Hatch Distance Research Articles

Optimal process parameter determination in selective laser melting via machine learning-guided sequential quadratic programing

Selective Laser Melting (SLM) is a widely used additive manufacturing method with critical processing parameters such as Laser Power, Scanning Speed, Hatch Distance, and Laser Beam Diameter, which significantly impact process quality and mechanical properties of fabricated parts like Relative Density, Hardness, and Surface Roughness. This study investigates an effective approach to modeling the SLM process for predicting and optimizing processing parameters using a combination of Machine Learning (ML) and Sequential Quadratic Programing (SQP). The proposed method aims to predict the mechanical properties of SLM-produced AlSi10Mg parts using Machine Learning techniques and then transform the process into a constrained multiple-objective optimization model employing the SQP algorithm to determine optimal process parameters. Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and Support Vector Machine (SVM) algorithms are applied to establish correlations between process parameters and mechanical properties, represented as mathematical functions. A cost function is formulated using these functions and minimized using the SQP method. Statistical analysis is implemented to validate the influence of processing parameters on mechanical properties accordingly. The outcomes of the method are verified through additional experiments and analyses using Micro-CT scanning techniques. The results demonstrate that processing parameters have a significant impact on part properties across different scales, with Micro-CT scanning proving instrumental in validating mechanical properties. Overall, this study establishes that multiple objectives can be efficiently optimized through the integration of ML and SQP methods, complemented by a judicious number of experiments.

Powder bed fusion of solid and permeable Crofer 22 APU parts for applications in chemical process engineering

AbstractAdditive manufacturing of metals has attracted significant attention across various industries. However, its adoption in certain chemical and energy sectors remains constrained by the absence of optimized alloys tailored for high temperatures and corrosive environments. This study explores the laser-based powder bed fusion processing of Crofer 22 APU, a high-temperature, corrosion-resistant alloy ideal for applications such as methane steam reforming reactors, high-temperature fuel cells, and palladium membrane supports. Systematic optimization of laser parameters including laser power, hatch distance, point distance, and building angles was conducted for both dense and porous objects. Dense parts achieved a relative density of 0.9999 and surface roughness of Sa= 41.27±1.48 on a 45$$^\circ$$ ∘ overhang. Porous samples showed a porosity range of 28.655.5% and surface roughness Sa 22.2 $$\upmu$$ μ m to 45.9 $$\upmu$$ μ m as hatch distance increased from 0.12 mm to 0.16 mm. Additionally, an 8YSZ coating applied via screen printing demonstrated the impact of hatch distance and laser power on surface quality. The combination of additive manufacturing of Crofer 22 APU and screen printing of 8YSZ simplifies the preparation of metallic supports for Pd-based membranes, reducing fabrication time and cost by shortening the number of preparation steps. This technique offers a promising approach for scaling up membranes and membrane reactors.

Experimental Study and Random Forest Machine Learning of Surface Roughness for a Typical Laser Powder Bed Fusion Al Alloy

Surface quality represents a critical challenge in additive manufacturing (AM), with surface roughness serving as a key parameter that influences this aspect. In the aerospace industry, the surface roughness of the aviation components is a very important parameter. In this study, a typical Al alloy, AlSi10Mg, was selected to study its surface roughness when using Laser Powder Bed Fusion (LPBF). Two Random Forest (RF) models were established to predict the upper surface roughness of printed samples based on laser power, laser scanning speed, and hatch distance. Through the study, it is found that a two-dimensional (2D) RF model is successful in predicting surface roughness values based on experimental data. The best and minimum surface roughness is 2.98 μm, which is the minimum known without remelting. More than two-thirds of the samples had a surface roughness of less than 7.7 μm. The maximum surface roughness is 11.28 μm. And the coefficient of determination (R2) of the model was 0.9, also suggesting that the surface roughness of 3D-printed Al alloys can be predicted using ML approaches such as the RF model. This study helps to understand the relationship between printing parameters and surface roughness and helps print components with better surface quality.

