Laser Metal Deposition Process Research Articles

Localized defect frequencies for Laser Metal Deposition processes

Laser Metal Deposition (LMD) uses laser energy and powder material to create structures on existing components. It is capable of producing cost-effective multi-material compositions, such as reinforcing metals with ceramic particles for improved wear resistance. However, the use of dissimilar materials often leads to defects, particularly delamination. Previous studies have found a connection between these defects and specific airborne acoustic emissions (AE).To mitigate the impact of defects, extensive optimization of process parameters and real-time process monitoring are recommended. For AE, precise localization of defects is crucial besides to time- and frequency-resolved information, especially while producing multiple components on a substrate material.This study evaluates multi-sensor arrays for the localization of delamination defects. The research investigates the influence of localization algorithms and array patterns on the accuracy and reliability of defect localization. Experiments were conducted on a test platform with simulated acoustical events to determine the most suitable localization setup.

Off-axis optical system for the monitoring of the Laser Metal Deposition process

The Laser Metal Deposition (LMD) is emerging among the additive manufacturing (AM) technologies of metals for its versatility. It takes advantage of the flexibility of a laser source and a powder flow to fabricate or repair components with very complex features. The challenging process conditions that characterize the processing of metallic materials (temperatures and stresses) underlie the occurrence of several defects that plague such AM processes. Thus, the necessity to develop monitoring systems that can comprehensively analyze the production phase arises. In the present work, an innovative off-axis optical system consisting of three cameras with appropriate filters is proposed for the monitoring of LMD process. The peculiarity of this system lies in the capability of monitoring the spatial evolution of the melt pool, enabling eventually a complete control of the deposition process. In fact, through the use of properly developed image processing algorithms, the system enables the tridimensional definition of the size and shape of the melt pool and at the same time the reconstruction of each deposited layer. The potential of the monitoring system was tested on a series of thin-walled components. Subsequently, the analysis results were validated by comparison with 3D scanning of the parts and analyses performed using a coaxial monitoring system.

Initial experiments to regenerate the surface of plasma-facing components by wire-based laser metal deposition

Plasma-facing components (PFC) in nuclear fusion reactors are exposed to demanding conditions during operation. The combination of thermal loads, plasma exposure as well as neutron induced damage and activation limits the number of materials suitable for this application. Due to its properties, tungsten (W) is foreseen as plasma-facing material (PFM) for the future DEMOnstration power plant. It is considered suitable due to its exceptionally high melting point, excellent thermal conductivity, low tritium retention and low erosion resistance during plasma exposure. But even tungsten armored PFCs have a limited lifetime due to, among other factors, surface erosion and the resulting thickness reduction of the armor material.In-situ local deposition of tungsten by means of additive manufacturing (AM) could counteract surface erosion and thus increase the service life span of PFCs. After evaluation of the potential AM processes qualified for this task, the wire-based laser metal deposition (LMD-w) process was selected as the most suitable process. First trials were conducted to examine if it is possible to reliably deposit tungsten onto tungsten substrate using the LMD-w process. In these first studies, single welding beads were generated, and in later experiments, entire layers were created from several welding beads which are arranged next to each other. To ensure reproducibility of the results, the substrate temperature was kept constant. Further experiments aimed at the elimination or minimization of problems such as oxidation, occurrence of balling defects, porosity, cracking, surface waviness and insufficient connection to the substrate. To increase the welding bead quality, the input parameters like laser power, deposition velocity, wire feed rate, inert gas flow, as well as the wire position were optimized. Furthermore, stacking of several layers, as well as the remelting of an already created layer, were carried out and investigated. This study represents the first steps in testing the feasibility of an in-situ surface regeneration concept for PFCs.

