Laser Melting Process Parameters Research Articles

Determination of selective laser melting process parameters of tungsten carbide powders coated with nickel via electroless plating for improved interface properties

Tungsten carbide powders are commonly used at various industrial applications due to their high hardness. However, these powders may exhibit low binding and processing challenges without a binder. Therefore, various binding methods such as electroless Ni coating are used to hold WC powders together, increase their processability and improve the mechanical properties of the final product. Electroless Ni plating plays an important role in the use of WC powders, especially in processes such as selective laser melting. The structural, tribological, and mechanical properties of parts manufactured by SLM method are significantly influenced by the parameters employed in the process. Hence, optimizing process variables is essential to unlock the full potential of this advanced manufacturing technique. The main objective of this study was to identify the optimum process parameters for the SLM method of WC-Ni composite powders, which were prepared by coating WC powder materials with electroless Ni. Experimental investigations focused on analyzing the laser power, scanning speed, and hatch spacing parameters. The effects of these parameters on the mechanical and tribological properties of WC-Ni composite material were investigated using microhardness tester, tribometer device, optical microscope, 3D optical profilometer and scanning electron microscope. Eventually, it was determined that the manufacturing parameters employed in the SLM method had a significant impact on relative density, microstructure, surface roughness, hardness, and tribological properties. Samples exhibited a relative density of nearly 99%, and the highest observed hardness value was 1962 HV. This article supports a specialized SLM manufacturing process developed specifically to enhance durability and performance across a broad spectrum of industrial applications through interface improvement and the optimization of manufacturing parameters.

Effects of selective laser melting process parameters on 3D-printing of Ti6Al4V/ST316L composite material and their optimization using response surface methodology

The mechanical properties of Ti6Al4V and ST316L bone implants make them superior to natural bone, which results in fewer contact points with the bone. Different manufacturing processes, such as selective laser melting (SLM), may result in different mechanical properties between Ti-6Al-4V and ST316L implants. Sustainable development for the composite implants was optimized (SLM) in this study to minimize their compressive strength and Young's modulus. A three-dimensional printing process using SLM was optimized based on laser power, hatch distance, laser velocity, and ST316L weight percentage. Composite implants made from titanium alloys and steel alloys were evaluated using response surface methodology (RSM). ST316L composition has been found to influence the mechanical properties of composites in a significant manner, based on the results of parameter optimization. Using Ti6Al4V/ST316L as a biomaterial in knee joint prostheses is possible.

Comprehensive optimization of selective laser melting process parameters for microstructure, density, hardness, and tribological performance of pure copper

This study is concerned with the optimisation of the processing parameters for the selective laser melting (SLM) of pure copper. The influence of these parameters on the microstructure, density and mechanical properties of copper samples produced by SLM is investigated in detail. Taguchi analysis is used to assess the importance of key building parameters including layer thickness, laser spot size and hatch distance on density. In addition, ANOVA is used to describe the contribution of each parameter to the density. The results reveal that layer thickness is the most effective parameter on density with an impact rate of 88.86%. Contrary to this situation, it appears that the effect of laser spot size and hatch distance on the density is quite limited, with an impact rate of 2.57% and 0.10%, respectively. Optimum results, including a relative density of 95.4% and a hardness of 63 HV, are achieved under specific parameters: a layer thickness of 0.03 mm, a hatch distance of 110 mm and a laser spot size of 70?m. This study provides a valuable insight into SLM processing of pure copper and offers practical recommendations for optimising the parameters used.

Quality assurance thermophysical aspects of highly porous implants with cellular structure obtained by selective laser melting

Selective laser melting (SLM) is an additive manufacturing process that involves the layer-by-layer construction of a three-dimensional object by local melting of a powder layer based on a prepared CAD model. This technology makes it possible to manufacture products of complex configuration, including internal channels of complex geometry. Such products include personalized highly porous implants, which are subject to very strict requirements in the field of elastic and strength properties, ensuring their compliance with the properties of the biological objects being replaced. The quality of highly porous cellular products formed by the selective laser melting method based on metal powder compositions is determined by a significant number of factors, the combined influence of which is difficult to control. At the same time, the structure and mechanical properties of highly porous cellular materials (HPCM) obtained by laser synthesis are largely determined by the melt bath shape stability, which depends on the ability of local heat dissipation, which in turn is determined by the fused product geometry. Under these conditions, simulation of thermal processes, including the prediction of the part fusion temperature modes, is of paramount importance. This study focuses on the numerical analysis of the powder layer thermophysical parameters during the laser melting process, which is difficult to analyze by direct measurements, and a computational model based on COMSOL Multiphysics has been created to predict the melt bath temperature field. The numerical model made it possible to quantify the influence of the selective laser melting process parameters (laser power and scanning speed) in combination with the choice of material and topology of the part on the temperature fields formation to determine the process technological parameter and the features of creating geometry for additive manufacturing, which make it possible to obtain products of proper quality. Cellular implants based on Ti6Al4V powder have been grown by selective laser melting.

