Research on High Layer Thickness Fabricated of 316L by Selective Laser Melting

Process Parameter Optimization for Laser Powder Bed Fusion of Fe-Si Alloy Considering Surface Morphology and Track Width of Single Scan Track

A laser power bed fusion (L-PBF) manufacturing process was optimized by analyzing the surface morphology and track width w of single scan tracks (SSTs) on Fe-3.4wt.%Si. An SST was evaluated under process conditions of laser power P, scan speed V, and energy density E = P/V. The SST surface shape was mainly affected by E; desirable thin and regular tracks were obtained at E = 0.3 and 0.4 J/mm. An L-PBF process window was proposed considering the optimal w of SST, and the appropriate range of E for the alloy was identified to be 0.24 J/mm to 0.49 J/mm. w showed a strong relationship with E and V, and an analytic model was suggested. To verify the process window derived from the appropriate w of SST, cubic samples were manufactured with the estimated optimal process conditions. Most samples produced had a high density with a porosity of <1%, and the process window derived from SST w data had high reliability. This study presents a comprehensive approach to enhancing additive manufacturing for Fe-3.4Si alloy, offering valuable insights for achieving high-quality samples without the need for time-intensive procedures.

Quality Quantification and Control via Novel Self-Growing Process-Quality Model of Parts Fabricated by LPBF Process

Laser Powder Bed Fusion (LPBF) presents a more extensive allowable design complexity and manufacturability compared with the traditional manufacturing processes by depositing materials in a layer-wised manner. However, the process variability in the LPBF process induces quality uncertainty and inconsistency. Specifically, the mechanical properties, e.g., tensile strength, are hard to be predicted and controlled in the LPBF process. Much research has recently been reported exploring the qualitative influence of single/two process parameters on tensile strength. In fact, mechanical properties are comprehensively affected by multiple correlated process parameters with unclear and complex interactions. Thus, the study on the quantitative process-quality model of the metal LPBF process is urgently needed to provide an enough-strength component via the metal LPBF process. Recent progress in artificial intelligence (AI) and machine learning (ML) provides new insight into quality prediction in terms of computational accuracy and speed. However, the predictive model quality through the traditional AL/ML is heavily determined by the training data size, and the experimental analysis can be expansive on LPBF. This paper explores the comprehensive effect of the tensile strength of 316L stainless-steel parts on LPBF and proposes a valid quantitative predictive model through a novel self-growing machine-learning framework. The self-growing framework can autonomously expand and classify the growing dataset to provide a high-accuracy prediction with fewer input data. To verify this predictive model of tensile strength, specimens manufactured by the LPBF process with different group process parameters (laser power, scanning speed, and hatch spacing) are collected. The experimental results validate the predicted tensile strengths within a less than 3% deviation.

Performance of High-Layer-Thickness Ti6Al4V Fabricated by Electron Beam Powder Bed Fusion under Different Accelerating Voltage Values

The electron beam powder bed fusion (EB-PBF) process is typically carried out using a layer thickness between 50 and 100 μm with the accelerating voltage of 60 kV for the electron beam. This configuration ensures forming accuracy but limits building efficiency. The augmentation of the accelerating voltage enlarges the molten pool due to the rise in penetrability, suggesting that a higher layer thickness can be used. Therefore, the effects of layer thickness and accelerating voltage were investigated simultaneously in this study to explore the feasibility of efficiency improvement. Ti6Al4V was fabricated by EB-PBF using layer thicknesses of 200 and 300 μm. Two accelerating voltage values of 60 and 90 kV were used to study their effects under expanded layer thickness. The results reveal that dense parts with the ultimate tensile strength higher than 950 MPa and elongation higher than 9.5% could be fabricated even if the layer thickness reached 300 μm, resulting in a building rate of up to 30 mm³/s. The expansion of the layer thickness could decrease the minimum bulk energy density needed to fabricate dense parts and increase the α platelet thickness, which improved the energy efficiency. However, expanding layer thickness had a significant negative effect on surface roughness, but it could be improved by applying augmented accelerating voltage.