Experimental evaluation of a WC–Co alloy layer formation process by multibeam-type laser metal deposition with blue diode lasers

A tungsten carbide–cobalt (WC–Co) composite layer was formed on a stainless-steel type 304 (SS304) substrate using multibeam laser metal deposition (LMD) with blue diode lasers. This paper aims to provide WC–Co layer formation with low porosity and high layer formation efficiency by using the multibeam LMD process. The effects of process parameters such as laser output power and powder feed rate are tied together to explain the geometry of the melt layer as well as the fraction of the laser energy used for melting a material. The experimental results show that the porosity rate and layer formation efficiency were recorded at 0.3% and 0.0042 mm3/J, respectively, at the laser output power of 180 W and a powder feed rate of 75 mg/s. It was revealed that layer formation efficiency was dependent on the laser output power.

Dry and Minimum Quantity Lubrication Machining of Additively Manufactured IN718 Produced via Laser Metal Deposition

Inconel 718 (IN718), a Ni-based superalloy, is immensely popular in the aerospace, nuclear, and chemical industries. In these industrial fields, IN718 parts fabricated using conventional and additive manufacturing routes require subsequent machining to meet the dimensional accuracy and surface quality requirements of practical applications. The machining of IN718 has been a prominent research topic for conventionally cast, wrought, and forged parts. However, very little attention has been given to the machinability of IN718 additively manufactured using laser metal deposition (LMD). This lack of research can lead to numerous issues derived from the assumption that the machining behavior corresponds to conventionally fabricated parts. To address this, our study comprehensively assesses the machinability of LMDed IN718 in dry and minimum quantity lubrication (MQL) cutting environments. Our main goal is to understand how LMD process variables and the cutting environment affect cutting forces, tool wear, surface quality, and energy consumption when working with LMDed IN718 walls. To achieve this, we deposited IN718 on SS309L substrates while varying the following LMD process parameters: laser power, powder feed rate, and scanning speed. The results unveil that machining the deposited wall closer to the substrate is significantly more difficult than away from the substrate, owing to the variance in hardness along the build direction. MQL greatly improves machining across all processing parameters regardless of the machining location along the build direction. Laser power is identified as the most influential parameter, along with the recommendation for a specific combination of power feed rate and scanning speed, providing practical guidelines for optimizing the machining process. While MQL positively impacts machinability, hourly energy consumption remains comparable to dry cutting. This work offers practical guidance for improving the machinability of LMDed IN718 walls and the successful adoption of LMD and the additive–subtractive machining chain. The outcomes of this work provide a significant and critical understanding of location-dependent machinability that can help develop targeted approaches to overcome machining difficulties associated with specific areas of the LMDed structure. The finding that MQL significantly improves machining across all processing parameters, particularly in the challenging bottom region, offers practical guidance for selecting optimal cutting conditions. The potential economic benefits of MQL in terms of tool longevity without a substantial increase in energy costs is also highlighted, which has implications for incorporating MQL in several advanced manufacturing processes.

In-process monitoring of track geometry as a control approach for laser metal deposition

Laser metal deposition (LMD) is an additive manufacturing process, which is used to generate large parts or for reconditioning machine components. During the process the welding tracks are affected by complex dynamic temperature-time curves that results in geometric deviations, which limits the build-up process. Therefore, complex structures are more difficult to manufacture with constant parameters. The present work describes an in-process monitoring system and first approaches of a control concept for LMD processes. It is set up using a newly developed laser triangulation sensor from Falldorf Sensor GmbH, which is trailing mounted. Due to the resistance to diffused radiation, e.g. from process light, it is possible to place the sensor close to the process zone which offers the possibility of a height control system. For the experiments, single tracks were welded from 316L powder by using a diode laser. The results show that the track width and height increase with rising laser power. Depending on the process parameter the height changes up to 29% and the width up to 58% if only the laser power is modified by 1800 W. The monitoring system forms a good basis for a later control concept, which can be used to make the process more stable in the case of complex structures.