Multi-objective optimization to specify optimal selective laser melting process parameters for SS316 L powder

PurposeThis paper adopts a modified Taguchi approach to develop empirical relationships to the performance characteristics (output responses) in terms of process variables and demonstrated their validity through comparison of test data. The method suggests a few tests as per the orthogonal array and provides complete information for all combinations of levels and process variables. This method also provides the estimated range of output responses so that the scatter in the repeated tests can be assessed prior to the tests.Design/methodology/approachIn order to obtain defect-free products meeting the required specifications, researchers have conducted extensive experiments using powder bed fusion (PBF) process measuring the performance indicators (namely, relative density, surface roughness and hardness) to specify a set of printing parameters (namely, laser power, scanning speed and hatch spacing). A simple and reliable multi-objective optimization method is considered in this paper for specifying a set of optimal process parameters with SS316 L powder. It was reported that test samples printed even with optimal set of input variables revealed irregular shaped, microscopic porosities and improper melt pool formation.FindingsFinally, based on detailed analysis, it is concluded that it is impossible to express the performance indicators, explicitly in terms of equivalent energy density (E_0ˆ*), which is a combination of multiple sets of selective laser melting (SLM) process parameters, with different performance indicators. Empirical relations for the performance indicators are developed in terms of SLM process parameters. Test data are within/close to the expected range.Practical implicationsBased on extensive analysis of the SS316 L data using modified Taguchi approach, the optimized process parameters are laser power = 298 W, scanning speed = 900 mm/s and hatch distance = 0.075 mm, for which the results of surface roughness = 2.77 Ra, relative density = 99.24%, hardness = 334 Hv and equivalent energy density is 4.062. The estimated data for the same are surface roughness is 3.733 Ra, relative density is 99.926%, hardness is 213.64 Hv and equivalent energy density is 3.677.Originality/valueEven though equivalent energy density represents the energy input to the process, the findings of this paper conclude that energy density should no longer be considered as a dependent process parameter, as it provides multiple results for the specified energy density. This aspect has been successfully demonstrated in this paper using test data.

The effect of selective laser melting process parameters and remelting scanning strategy on relative density and surface hardness of stainless steel 316L

Selective laser melting (SLM) process is the foremost metal additive manufacturing (AM) technology that precisely generates complex geometries from CAD files. Mechanical behavior of printed parts is greatly affected by printing parameters and defining the optimal values of the process parameters to enhance the mechanical properties of components is highly regarded. In this work, four different SLM parameters including scanning speed, laser power, hatch spacing and scan pattern angle were applied to manufacture SS316L parts. For investigating the effect of each parameter and their interactions on hardness and relative density, Taguchi L16 orthogonal array was employed. The influence of part geometry and remelting is also evaluated in order to optimize the hardness and relative density of components. The results exhibited that the laser scanning speed was the most predominant SLM parameter for investigated mechanical properties. Analyzing the regression formula obtained from the results showed that the optimum laser energy density resulted in a 0.37% and 5.38% increase compared to the lowest relative density and hardness, respectively. High remelting energy associated with low remelting scanning speed, caused an 8.5% and 17.9% rise in hardness of squares and triangles, respectively; however, it led 12.5% reduction in hardness for circles. Remelting caused a 2.32% reduction, 2.1% increase and 5.3% rise on relative density for circles, squares and triangles, respectively.

An Investigation into the Optimization of the Selective Laser Melting Process Parameters for Ti6Al4V Through Numerical Modelling

An Investigation into the Optimization of the Selective Laser Melting Process Parameters for Ti6Al4V Through Numerical Modelling

Optimization of Selective Laser Melting Process Parameters Via Taguchi's Methods and Gray Relational Analysis for 3D Printing of 18Ni‐300 Maraging Steel