Towards bespoke gas permeability by functionally graded structures in laser-based powder bed fusion of metals

Permeable, media transporting, components are an integral part in numerous technical applications. In gas turbines combustors, for example, gaseous oxidizer and fuel are transported separately into the burner, where they are injected and mixed, and subsequently combusted. The mixture homogeneity strongly affects the combustion performance and emissions formation and is, amongst other, determined by the spatial distribution of fuel injection ports. In this context, porous media provide the limiting case for a spatial distribution of media-injecting pores, yet is typically associated with a high pressure drop that yields a loss in efficiency. In this study, possibilities of achieving gas permeability in additively manufactured porous structures are investigated. The objective is to selectively functionalize the permeable layers for gaseous media supply with low pressure loss and, when needed, enable a targeted mixing of different gas streams. For this purpose, a laser-based powder bed fusion process (PBF-LB/M) was used in this study. It offers the opportunity to manufacture varying porosities inside complex monolithic metal parts. To produce the porous structures and to achieve gas permeability, the effect of scan rotation angle, hatch distance, build-up direction and length of the porous specimen is investigated. Due to the high temperatures present in combustion systems, the present work utilizes Inconel 718 material. The AM gas permeable specimen are experimentally characterized by means of surface topography, micro X-ray computed tomography (µXRCT) as well as flow and pressure loss test. The results show, that the AM process parameter provide effective control parameters to adjust the permeability. The strongest effect originates from the hatch distance for a given build-up direction. Depending on the scan rotation, the flow transitions from a turbulent pipe flow to a Darcy flow as present in conventional porous media. A structured alignment and connectivity of pores can be realized as evident in the µXRCT results, surface topography and the flow measurements. Residual powder, powder adhering to the pore walls and stochastic closure of pores or channels lead to deviations and need to be considered when designing respective parts. Nonetheless, the results further show that a directional dependence of the permeability and the build-up direction can be realized and controlled. Consequently, when considering the AM build-strategy in the design of components, this directed permeability can be functionalized in the generation of gas transporting and gas mixing layers separately by adjusting the AM processing parameter.

Process parameter optimization for selective laser melting Ti-6Al-4V with high layer thickness

Increasing the layer thickness is an important method to increase the forming efficiency of selective laser melting (SLM) but affects the forming quality. In this work, a single track and cube sample with an 80µm layer thickness was fabricated by SLM, and then the relative density, hardness, defects, and forming efficiency were studied. It is found that the morphology of the single tracks changes significantly with the change of scanning speed. Fewer defects appear on the top surface and cross section with scanning speed below 850mm/s. However, the defects increase significantly with further increasing scanning speed. Furthermore, the relative density of the Ti-6Al-4V can reach 99.89% when the scanning speed is 800mm/s. The Vickers hardness is highest when the scanning speed is 500mm/s with the top surface of 402 HV and the side surface of 378 HV. An increase of scanning speed not only causes larger balling particles, but also results in making an appearance of micro-cracks. The increase in layer thickness leads to insufficient energy density, which affects the occurrence of lack of fusion concurrently. Element evaporation occurs at low scanning speeds, which can increase defects in the sample. The appropriate process parameters are the laser power of 300W, the scanning speed of 800mm/s, and hatch distance of 0.17mm. At this time, the forming efficiency is as high as 8.96 mm3/s.

A new model framework of laser powder bed fusion by integrating a powder-scale model with a thermodynamic database

Laser powder bed fusion (LPBF) has been increasingly practised in powder-based additive manufacturing industries, yet the fundamentals including multiphase flow and phase change were not well understood. This work develops a powder-scale computational fluid dynamics-discrete element method-volume of fluid (CFD-DEM-VOF) model integrated with a temperature-dependent thermodynamic database to simulate the multiphase flow with phase change in the LPBF process. The integrated model is validated by comparing prediction results with the experimental measurements. Several LPBF cases with different laser powers, track numbers, and hatch distances are numerically studied. The simulation results demonstrate that the model can capture the key phenomena and key features in the LPBF process observed experimentally, including temperature distribution and morphology of molten tracks. The results also show the random configuration of the powders leads to the asymmetrical distribution of the temperature in the molten pool. The laser beam with a lower power density causes pore defects in the transition zone of the laser track because of partially melted particles, causing a rough molten surface. Incorporating an overlap between two molten tracks is crucial for enhancing the surface quality and mitigating issues such as discontinuity and particle adherence along the track edge. This model provides a cost-effective solution for comprehending and optimizing multiphase flow and phase change phenomena within the LPBF process in additive manufacturing.