Effect of Process Parameters and Layer Thickness on the Quality and Performance of Ti-6Al-4V Fabricated by Selective Laser Melting

To improve the quality of thick powder bed and realize the matching of thick powder bed and thin powder bed in the later stage, the influence of process parameters for the single-track, multi-layer fabrication, relative density, surface quality, defect, remelting, and boundary optimization performance of different layer thicknesses of Ti-6Al-4V fabricated by selective laser melting were investigated. It is more conducive to the stable forming of single-track when the point distance is half the diameter of the laser beam, and the exposure time is appropriately extended. The thin powder bed needs the corresponding point distance and exposure time under the laser power of 280–380 W to obtain high-density specimens. The thick powder bed needs to be able to ensure the formation of high-quality specimens under the smaller point distance and longer exposure time under higher laser power of 380 W. Both thick powder bed and thin powder bed will cause un-melted defects between molten pools, spheroidization defects caused by splashing, and microporous defects. The remelting process can significantly improve the surface quality of the formed specimen, but the surface quality of the thick powder bed is worse than that of the thin powder bed. The boundary quality of thick powder bed is worse than that of thin powder bed, and the boundary shape has a greater influence on the quality of the SLM forming boundary. Different strategies should be adopted to form the boundary of different shapes. Increasing the boundary count and increasing the laser power are more conducive to the improvement of boundary quality.

Turning Research of Additive Laser Molten Stainless Steel 316L Obtained by 3D Printing

This paper presents the characteristic of 316L steel turning obtained by 3D printing. The analysis of the influence of turning data on the components of the total cutting force, surface roughness and the maximum temperature values in the cutting zone are presented. The form of chips obtained in the machining process was also analyzed. Statistical analysis of the test results was developed using the Taguchi method.

Effect of Powder Feedstock on Microstructure and Mechanical Properties of the 316L Stainless Steel Fabricated by Selective Laser Melting

Additive manufacturing by selective laser melting (SLM) was used to investigate the effect of powder feedstock on 316L stainless steel properties include microstructure, relative density, microhardness and mechanical properties. Gas atomized SS316L powders of three different particle size distribution were used in this study. Microstructural investigations were done by scanning electron microscopy (SEM). Tensile tests were performed at room temperatures. Microstructure characterization revealed the presence of hierarchical structures consisting of solidified melt pools, columnar grains and multiform shaped sub-grains. The results showed that the SLM sample from the fine powder obtained the highest mechanical properties with ultimate tensile strength (UTS) of 611.9 ± 9.4 MPa and yield strength (YS) of 519.1 ± 5.9 MPa, and an attendant elongation (EL) of 14.6 ± 1.9%, and a maximum of 97.92 ± 0.13% and a high microhardness 291 ± 6 HV0.1. It has been verified that the fine powder (~16 μm) could be used in additive manufacturing with proper printing parameters.

Estimation of Residual Stress in Selective Laser Melting of a Zr-Based Amorphous Alloy

An accurate estimation of residual stresses is crucial to ensure dimensional accuracy and prevent premature fatigue failure of 3D printed components. Different from their crystalline counterparts, the effect of residual stress would be worse for amorphous alloys owing to their intrinsic brittleness with low fracture toughness. However, the generation of residual stress and its performance in 3D printed amorphous alloy components still remain unclear. Here, a finite element method combined with experiments and theoretical analyses was introduced to estimate the residual stress in selective laser melting of a Zr-based amorphous alloy. The results revealed that XY cross scanning strategy exhibits relatively low residual stress by comparison with X and Y strategies, and the residual stress becomes serious with increasing bar thickness. The residual stress, on the other hand, could be tuning by annealing or preheating the substrate. The above scenario is thoroughly understood according to the temperature gradient mechanism and its effect on microstructure evaluation.