Microstructure evolution and corrosion behavior of TC11 laser melt deposition additive components after post-heat treatment

The TC11 components were produced using a high-power, high-speed laser metal deposition (LMD) process. Subsequent post-heat treatment significantly improved the microstructures and corrosion resistance of the components. The results showed that the microstructure of the as-deposited component primarily comprised α Widmanstatten microstructure and mesh basket-weave microstructure. After post-heat treatment, the original interlayer zone disappeared in the deposition direction, and the microstructures were transformed from α’ to α phase. The aspect ratio of the α phase decreased, and the α grain boundary (αGB) became spheroidized. The tensile strength decreased but plasticity increased significantly. Overall, the corrosion resistance was improved in both directions, with greater improvements observed in the deposition direction. Phase ratio, grain size and KAM value are all factors affecting the corrosion resistance, but for the deposited direction, the significant improvement of the corrosion resistance is mainly due to the weakening of the charged galvanic corrosion effect between the non-interlayer zone and interlayer zone.

Towards Laser Metal Deposition of Modified PH 13-8Mo Powder

Modified PH 13-8Mo alloy exhibits a good combination of corrosion resistance and mechanical properties for demanding applications in aerospace, petrochemical, and tooling industries. Additive manufacturing, specifically the laser metal deposition process with powder as feedstock (LMDp), has the potential to be utilized in these industries. However, very limited knowledge on the LMDp of this alloy currently exists. The aim of this work was, therefore, to deposit a multi-track single layer of modified PH 13-8Mo alloy as a first step towards 3D geometries, and to analyze the resulting microstructure by using Optical Microscopy, Scanning Electron Microscopy, X-Ray Diffraction, Electron Backscatter Diffraction, and micro-hardness. It was found that the multi-track single layer was free from major defects. The microstructure was heterogeneous, and it consisted of a martensitic matrix and small amounts of δ ferrite, austenite, and AlN. The results of this research will be used to tailor the microstructure and properties of future 3D additively manufactured components.

Temperature Evaluation of Cladding Beads and the Surrounding Area during the Laser Metal Deposition Process

Cracks usually generate during the formation of beads composed of a WC-12mass%Co cemented carbide by the laser metal deposition (LMD). Measuring temperatures of the formed bead and substrate during the LMD process is important for realizing crack-free beads. In this study, temperatures of the substrate around the formed bead during the LMD process were measured using a thermoviewer. Temperatures of the formed beads during the LMD process were predicted by simulation based on the thermal conduction analysis using the experimentally measured temperatures of the substrate. The experimental results obtained during forming the WC-12mass%Co cemented carbide beads on JIS SKH51 (ISO HS-6-5-2) substrates showed that the maximal temperatures of the substrates at 0.2 mm away from the center of the formed beads ranged from 229 °C to 341 °C at laser powers ranging from 80 W to 160 W. The predicted maximal temperatures of the formed beads were in the range of 2433 °C to 4491 °C in the simulation using a laser absorption coefficient of 0.35 for the substrate. Validity of these simulation results was discussed based on the melting point of the substrate and microstructures of the formed WC-12mass%Co cemented carbide beads.

Microstructure and tribological behavior of Al–12Si – Nano graphene composite fabricated by laser metal deposition process

To improve the wear resistance of the Al-based alloys and extend its application spectrum, graphene nano-platelets (GNPs) reinforced Al–12Si matrix composites were fabricated by laser melting deposition (LMD) technology. The microstructure, wear morphologies and surface roughness were characterized by scanning electron microscopy (SEM), electron back-scattered diffraction (EBSD) setups and 3D confocal microscopy. The microhardness and high-speed reciprocating frictional properties both Al–12Si and GNPs/Al–12Si composites were evaluated. The addition of graphene significantly refines the microstructure and improves the wear resistance of the matrix. The formation of a relatively stable mechanically mixed layer (MML) reduces the contact area between the friction pair material and the wear surface, the wear rate and roughness of the Al–12Si – 0.5 wt% GNP reinforced composites decrease with the increase of sliding speed, and the wear mechanism changes from adhesive wear accompanied by abrasive wear to fatigue wear. Meanwhile, as the load increases, the wear rate and roughness increase. The wear mechanism of the composite changes from abrasive wear to a mixed mode (combination of both adhesive and abrasive). This research not only offers valuable information about the Al–Si-based composites but provides theoretical light on their industrial applications.