Elucidating the effects of metal transfer modes and investigating the material properties in wire-arc additive manufacturing (WAAM)

AbstractStudies have shown the influence of WAAM process parameters on mechanical properties, bead formation, dimensional accuracy, and microstructure. However, metal transfer modes and their interactions with input variables have not been investigated thoroughly. Therefore, short/spray, pulse and double pulse modes were investigated in this study at different current levels. Bead-on-plate trials were conducted by depositing ER70S-6 wire to investigate bead morphology, dilution, microstructure, and hardness. The study was supported by a detailed statistical approach, including analysis of variance (ANOVA) and regression analysis. Similarly, the combined effects of hatch distance and current were studied on bead formation in multi-layer deposits. Moreover, a thin wall and a cubic structure were deposited to realize the WAAM capability for larger depositions. The microstructures of thin wall and cubic structure were analyzed using optical microscopy (OM) and scanning electron microscopy (SEM). The study concludes that metal transfer modes at various currents significantly influence bead geometry, microstructure and hardness. The microstructure of bead-on-plate trials show fine lamellar structure at low current in all modes. Higher current results in coarse grains with a polygonal and columnar morphology. The hardness shows a decreasing trend as the current increases. The combined effects of current and hatch distance alter bead morphology; however, an optimized combination yields smoother surfaces. The microstructure of thin wall showed a slight anisotropy along the building direction. The presence of small pores was witnessed from OM and SEM images. Similarly, the cubic structure showed a more homogeneous microstructure with much lower porosity. The hardness profile of the thin wall exhibited small fluctuations along the building direction, while that of the cubic structure was more uniform.

Development and Validation of a One‐Dimensional Finite Difference Simulation Scheme for Polymer Laser Powder Bed Fusion with Application to the Effect of the Inter Layer Time

The division of the polymer laser powder bed fusion process polymers (PBF‐LB/P) into temporal regimes originating from laser motion, thermal diffusion, viscous flow, crystallization kinetics, and powder application is exploited by considering only the building direction. The reduction of dimensionality enables fast simulations which are used to investigate the influence of the inter layer time on the final part density. Numerical simulation results are validated by experiments using polyamide 12 (PA 12) with good agreement in terms of part density. It is shown that an inter layer time of 90 s leads to nearly dense PA 12 parts while a time of 45 s leads to less dense parts. The cooling effect of the applied powder is identified as a cause for insufficient densification of the previous layer. The simulation tool is quantitatively validated against experimental results for the surface temperature of PA 12 as function of scan speed and hatch distance, for the melt pool depth of polyamide 6 as function of scan speed and for the melt pool depth of polyetherketoneketone as function of laser power. The presented simulation method enables rapid process parameter adjustment for new polymer materials in the PBF‐LB/P process.

Optimizing Selective Laser Melting of Inconel 625 Superalloy Through Statistical Analysis of Surface and Volumetric Defects

This article delves into optimizing and modeling the input parameters for the selective laser melting (SLM) process on Inconel 625. The primary aim is to investigate the microstructure within the interlayer regions post-process optimization. For this study, 100 layers with a thickness of 40 µm each were produced. Utilizing the design of experiments (DOE) methodology and employing the Response Surface Method (RSM), the SLM process was optimized. Input parameters such as laser power (LP) and hatch distance (HD) were considered, while changes in microhardness and roughness, Ra, were taken as the responses. Sample microstructure and surface alterations were assessed via scanning electron microscopy (SEM) analysis to ascertain how many defects and properties of Inconel 625 can be controlled using DOE. Porosity and lack of fusion, which were due to rapid post-powder melting solidification, prompted detailed analysis of the flaws both on the surfaces of and in terms of the internal aspects of the samples. An understanding of the formation of these imperfections can help refine the process for enhanced integrity and performance of Inconel 625 printed material. Even slight directional changes in the columnar dendrite structures are discernible within the layers. The microstructural characteristics observed in these samples are directly related to the parameters of the SLM process. In this study, the bulk samples achieved a microhardness of 452 HV, with the minimum surface roughness recorded at 9.9 µm. The objective of this research was to use the Response Surface Method (RSM) to optimize the parameters to result in the minimum surface roughness and maximum microhardness of the samples.