Taguchi methods and gray relational analysis are used to determine optimal processing conditions for the selective laser melting (SLM) of 18Ni‐300 maraging steel. The following SLM process parameters are selected for optimization: laser power (P), scanning speed (v), and hatch spacing (h). Statistical analysis indicates that SLM parameter configuration no. 5 (275 W, 700 mm s−1, 0.08 mm) as most suitable for the simultaneous improvement of tensile strength, elongation (or ductility), hardness, and impact toughness. The order of influence of SLM parameters is identified as follows: . Samples with improved mechanical properties can be produced using configurations with higher linear energy density (). This is because the increased laser energy input facilitates complete melting of metal powder, as well as better interlayer bonding between melt pools. Higher can be achieved by either increasing P or decreasing v. Digital image correlation analysis indicates that tensile test samples with higher porosity exhibit lower ductility due to its inability to accommodate plastic strain accumulation for prolonged durations. Fractography analysis indicates that during tensile loading, cracks will nucleate around the pore perimeter and propagate via microvoid coalescence. Fracture will occur at regions with higher porosity due to it having multiple crack initiation sites.

Laser powder bed fusion of 316L stainless steel/Al2O3 nanocomposites: Taguchi analysis and material characterization

This work deals with the mechanical properties and microstructure of additively manufactured (AM) 316L stainless steels strengthened with Al2O3 nanoparticles. At first, the critical processing parameters of laser powder bed fusion (LPBF) were optimized using Taguchi analysis in terms of laser power (180–210 W), scan speed (90–270 mm/s), hatch space (200–300 µm), and layer thickness (20–40 µm) to obtain materials with the highest density. Based on the modeling predictions and experimental findings, energy density was determined as a critical factor in controlling the integrity of deposited structures and their cracking behavior. The microstructural features and mechanical properties of the produced nanocomposites were characterized afterward. Grain structural aspects and crystallographic textural evolution across different sections of the printed nanocomposites, along with the distribution of reinforcing alumina nanoparticles, were studied using optical microscopy (OM), channeling contrast field emission-scanning electron microscopy (FE-SEM) imaging, electron backscattering diffraction (EBSD), and transmission electron microscopy (TEM) analyses. The fabricated materials' mechanical properties were also evaluated using indentation micro-hardness testing across the printed cubic structures. Trends revealed a considerable grain structural refinement down to the nanometric scale by incorporation and uniform distribution of alumina nanoparticles depending on the selective laser melting (SLM) processing parameters. This consequently improved the hardness of the materials up to around 270 Vickers. The role of unstable Al2O3 nanoparticles would directly strengthen the stainless steel metal matrix by generating new in-situ agents during LPBF. Moreover, the crucial indirect influence was discovered in controlling the involved solidification mechanisms and subsequent microstructural features.

Experimental, computational, and data-driven study of the effects of selective laser melting (SLM) process parameters on single-layer surface characteristics

Experimental, computational, and data-driven study of the effects of selective laser melting (SLM) process parameters on single-layer surface characteristics

Microstructure evolution and corrosion behavior of the novel maraging stainless steel manufactured by selective laser melting

The effects of selective laser melting (SLM) processing parameters on the microstructure and corrosion behavior of CX (Corrax) stainless steel were investigated via microstructure characterization, electrochemical tests and passive layer analysis. Different processing parameters (including the laser power of 150-170 W and scanning speed of 0.9–1.3 m·s−1) were used to manufacture the SLMed CX samples. The results revealed that the relative density of SLMed CX samples reached above 96%, which exhibited a higher densification effect. Besides that, the SLMed CX samples had the high-density of geometrically necessary dislocations (GNDs, ranging from 9.63 × 1014 m−2 to 9.86 × 1014 m−2), and the average grain size mainly distributed within 2 μm, in which the sample S1 (manufactured with P = 170 W, V = 0.9 m·s−1) exhibited the smallest average grain size of 1.1 μm. The proportion of Σ3 boundaries varied slightly in samples, ranging from 4.13% to 4.87%, which was positively correlated with the content of recrystallization. In addition, the electrochemical test results indicated that the scanning speed had a greater effect on corrosion resistance of SLMed CX samples, comparing with the laser power. The sample S1 exhibited both the largest relative density of 99.13% and the best corrosion resistance, including the largest value of corrosion potential (ECorr, −259 ± 12mVSCE) and the lowest value of corrosion current density (ICorr, 0.484 ± 0.012 μA·cm−2). The corrosion resistance of SLMed CX sample was ascribed to the synergistic effects of its relative density, grain size, grain boundary character distribution and GNDs density, and these influence factors were also discussed in detail.