Prediction of single track clad quality in laser metal deposition using dissimilar materials: Comparison of machine learning-based approaches

Powder-based laser metal deposition (LMD) offers a promising additive manufacturing process, given the large number of available materials for cladding or generative applications. In laser cladding of dissimilar materials, it is necessary to control the mixing of substrate and additive in the interaction zone to ensure safe metallurgical bonding while avoiding critical chemical compositions that lead to undesired phase precipitation. However, the generation of empirical data for LMD process development is very challenging and time-consuming. In this context, different machine learning models are examined to identify whether they can converge with a small amount of empirical data. In this work, the prediction accuracy of back propagation neural network (BPNN), long short-term memory (LSTM), and extreme gradient boosting (XGBoost) was compared using mean squared error (MSE) and mean absolute percentage error (MAPE). A hyperparameter optimization was performed for each model. The materials used are 316L as the substrate and VDM Alloy 780 as the additive. The dataset used consists of 40 empirically determined values. The input parameters are laser power, feed rate, and powder mass flow rate. The quality characteristics of height, width, dilution, Fe-amount, and seam contour are defined as outputs. As a result, the predictions were compared with retained validation data and described as MSE and MAPE to determine the prediction accuracy for the models. BPNN achieved a prediction accuracy of 0.0072 MSE and 4.37% MAPE and XGBoost of 0.0084 MSE and 6.34% MAPE. The most accurate prediction was achieved by LSTM with 0.0053 MSE and 3.75% MAPE.

A Study on the Effects of Shape of the Substrate on Residual Stress Distributions of the Deposited Region for Repair of Axi-symmetric Part Using Laser Metal Deposition Process

A Study on the Effects of Shape of the Substrate on Residual Stress Distributions of the Deposited Region for Repair of Axi-symmetric Part Using Laser Metal Deposition Process

Effects of WC ratios on bead size and crack initiation in forming WC-Co cemented carbides by the laser metal deposition

Enhancing the durability of molds, jigs, and tools is crucial for the industry, and one approach to achieve this is by forming a metallic layer with high hardness on their surfaces. Metallic layers with high hardness can be formed through laser metal deposition (LMD), which is one of the additive manufacturing processes, using cemented carbide powder. However, crack initiation typically occurs inside cemented carbide layers formed by the LMD. Therefore, achieving a cladding process for cemented carbide layers without cracks is desired for practical applications. In this study, the effects of tungsten carbide (WC) ratios in WC-Co cemented carbide granulated powder on formed bead size and crack initiation during the LMD processing were investigated. The number of cracks generated during the LMD processing was evaluated using an acoustic emission (AE) technique. The number of burst-type AE signals generated was counted as the number of cracks. Seven types of WC-Co cemented carbide granulated powders with WC ratios ranging from 30.5 to 92 mass% were prepared. Beads were formed using each powder through the LMD, with AE signals being measured. In the case of a WC ratio of 42.9 mass% or less, no crack was observed. On the other hand, cracks were observed when the WC ratio was 53.9 mass% or greater, and the number of cracks increased with an increase in the WC ratio.

Enhancing productivity and efficiency in conventional laser metal deposition process for Inconel 718 – Part II: advancing the process performance

This paper is the second part of a work focused on optimizing the performance of conventional Laser Metal Deposition (C-LMD) process for Inconel 718 (IN718). In Part I, through an extensive experimental campaign on single tracks, the interplay between process parameters and their impact on the deposition rate, powder catchment efficiency, and clad geometry is examined. The parameters investigated include laser power, scan speed, powder feed rate, and standoff distance. By systematically adjusting these parameters, the aim is to identify optimal conditions that maximize productivity while maintaining a favorable clad shape for multi-pass multi-layer depositions. Part II starts from the findings and results of Part I by continuing the optimization on thick wall structures. These are utilized to assess the effect of 3D geometrical process parameters, specifically hatch spacing and Z-step, on process performance and stability. Based on the findings, further optimization procedure is presented, pushing the boundaries of the C-LMD process for IN718. By fine-tuning the process parameters, the capability of the C-LMD process to deposit fully dense IN718 with a productivity of 1500 g/h and a powder catchment efficiency of 70% is demonstrated. These results highlight the potential of C-LMD as a viable manufacturing technique for efficiently fabricating large components. Overall, this study contributes to a deeper understanding of the relationship between process parameters and performance in C-LMD for IN718. The insights gained from this research can guide the development of efficient and cost-effective LMD strategies, facilitating the practical implementation of this process in various industries.

