thin stainless steel sheets. Considering the rapid development of laser cladding and relatively wide range of equipment available in modern industrial settings, this technology can also be applied to laser welding, where the procedure is performed with a filler material comprising blown powder. To this end, an exhaustive experimental campaign has been carried out with the aim of evaluating the influence of the main process parameters, including laser power and powder feed rate, on the resulting weld bead characteristics. Two joint configurations have also been considered to assess the best solution in terms of both chamfer shape and sheet positioning. Butt and lap joints were prepared, with 30° and 45° V-groove configurations tested and characterized in the former case. In order to assess the resulting weld quality, metallographic analyses were carried out to measure the main morphological parameters of the weld beads, including width, penetration depth and reinforcement, and to evaluate the possible presence of defects such as pores, cracks or lack of melting. Tensile tests were also carried out with the purpose of characterizing the overall mechanical performance of the joints. These tests demonstrated good overall process feasibility and highlighted the fact that lap joints and 30° V-groove butt joints were the best configurations in terms of both weld bead quality and fused zone morphology.

Novel Ni–Co-based superalloys with high thermal stability and specific yield stress discovered by directed energy deposition

Compared with pure titanium, ceramic reinforced titanium matrix composites (TMCs) have the advantages of higher microhardness, higher wear resistance, and better load endurance properties, which enable their further applications under severe friction and cyclic loading conditions. B4C-Ti composite, as a kind of TMCs, has been fabricated by laser directed energy deposition (DED) technology. However, there are still some problems needed to be solved. First, the B4C particles are not fully melted. It suppresses the reactions between B4C and titanium and reduced the generation of TiB and TiC during the fabrication, which deteriorates the hardness of the B4C-Ti composite. Second, the reinforcement materials are not evenly distributed in the titanium matrix, which damages the performance of the B4C-Ti composite. In this study, B4C-Ti composite parts are fabricated by the ultrasonic vibration-assisted laser DED process. The effects of laser power and ultrasonic vibration on the phase compositions, microstructure, and hardness are investigated.

AlSi10Mg cylindrical specimens were fabricated using the Laser-based Powder Bed Fusion (L-PBF) process, focusing on optimizing scanning speed, hatch spacing, and layer height through the box-behnken design (BBD). The study aimed to minimize surface roughness and maximize relative density. The analysis involved ANOVA, regression analysis, and composite desirability, revealing that hatch spacing and layer height significantly influence relative density and surface roughness. Under optimized conditions (scanning speed: 500 mm s−1, hatch spacing: 100 microns, layer height: 30 microns), the L-PBF specimen achieved a 96.70% relative density, 2.07 microns surface roughness (Ra), and an average microhardness of 124.9 HV0.5 (longitudinal) and 120.5 HV0.5 (transverse).

Microstructural and wear properties of WC-12Co cemented carbide fabricated by direct energy deposition