Effects of selective laser melting process parameters on the accuracy of the intaglio surface of maxillary removable partial denture frameworks

PurposeThis in vitro study aims to explore the effects of selective laser melting (SLM) process parameters on the accuracy of the intaglio surface of cobalt–chromium alloy (Co–Cr), commercially pure titanium (CP Ti) and titanium alloy (Ti–6Al–4V) maxillary removable partial denture (RPD) frameworks and optimize these process parameters.Design/methodology/approachMaxillary RPD framework specimens designed on a benchmark model were built. The process parameters, including contour scan speed and laser power, infill scan speed and laser power, hatch space, build orientation and metallic powder type, were arranged through the Taguchi design. Three-dimensional deviations of the clasps area, connector area and overall area of maxillary RPD frameworks were analyzed by using root mean square (RMS) as a metric. One-way analyses of variance with the above RMSs as the dependent variable were carried out (α = 0.05).FindingsMaxillary RPD frameworks built horizontally had a more accurate intaglio surface than those built at other orientation angles; CP Ti or Ti–6Al–4V maxillary RPD frameworks had a more accurate intaglio surface than Co–Cr ones; the Maxillary RPD framework built with a higher infill scan speed and lower infill laser power had the more accurate intaglio surface than the one built with other levels of these two process parameters.Originality/valueA novel benchmark model for evaluating the accuracy of the intaglio surface of maxillary RPD frameworks manufactured by SLM is proposed. The accuracy of the intaglio surface of maxillary RPD frameworks can be improved by adjusting SLM process parameters. The optimal setting of process parameters concerning the accuracy of the intaglio surface of maxillary RPD frameworks was given.

Robust prediction and validation of as-built density of Ti-6Al-4V parts manufactured via selective laser melting using a machine learning approach

It is well known that slight changes in selective laser melting (SLM) process parameters may alter the outcome of mechanical and physical properties of the as-built material in a drastic and haphazard fashion. To overcome this, reliable property prediction models are most pertinent. In this study, a machine learning approach based on Gaussian Process Regression (GPR) is proposed to predict the relative density of as-built Ti-6Al-4V alloy manufactured via SLM, based on the most common input process parameters such as laser power, scanning speed, hatch spacing, and layer thickness, as well as an integrated input of volumetric energy density. A most comprehensive test dataset to train and verify GPR models was retrieved from literature papers that extensively investigated mechanical and physical properties of additively manufactured Ti-6Al-4V alloy. GPR models with four different kernel functions were analyzed and exponential GPR model with optimized hyperparameters was chosen as the most viable model for predicting as-built density of Ti-6Al-4V alloy. A parametric multiple linear regression (MLR) model was also presented and serves as a benchmark. When inferences were made on newer publication data, the GPR model and the MLR model predicted the densities with mean absolute errors (MAE) of 1.12% and 5.22% respectively. The inferior performance of the MLR model compared emphasizes the need of non-parametric supervised learning technique for SLM. To truly demonstrate the effectiveness of the proposed GPR model in real-world metal AM jobs, 22 experimental samples were printed. Predictions made on all the samples, when compared to their actual density values, resulted in MAE of 0.27%. Clearly, creation of most comprehensive mined data, kernel selection, and rigorous validation and verification of GPR model make this study one of its kind and prove the GPR model's predictive dexterity and the potential impact in the world of additive manufacturing.

Influence of Selective Laser Melting Process Parameters on Microstructure and Properties of a Typical Ni-Based Superalloy

Influence of Selective Laser Melting Process Parameters on Microstructure and Properties of a Typical Ni-Based Superalloy

The interaction effect of process parameters on the phase transformation behavior and tensile properties in additive manufacturing of Ni-rich NiTi alloy

In this work, response surface methodology (RSM), as a reliable and cheap prediction tool, was developed to establish a quadratic regression model between selective laser melting (SLM) process parameters and the martensite transformation temperatures (MTTs) of SLM-NiTi alloys during SLM process. In the case of martensite start temperature (Ms) and austenite finish temperature (Af), analyzing the result of RSM illustrated that the average error percentage between the predicted and experimental results are within 7.42 ± 0.45% and 3.83 ± 0.23%, respectively. Besides, we show that the interaction of laser power (P) and scanning speed (v) have a remarkable impact not only on MTTs but also on tensile properties and tensile recovery strain of SLM-fabricated NiTi samples. With the decrease of P and the increase of v, the Ms and Af decrease, respectively. The tensile experimental results showed that the group of 150 W samples equipped with high elongation, in which the highest elongation up to 12 ± 0.4%, but the high tensile recovery strain was presented in the 100 W series. This study provided a new-fangled insight for how process parameters modulate phase transformations and mechanical properties in the SLM fabricated NiTi, which can be conducted to target mechanical properties for different applications.

