Virtual Development of Process Parameters for Bulk Metallic Glass Formation in Laser-Based Powder Bed Fusion

The development of process parameters and scanning strategies for bulk metallic glass formation during additive manufacturing is time-consuming and costly. It typically involves trials with varying settings and destructive testing to evaluate the final phase structure of the experimental samples. In this study, we present an alternative method by modelling to predict the influence of the process parameters on the crystalline phase evolution during laser-based powder bed fusion (PBF-LB). The methodology is demonstrated by performing simulations, varying the following parameters: laser power, hatch spacing and hatch length. The results are compared in terms of crystalline volume fraction, crystal number density and mean crystal radius after scanning five consecutive layers. The result from the simulation shows an identical trend for the predicted crystalline phase fraction compared to the experimental estimates. It is shown that a low laser power, large hatch spacing and long hatch lengths are beneficial for glass formation during PBF-LB. The absolute values show an offset though, over-predicted by the numerical model. The method can indicate favourable parameter settings and be a complementary tool in the development of scanning strategies and processing parameters for additive manufacturing of bulk metallic glass.

Residual stress, distortion, and porosity analysis of LED heat sink printed by SLM process using machine learning

In recent years, Light-emitting diodes (LEDs) are dominating the traditional lighting system. Besides mercury-free, they have small size, good break resistance and long life. Although LEDs are cool to touch, they generate a lot of unnecessary heat inside the gadgets. It is important to remove the heat using efficient thermal management component such as heat sink. Instead of using a conventional manufacturing process, selective laser melting (SLM) process is used to manufacture the heat sink. The quick solidification and various thermal regimes of the material during the SLM process led to the development of residual stresses that causes the part distortion and harm the mechanical properties of the component. The objective of the current study is to find the optimum value of laser power, scanning speed, and hatch spacing to bring down the residual stress and distortion in the SLM process to an acceptable range. Residual stress and distortion values of the heat sink are simulated using MSC Simufact additive and ANSYS Additive software. The conflicting nature between residual stress and porosity was observed. Hence, grey relation analysis was used to convert residual stress & porosity into a single objective. Optimum process parameters obtained were, laser power 80 (W), scanning speed 950 (mm/s), and hatch spacing of 70 (μm). The values of residual stress and porosity at optimum parameters were found to be 385.58 MPa and 12.21 %. Multiple regressions algorithm of machine learning was used to form a relationship between residual stresses and porosity. It was also observed that the magnitude of residual stress and distortion were low at lower energy densities and high at higher energy densities and the residual stress and porosities were high in the z-direction.

Work Hardening of Heat-Treated AlSi10Mg Alloy Manufactured by Single and Double Laser Selective Laser Melting: Effects of Layer Thickness and Hatch Spacing

The present study analyzed the microstructure and the mechanical properties of AlSi10Mg SLMed bars (10 × 10 × 300 mm) and billets (10 × 100 × 300 mm) before and after the direct aging at 200 °C for 4 h and the T6 heat treatment. The discussed results are compared to those obtained by the AlSi10Mg samples manufactured with the same geometry but using different process parameters (layer thickness higher than 40 μm and a hatch spacing lower than 100 μm) and also through the Quality Index (QI). These work conditions allow the obtaining of a microstructural variation and different tensile properties in as-built top samples. In both batches, the cycle time was 45 h and together with the preheated build platform at 150 °C, induced an increase of UTS (Ultimate Tensile Strength) and yield strength on the bottom rather than the top samples due to the aging phenomena. Upon completion of the direct aging heat treatment, the effects induced by the platform were cancelled, keeping a full cellular microstructure that characterized the as-built SLMed (Selective Laser Melted) samples. Moreover, the Considère criterion and the work hardening analysis showed that the failure occurs after the necking formation in some of the T6 heat-treated samples. In this last case, the Si eutectic network globularized into Si particles, causing a decrease of UTS (from around 400 MPa to 290 MPa) in favour of an increase of ductility up to 15% and reaching a QI in the range 400 ÷ 450 MPa. These values place these samples between the high-quality aluminium cast alloy and T6 heat-treated ones.

Simulation Study of Hatch Spacing and Layer Thickness Effects on Microstructure in Laser Powder Bed Fusion Additive Manufacturing using a Texture-Aware Solidification Potts Model

Microstructure control in the laser powder bed fusion additive manufacturing processes is a topic of major interest because of the submillimeter length scale at which the manufacturing process occurs. The ability to control the process at the melt pool scale allows for microstructure control that few other manufacturing techniques can match. The majority of work on microstructure control has focused on altering laser parameters to control solidification conditions (Ref (R.R. Dehoff, M.M. Kirka, W.J. Sames, H. Bilheux, A.S. Tremsin, L.E. Lowe, and S.S. Babu, Site Specific Control of Crystallographic Grain Orientation through Electron Beam Additive Manufacturing, Mater. Sci. Technol., 2014, 31(8), p 931–938. R. Shi, S.A. Khairallah, T.T. Roehling, T.W. Heo, J.T. McKeown, and M.J. Matthews, Microstructural Control in Metal Laser Powder Bed Fusion Additive Manufacturing Using Laser Beam Shaping Strategy, Acta Mater., 2020, 184, p 284–305, https://doi.org/10.1016/j.actamat.2019.11.053.)). Other machine parameters, besides the laser parameters, have also been shown to affect the microstructure of AM parts (Ref (N. Nadammal, S. Cabeza, T. Mishurova, T. Thiede, A. Kromm, C. Seyfert, L. Farahbod, C. Haberland, J.A. Schneider, P.D. Portella, and G. Bruno, Effect of Hatch Length on the Development of Microstructure, Texture and Residual Stresses in Selective Laser Melted Superalloy Inconel 718, Mater. Des., 2017, 134, p 139–150, https://doi.org/10.1016/j.matdes.2017.08.049. F. Geiger, K. Kunze, and T. Etter, Tailoring the Texture of IN738LC Processed by Selective Laser Melting (SLM) by Specific Scanning Strategies, Mater. Sci. Eng. A, 2016, 661, p 240–246, https://doi.org/10.1016/j.msea.2016.03.036.)). We propose an investigation of the effects of hatch spacing and layer thickness on microstructure development in laser powder bed fusion additive manufacturing. A Monte Carlo Potts model with textured solidification capabilities is used to study the effects of these parameters on a unidirectional scan strategy. The simulation results reveal substantial changes in grain morphology as well as texture. Additionally, EVP-FFT crystal plasticity simulations were performed to evaluate the effect of the microstructural shifts on mechanical response. The conclusions from this work elucidate the effects of these parameters on part microstructure as predicted by the texture-aware solidification Potts model and inform understanding of how bulk texture is predicted by the simulation approach.