Strengthening effect in laser metal deposited Ti6Al4V alloy via layer-by-layer ultrasonic impact treatment

The present work investigates the influence of incorporation of the layer-by-layer ultrasonic impact treatment (UIT) into the laser metal deposition (LMD) processing of Ti6Al4V alloy. The microstructure and mechanical properties of the samples with/without the assistance of UIT are comparatively studied. The curved shape boundaries of α/α′ phase with inconsistent misorientation angles and the ultra-fine α phase are observed in the UIT-assisted LMD (ULMD) sample. The α/α′ phase in the ULMD sample is characterized by high-density dislocations, larger lattice strain and distortion in comparison with that in the LMD sample. An ultimate tensile strength of 1386 MPa is obtained in the ULMD sample that exceeds that of the LMD sample by 373 MPa and is superior to the values reported in majority of the previous works. Crystallographic orientation change, increased dislocation density and α/α′ phase lattice distortion, and formation of ultra-fine α grains are found to influence the properties. The present work provides an in-depth understanding of the mechanisms/factors influencing the mechanical strengths of additive-manufactured titanium alloys.

Enhancing productivity and efficiency in conventional laser metal deposition process for Inconel 718 - part I: the effects of the process parameters

The sustainable energy transition has spurred the development of technologies that minimize material and energy waste, such as additive manufacturing (AM). Laser metal deposition (LMD) is a promising AM technique, but its complexity and limited automation hinder its implementation in production chains. To enhance productivity, the high deposition rate LMD (HDR-LMD) technology has been developed, requiring advanced equipment and powerful laser sources. In contrast, the conventional LMD (C-LMD) process is simpler and less expensive to implement. This study aims to optimize the productivity and efficiency of C-LMD by adjusting laser power, scan speed, powder feed rate, and standoff distance on Inconel 718 single tracks. An innovative approach eliminates the need for cutting specimens to evaluate single tracks, allowing comprehensive geometric and performance characterization with limited operator involvement, making the analysis quicker and more robust. An extensive experimental campaign was conducted to examine the influence of process parameters on track geometry, productivity, and efficiency. A multi-objective optimization procedure identified parameter combinations maximizing productivity while maintaining high efficiency and desirable clad shape. The study attained deposition rates ranging from 700 to 800 g/h, with powder catchment efficiency ranging between 75 and 90%. These results were achieved using parameters including 1775 W of laser power, scan speeds ranging from 960 to 1140 mm/min, powder feed rates between 810 and 1080 g/h, and standoff distance of 9 mm. The study also clearly indicated that further potential for improving C-LMD process performance may be possible. The findings gathered in this paper are the base for the further optimization presented in the second part of the work, which is focused on multi-pass multi-layer and reaches deposition rates of 1500 g/h, promoting the implementation of C-LMD process at industrial level.

Online monitoring of direct laser metal deposition process by means of infrared thermography

Direct laser metal deposition (LMD–DED) is an additive manufacturing (AM) process that is used to build up and repair high-quality metal components. It works by overlapping layers of powder material and melting them with a laser. To get a stable process without defects and to reach, at the same time, high mechanical properties, a robust assessment and control of the process parameters, and above all of their combination, is required. The ideal goal is to assure the online control, to stop or correct the process in case of unexpected anomalies. In this work, a robust online monitoring of the laser metal deposition (LMD–DED) process based on the use of infrared thermography was developed and proposed. After choosing the suitable process parameters, a customized design of experiments (DOE) was set, and the statistical analysis of different thermal features was carried out to develop the most robust models that correlate them with the input process parameters (laser power, scanning speed, and powder flow rate). The proposed procedure was based on the extraction of different thermal features from suited regions of interest (ROI), performing statistical analyses by means of analysis of variance (ANOVA) and building regression models to correlate the process parameters with the thermal behavior. The obtained results demonstrated the possibility to control the process by means of the chosen thermal features, independent of the position of the ROI. Moreover, the possibility to use the models to detect typical AM defects, and anomalies, online directly during the process, has been proved and verified by destructive macrographs carried out on the manufactured coupons.