Investigation of the Influence of Selective Laser Melting Process Parameters on the Microstructure and Mechanical Properties of 18Ni-300 Maraging Steel

The influence of SLM process parameters (i.e. laser power, scanning speed, and hatch spacing) on the microstructure and mechanical properties of 3D printed 18Ni-300 maraging steel was investigated. In experiments on 3D printed scan tracks, better fusion of powder material was achieved in parameter configurations with higher linear energy density (i.e. LED ≥ 375.00 J m-1). A higher LED indicates that more laser energy is transferred to the powder material, resulting in complete melting of the powder and the creation of a microstructure with less defects. In experiments on fully built samples, higher relative density was achieved when the hatch spacing was increased or the scanning speed was decreased. Fully built samples produced using parameter configuration B-2 (300 W, 700 mm s-1, 0.10 mm) have higher relative density and ultimate tensile strength as compared to the other parameter configurations.

Improving the Pitting Corrosion Performance of Additively Manufactured 316L Steel Via Optimized Selective Laser Melting Processing Parameters

Improving the Pitting Corrosion Performance of Additively Manufactured 316L Steel Via Optimized Selective Laser Melting Processing Parameters

Microstructural evolution and characterization of AlSi10Mg alloy manufactured by selective laser melting

Extensive investigation of the influence of the selective laser melting (SLM) process parameters on the evolution of the molten pool is of great significance to understanding microstructure control and SLM-fabricated part quality. This study focuses on the influence of the scan speed inducing the laser energy changes on the microstructural evolution, texture and phase of AlSi10Mg alloy during SLM. The microstructural evolution and characterization of the SLM-manufactured AlSi10Mg alloy were investigated by scanning electron microscope/electron backscattered diffraction (SEM/EBSD), transmission electron microscope/scanning transmission electron microscope (TEM/STEM) and X-rays diffraction (XRD). The microstructural features of the sample have shown that the primary cellular dendritic structure sizes in the coarse grain zones were about three times larger than those in fine grain zones due to the different cooling rates. Besides, the microstructure boundary contains a eutectic mixture of Al and Si while the matrix is mainly composed of α-Al. The interplanar distance between the fringes are measured as 3.84 Å and 2.86 Å corresponding to the (110) plane of Si and (110) plane of Al. On the other hand, the hardness measurement data show that the sample due to the high scan speed is larger than that of the low scan speed. Meanwhile, the (001) Al texture strength of samples in the low scan speed is stronger than those in the high scan speed. Finally, the XRD analysis reveals that no significant differences are found in the intensity of (111) α-Al, while the intensity of the (200) α-Al presents a difference because of the grain orientation and size.

Ni-based alloy 713C manufactured by a selective laser melting method: characteristics of the microstructure

PurposeThe purpose of this paper is to obtain high-temperature-resistant material with high density and to conduct microstructural investigations of 3D-printed Ni-based alloy 713C specimens.Design/methodology/approachHigh-density specimens of Ni-based alloy 713C were obtained by the optimizing selective laser melting (SLM) process parameters and an X-ray diffraction (XRD) analysis confirmed the occurrence of γ and γ′ phases and the presence of carbides in the SLM-manufactured Ni-based alloy 713C. The analysis of electron backscatter diffraction (EBSD) studies suggested a preferred 〈100〉 direction orientation and low angle misorientation for the SLM specimens.FindingsThe high-density specimens of Ni-based alloy 713C were obtained by the optimized SLM process parameters. XRD analysis confirmed the presence of γ and γ′ phases and carbides in the SLM-manufactured Ni-based alloy 713C. Analysis of EBSD studies suggested a preferred 〈100〉 direction orientation and low angle misorientation for the SLM specimen.Originality/valueIn this study, 3D-printed Ni-based alloy 713C with a high density of 99% was obtained for the first time, to the best of the authors’ knowledge.

Effects of processing parameters and post-process heat treatment on selective laser melted SiC/AlSi10Mg composites

In this letter, SiC/AlSi10Mg composites have been fabricated under different selective laser melting (SLM) processing parameters, and then heat-treated for the microstructure and property tailoring. The resulted effects on densification responses, phase constituents, microstructure evolution and mechanical properties of the SiC/AlSi10Mg composites are analyzed and discussed in detail. The results showed that the highest densification and tensile strength were achieved due to the precipitation hardening of Si and Mg2Si, dispersion strengthening of SiC and solid-solution strengthening of α-Al. After kept at 300 °C for 2 h, the ductility of the sample improved significantly with certain sacrifice of tensile strength due to the precipitation of β-Al4.5FeSi, coarsening of Si particles and weakened solid-solution effects from supersaturated α-Al.