Hole quality geometrical measurement and surface roughness for α-Phase titanium alloy (α-Ti-6Al-4V) materials by using L-PBF (laser powder bed fusion) orthopedic implant application

This study examines the quality of circular-hole 3D-printed objects using laser powder bed fusion (L-PBF) on Ti-6Al-4V titanium alloy that typically used for orthopedic implants. Meanwhile measuring surface roughness and hole dimension deviations in AM specimens is very challenging. Thus, the specimens were printed with varying process parameters, followed by an L9 orthogonal array experiment, where parameters included laser power (LP) at 175, 185, and 195 W; scanning speed (SS) at 600, 900, and 1200 mm/s; and hatch distance (HD) at 70, 90, and 110 µm. Thus the, minimum surface roughness values are Ra 2.4 µm for the top surface and Ra 16.06 µm for the inside hole curve. Whereas the smallest hole deviations are 0.1102 mm for external and 0.2094 mm for internal diameters. Therefore, this analysis include FESEM, EDX, XRD, profilometry and stereomicroscopy. Where the best settings are LP 195 W, SS 900 mm/s, and HD 70 µm, producing well-fused, uniform α-phase Ti-6Al-4V specimens that are suitable for biomedical applications.

A detailed study on optimizing DMLS process parameters to enhance AlSi10Mg metal component properties

This study investigates the effects of laser power, scan speed, and hatch distance on the features of aluminium specimens produced using direct metal laser sintering (DMLS). By systematically varying these parameters, we identified optimal combinations for producing high-quality metal components. Our findings were validated through reproducible printing processes. Analysis of variance (ANOVA) and grey relational analysis (GRA) were employed to optimize the production parameters further. We found a significant trade-off between laser power, tensile strength, and fatigue resistance, with laser power having the most substantial impact on mechanical properties, microstructure, and surface roughness. Statistical analysis confirmed that higher laser power improves mechanical characteristics but may increase surface roughness. These insights are crucial for enhancing the efficiency and quality of DMLS-produced metal components.

Controlled Porosity of Selective Laser Melting-Produced Thermal Pipes: Experimental Analysis and Machine Learning Approach for Pore Recognition on Pipes Surfaces.

This study investigates the methods for controlling porosity in thermal pipes manufactured using selective laser melting (SLM) technology. Experiments conducted include water permeability tests and surface roughness measurements, which are complemented by SEM image ML-based analysis for pore recognition. The results elucidate the impact of SLM printing parameters on water permeability. Specifically, an increase in hatch and point distances leads to a linear rise in permeability, while higher laser power diminishes permeability. Using machine learning (ML) techniques, precise pore identification on SEM images depicting surface microstructures of the samples is achieved. The average percentage of the surface area containing detected pores for microstructure samples printed with laser parameters (laser power (W) _ hatch distance (µm) _ point distance (µm)) 175_ 80_80 was found to be 5.2%, while for 225_120_120, it was 4.2%, and for 275_160_160, it was 3.8%. Pore recognition was conducted using the Haar feature-based method, and the optimal patch size was determined to be 36 pixels on monochrome images of microstructures with a magnification of 33×, which were acquired using a Leica S9 D microscope.