Revealing the evolution of microstructure and mechanical properties with energy density to achieve high-strength Ti-6wt%Cu alloy by laser metal deposition

In this work, Ti-6wt%Cu alloys were fabricated by laser metal deposition (LMD) technology to understand how the energy densities impact the microstructure and consequent mechanical properties. The results show that a bimodal microstructure of ultrafine eutectoid lamellae and Widmanstätten-α can be obtained at low energy density (118 J/mm3), while higher energy density produces coarse colony-α structure. The multi-scale microstructural refinement is achieved due to the fast cooling rate and low heat accumulation in low energy density deposits, resulting in a sound combination of property with tensile strength of 1063 MPa and elongation of 10%. Based on the solidification theories and accurate solidification parameters in the LMD process, the columnar to equiaxed transition (CET) was proposed to elucidate the refinement mechanism of near-equiaxed prior-β grains. Furthermore, detailed microstructural characterization identified the effect of Cu segregation on the formation of eutectoid lamellae. The Cu aggregation at low energy density plays a crucial role in phase transition and microstructural refinement, as well as account for orientation heterogeneity of lamellae. In addition, the strengthening mechanisms were discussed by considering microstructural evolutions due to different energy densities.

Numerical Analysis and Experimental Investigation of High Cycle Fatigue Behavior in Additively Manufactured Ti–6Al–4V Alloy

Additive Manufacturing (AM) of the Ti–6Al–4V alloy has gained significant importance across various industries, including biomedical, aerospace, cellular, and land vehicle applications, due to its numerous benefits. The certification of performance and reliability of AM materials, particularly for critical applications, heavily relies on evaluating fatigue strength. In this study, a numerical analysis based on the finite element method is presented to predict the High Cycle Fatigue (HCF) behavior of AM Ti–6Al–4V alloy. The investigation focuses on exploring the sensitivity of material fatigue life to surface roughness and Ultimate Tensile Strength (UTS). Uniaxial tensile and High Cycle Fatigue (HCF) tests were conducted on Ti–6Al–4V alloy samples extracted from rectangular walls manufactured using the Laser Metal Deposition (LMD) process. The walls were surface machined prior to sample extraction. Porosity and surface roughness measurements were performed on the samples. Numerical simulations of the HCF tests were carried out, considering various surface roughness ranges and UTS values. The numerical results were then compared to experimental data. The findings consistently demonstrated that higher surface roughness led to a shorter fatigue life, while higher UTS values resulted in a longer fatigue life. The numerical solutions aligned with the experimental results, indicating the efficacy of the finite element method in predicting the fatigue behavior of AM Ti–6Al–4V alloy. These insights contribute to a better understanding of the relationship between surface roughness, UTS, and fatigue life of Ti–6Al–4V alloys manufactured by AM.

Optimizing porosity detection in wire laser metal deposition processes through data-driven AI classification techniques

Additive manufacturing (AM) is an attractive solution for many companies that produce geometrically complex parts. This process consists of depositing material layer by layer following a sliced CAD geometry. It brings several benefits to manufacturing capabilities, such as design freedom, reduced material waste, and short-run customization. However, one of the current challenges faced by users of the process, mainly in wire laser metal deposition (wLMD), is to avoid defects in the manufactured part, especially the porosity. This defect is caused by extreme conditions and metallurgical transformations of the process. And not only does it directly affect the mechanical performance of the parts, especially the fatigue properties, but it also means an increase in costs due to the inspection tasks to which the manufactured parts must be subjected. This work compares three operational solution approaches, product-centric, based on signal-based feature extraction and Topological Data Analysis together with statistical and Machine Learning (ML) techniques, for the early detection and prediction of porosity failure in a wLMD process. The different forecasting and validation strategies demonstrate the variety of conclusions that can be drawn with different objectives in the analysis of the monitored data in AM problems.