Data-Driven Sensitivity Analysis for Static Mechanical Properties of Additively Manufactured Ti-6AL-4V

Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. A data-driven approach is proposed to investigate the influence of major fabrication parameters in the laser-based additively manufactured Ti-6Al-4V. Two separate laser-based Powder Bed Fusion (PBF) techniques, i.e., Selective Laser Melting (SLM) and Direct Metal Laser Sintering (DMLS) have been investigated and several data regarding the tensile properties of Ti-6Al-4V alloy with their corresponding fabrication parameters are collected from open literature. Statistical data analysis is performed for four fabrication parameters (scanning speed, laser power, hatch spacing, and powder layer thickness) and three post-fabrication parameters (heating temperature, heating time, and HIPed or not) which are major influencing factors and have been investigated by several researchers to identify their behavior on the static mechanical properties (i.e. yielding strength, ultimate tensile strength, and elongation). To identify the behavior of the relationship between the input and output parameters, both linear regression analysis and Artificial Neural Network (ANN) models are developed using 53 and 100 datasets for SLM and DMLS processes respectively. The linear regression model resulted in an average R squared value of 0.351 and 0.507 compared to 0.908 and 0.833 in the case of non-linear ANN modeling for SLM and DMLS based modeling, respectively. Both local and global sensitivity analyses are carried out to identify the important factors for future optimal design. Based on the current study, local sensitivity analysis suggests that SLM is most sensitive to laser power, scanning speed, and heat treatment temperature while DMLS is most sensitive to heat treatment temperature, hatch spacing, and laser power. In the case of DMLS fabricated Ti-6Al-4V alloy, laser power, and scan speed are found to be the most impactful input parameters for tensile properties of the alloy while heating time turned out to be the least affecting parameter. The global sensitivity analysis results can be used to tailor the alloy's static properties as per the requirement while results from local sensitivity analysis could be useful to optimize the already tailored design properties. Sobol's global sensitivity analysis implicates laser power, heating temperature, and hatch spacing to be the most influential parameters for alloy strength while powder layer thickness followed by scanning speed to be the prominent parameters for elongation for SLM fabricated Ti-6Al-4V alloy. Future work would still be needed to eradicate some of the limitations of this study related to limited dataset availability.

Process–Structure–Property Relationships of Copper Parts Manufactured by Laser Powder Bed Fusion

The process–structure–property relationships of copper laser powder bed fusion (L-PBF)-produced parts made of high purity copper powder (99.9 wt %) are examined in this work. A nominal laser beam diameter of 100 μm with a continuous wavelength of 1080 nm was employed. A wide range of process parameters was considered in this study, including five levels of laser power in the range of 200 to 370 W, nine levels of scanning speed from 200 to 700 mm/s, six levels of hatch spacing from 50 to 150 μm, and two layer thickness values of 30 μm and 40 μm. The influence of preheating was also investigated. A maximum relative density of 96% was obtained at a laser power of 370 W, scanning speed of 500 mm/s, and hatch spacing of 100 μm. The results illustrated the significant influence of some parameters such as laser power and hatch spacing on the part quality. In addition, surface integrity was evaluated by surface roughness measurements, where the optimum Ra was measured at 8 μm ± 0.5 μm. X-ray photoelectron spectroscopy (XPS) and energy-dispersive X-ray spectroscopy (EDX) were performed on the as-built samples to assess the impact of impurities on the L-PBF part characteristics. The highest electrical conductivity recorded for the optimum density-low contaminated coils was 81% IACS.

Process Optimization and Microstructure Analysis to Understand Laser Powder Bed Fusion of 316L Stainless Steel

The microstructural development of 316L stainless steel (SS) was investigated over a wide range of systematically varied laser powder bed fusion (LPBF) parameters, such as laser power, scan speed, hatch spacing and volumetric energy density. Relative density, melt pool width and depth, and the size of sub-grain cellular structure were quantified and related to the temperature field estimated by Rosenthal solution. Use of volumetric energy density between 46 and 127 J/mm3 produced nearly fully dense (≥99.8%) samples, and this included the best parameter set: power = 200 W; scan speed = 800 mm/s; hatch spacing = 0.12 mm; slice thickness = 0.03; energy density = 69 J/mm3). Cooling rate of 105 to 107 K/s was estimated base on the size of cellular structure within melt pools. Using the optimized LPBF parameters, the as-built 316L SS had, on average, yield strength of 563 MPa, Young’s modulus of 179 GPa, tensile strength of 710 MPa, and 48% strain at failure.