Tailoring Laser Powder Bed Fusion Process Parameters for Standard and Off-Size Ti6Al4V Metal Powders: A Machine Learning Approach Enhanced by Photodiode-Based Melt Pool Monitoring

An integral part of laser powder bed fusion (LPBF) quality control is identifying optimal process parameters tailored to each application, often achieved through time-consuming and costly experiments. Melt pool dynamics further complicate LPBF quality control due to their influence on product quality. Using machine learning and melt pool monitoring data collected with photodiode sensors, the goal of this research was to efficiently customize LPBF process parameters. A novel aspect of this study is the application of standard and off-size powder feedstocks. Ti6Al4V (Ti64) powder was used in three size ranges of 15–53 µm, 15–106 µm, and 45–106 µm to print the samples. This facilitated the development of a process parameters tailoring system capable of handling variations in powder size ranges. Ultimately, per each part, the associated set of light intensity statistical signatures along with the powder size range and the parts’ density, surface roughness, and hardness were used as inputs for three regressors of Feed-Forward Neural Network (FFN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The laser power, laser velocity, hatch distance, and energy density of the parts were predicted by the regressors. According to the results obtained on unseen samples, RF demonstrated the best performance in the prediction of process parameters.

Advanced manufacturing of high conductive graphene coatings on polyethylene terephthalate substrate through laser-induced processes and thermal optimization

Graphene holds immense promise for applications in sensors due to its exceptional properties such as large carrier mobility and high electrical and thermal conductivities. Nevertheless, the manufacture of high conductive graphene films onto flexible substrates remains a formidable challenge. This paper presented a novel method for the precise incorporation of high conductive graphene coatings onto polyethylene terephthalate (PET) through the back transfer of laser-reduced graphene oxide (LRGO) from Al2O3 ceramic to PET. A record-low sheet resistance for LRGO so far, approximately 12 Ω/sq. was achieved, meantime exhibiting 5B level adhesion performance with PET substrate. The sheet resistance of the transferred LRGO was measured and demonstrated to be adjustable by manipulating laser power, scanning speed, and hatch distance. The analysis of reduction of graphene oxide (GO) involved a comprehensive examination of alterations in topography image, chemical bond content, C/O atomic ratio, and ID/IG intensity ratio. These observations provided insights into the factors contributing to the decrease of sheet resistance within LRGO. The adoption of a continuous gigahertz (GHz) femtosecond laser as the light source, coupled with the incorporation of thermally conductive Al2O3 plate as a heat sink, facilitated the manufacturing processes including reduction and transfer of GO. The manufacture of graphene coatings with high electrical conductivity on PET in a versatile and cost-effective manner, presents significant potential for diverse applications, particularly in conductive-coatings-based sensors.

Powder Bed Fusion-Laser Beam of IN939: The Effect of Process Parameters on the Relative Density, Defect Formation, Surface Roughness and Microstructure.

This study investigates the effects of process parameters in the powder bed fusion-laser beam (PBF-LB) process on IN939 samples. The parameters examined include laser power (160, 180, and 200 W), laser scanning speed (400, 800, and 1200 mm/s), and hatch distance (50, 80, and 110 μm). The study focuses on how these parameters affect surface roughness, relative density, defect formation, and the microstructure of the samples. Surface roughness analysis revealed that the average surface roughness (Sa) values of the sample ranged from 4.6 μm to 9.5 μm, while the average height difference (Sz) varied from 78.7 μm to 176.7 μm. Furthermore, increasing the hatch distance from 50 μm to 110 μm while maintaining constant laser power and scanning speed led to a decrease in surface roughness. Relative density analysis indicated that the highest relative density was 99.35%, and the lowest was 93.56%. Additionally, the average porosity values were calculated, with the lowest being 0.06% and the highest reaching 9.18%. Although some samples had identical average porosity values, they differed in porosity/mm2 and average Feret size. Variations in relative density and average porosity were noted in samples with the same volumetric energy density (VED) due to different process parameters. High VED led to large, irregular pores in several samples. Microcracks, less than 50 μm in length, were present, indicating solidification cracks. The microstructural analysis of the XZ planes revealed arc-shaped melt pools, columnar elongated grains aligned with the build direction, and cellular structures with columnar dendrites. This study provides insights for optimizing PBF-LB process parameters to enhance the quality of IN939 components.

Durable self-cleaning anti-fog and antireflective titanium-based micro-nano structures on glass by laser marker ablation

Hierarchical micro-nano structured glass surfaces were produced by a low-cost laser marker ablation of Titanium-coated glass. The samples were systematically analyzed in terms of composition, structure, morphology, transparency, and anti-fog performance. The influences of varying laser scan hatch distance and Titanium (Ti) coating thickness on the resulting surface properties were studied. The results showed that the surface exhibited a 30 μm-sized periodic hillock-hollow micro-structure, with widely dispersed nanoparticles of approximately 50 nm in diameter all over the micro-structure. The most favorable surface characteristics were achieved with a 250 nm Ti coating and a 0.03 mm hatch distance, resulting in a notable enhancement of the average transmission of the glass by 1.29 % over a wide spectral range spanning from 400 nm to 1100 nm. Additionally, the treated surface exhibited super-hydrophilicity, evidenced by a contact angle of 0°, thereby demonstrating excellent anti-fog performance in fog tests that remained effective for an impressive duration of 318 days. It also exhibits exceptional anti-fouling and self-cleaning attributes, which remain effective over a span of 459 days. This outstanding antifog self-cleaninng performance and broadband transmission enhancement was, for the first time, co-achieved for laser treated glass. These accomplishments hold substantial practical relevance in diverse applications.

Effect of laser texturing and thermomechanical joining parameters on bond strength of steel-flax fiber reinforced vitrimer composites

The study examines laser texturing's impact on metal-composite hybrid joint mechanics formed via heat compression. It focuses on sustainable composite fabrication, utilizing flax fibers and a recyclable vitrimer resin known for dynamic covalent bond exchange capabilities, enhancing recyclability, repairability, and reshaping. Simulated heating conditions determined optimal bonding between the composite and laser-textured surfaces, considering the glass transition temperature for minimum temperature and time requirements. Deviations from initial heat pressing conditions (135 °C, 0.6 MPa, 5 min) reduced bonding strength, underscoring parameter sensitivity. Cross-tensional tests under varied laser texturing conditions, supported by microscopic examinations, revealed optimal strength (1680 N) with a 150 μm hatch distance and 9 repetitions, ensuring consistent ablation volume and time. Supplementary ANSYS simulations pinpointed stress concentration regions in cross-tensional joints, guiding adjustments in laser texturing within the region of interest to assess mechanical properties. The hybrid cross-tensional and lap shear joints were also reconnected after each fracture via heat compression, allowing for the evaluation of degradation in bonding strength over each cycle.

Permeability and strength of gradient printed permeable steel manufactured by selective laser melting

Based on the forming principle of laser rapid melting and layered manufacturing, the selective laser melting (SLM) process is suitable for the preparation of permeable metal materials with a certain porosity. One of the important applications of this special structure is the development of permeable steel. In this study, the permeable steel with micron-sized controllable pores was prepared by gradient printing using SLM process. The formation and connectivity mechanism of pore structure were analyzed by adjusting the interlayer arrangement of scanning melt channels, and the influence of process parameters on the pore characteristics, permeability and mechanical properties was systematically investigated. The results revealed that the porosity and pore size of permeable steel were effectively improved by controlling the hatch distance and scanning strategy, with the results ranging from 7.81 % to 17.32 % and 57 μm to 121 μm, respectively. Based on the gas permeation test, it was verified that the permeability of permeable steel showed a clear upward trend with increasing porosity, and the results ranged from 2.17 × 10−12 m2 to 4.26 × 10−12 m2, indicating that the pore structure provides a strong basis for gas flow. Moreover, the mechanical properties of permeable steel decreased significantly with the increase of porosity and pore size, and the compressive strength and tensile strength ranged from 1061 MPa to 528 MPa and 1018 MPa to 609 MPa, respectively. The mechanical behavior and deformation mechanism were closely related to the gradient evolution of the pore structure. Overall, the gradient printed permeable steel using SLM process has good permeability and mechanical properties.

Investigation of the shape-changing property of X-ray computed tomography in the evaluation of pores

Porosity in additive manufacturing is one of the main quality characteristics for components. In processes such as laser-based powder bed fusion of metals (LPBF-M), correlations can be observed between the process parameters used, such as laser power, hatch distance or layer thickness, and the pore shape produced. Therefor the surface depending criterion sphericity is a crucial parameter for the classification of pores. In addition to methods like micrographs or Archimedes' density determination, industrial X-ray computed tomography (CT) is a key measurement method for the spatial but also shape-dependent assessment of pores in components. However, due to the lack of standards, no measurement uncertainty for shape, position, and volume can be given for CT measurements. With the help of CT simulations and models for detector and X-ray source to real CT system, investigations can be made on the dependencies and influence on the detectability of pores. This study shows that the CT measurements as well as the analysis have an influence on the detectable volume and surface of pores. By modelling pore models with cosine periodic spatial frequencies (peaks), the spatial influence of CT on detectability can be investigated and assessed as a form of slope distribution. The simulation-based measurement uncertainty information can be used to improve the separation of pore shape classifications and thus contribute to the development of additive manufacturing.

A Comparative Analysis of Low and High SiC Volume Fraction Additively Manufactured SiC/Ti6Al4V(ELI) Composites Based on the Best Process Parameters of Laser Power, Scanning Speed and Hatch Distance.

Silicon carbide (SiC) exhibits intriguing thermo-physical properties such as higher heat capacity and conductivity, as well as a lower density than Ti6Al4V(ELI). These properties make SiC a good candidate for the reinforcement of Ti6Al4V(ELI) with respect to its use as a heat shield in aero turbines to increase their efficiency. The traditional materials used in aircraft structures were required to have a combination of good mechanical properties such as strength, stiffness, and hardness and low weight, as well as low thermo-physical properties such as coefficient of thermal expansion (CTE) and thermal conductivity. The alloy Ti6Al4V(ELI) has a density of 4.45 g/cm3, which is lower than that of structural steel (7.4 g/cm3) and higher than that of aluminium (2.5 g/cm3). Lower density benefits light weighting. Aluminium is the lightest of the traditional materials used but has relatively low strength. The CTE of SiC of 4.6 × 10-6/K is lower than that of Ti6Al4V(ELI) of 8.6 × 10-6/K, while the density of SiC of 3.21 g/cm3 is lower than that of Ti6Al4V(ELI) of 4.45 g/cm3. Therefore, from the theory of composites, SiC/Ti6Al4V(ELI) composites are expected to have lower densities and CTEs than those of Ti6Al4V(ELI), thus providing for lightweighting and less thermal related buckling or separation at their joints with carbon/epoxy resin panels. The specific strength, stiffness, and Knoop hardness of SiC of 75-490 kNm/kg, 132 MNm/kg, and 600-3800 GPa, respectively, are generally larger than those of Ti6Al4V(ELI) of 211 KNm/kg, 24 MNm/kg, and 880 GPa, respectively. Therefore, investigating reinforcement of Ti6Al4V(ELI) with SiC particles is worthwhile as it will lead to the formation of composites that are stronger, stiffer, harder, and lighter, with lower values of CTE. For additive manufacturing, this requires initial studies to optimise the process parameters of laser power and scanning speed for single tracks. To print single tracks in the present work, different laser powers ranging from 100 W to 350 W and scanning speeds ranging from 0.3 m/s to 2.7 m/s were used for different SiC volume fraction values of values. To print single layers, different values of hatch distance were used together with the best values of laser power and scanning speed determined elsewhere by the authors for different volume fractions of SiC. Through optical microscopy, the built tracks and their cross sections were examined. By using laser power and scanning speeds of 200 W and 1.2 m/s, and 150 W and 0.8 m/s, respectively, the best tracks at 5% and 10% volume fractions were obtained, whereas the best tracks at 25% volume fraction were achieved using a laser power of 200 W and a scanning speed of 0.5 m/s. Furthermore, the results showed that the maximum SiC volume percentage of 30% resulted in limited or no penetration. Therefore, it is concluded from the study that parts with improved mechanical properties can be produced at SiC volume fractions ranging from 5% to 25%, while parts produced at the high volume fraction of 30% would have unacceptable mechanical qualities for the final part.