Additive manufacturing (AM) is an emerging process that has been extremely improved in terms of technology and application in recent years. In this technology review, new industrial improvements in laser powder bed fusion (LPBF) of metals are discussed. LPBF has the lowest build rate among all AM processes that produce metals such as electron beam powder bed fusion, direct energy deposition, binder jetting and sheet lamination. The findings of the current research show that the most innovations and future directions of LPBF printers are toward increasing the speed of the process by using interchangeable feedstock chamber, closed-loop control powder handling, automated powder sieving, multi-layer concurrent printing, 2-axis coating and multi powder hoppers. To increase the speed of the process, the new improvements for transferring time and using fast lasers are presented. Another innovation in the building of LPBF printers is enhancing part quality by improving lasers with the shorter beam diameter, multi-lasers, uniform inert gas flow, accurate positioning systems, using high vacuum systems and using sensors and automation.

A review of technological improvements in laser-based powder bed fusion of metal printers

Study of residual stress in selective laser melting of Ti6Al4V

Laser powder bed fusion (LPBF) is one of the most promising additive manufacturing technologies. It has been utilized in the high level and stringent requirements fields such as aerospace and biomedicine industries. However, compared to subtractive manufacturing, the relatively poor surface finish and dimensional accuracy of the LPBF part hamper its widespread applications. In this work, a data-driven framework is proposed to obtain optimal process parameters of LPBF to get satisfactory surface roughness and dimensional accuracy. The effects of key process parameters on the surface roughness and dimensional accuracy are analyzed. Specifically, a machine learning technique is defined to reflect the dimensional accuracy and the surface roughness of the as-built products under different combinations of process parameters. Considering the limited experimental data, a machine learning model is introduced to predict the surface roughness and dimensional accuracy in the whole process parameters space. Then the predicted value is considered as an objective value when using the whale optimization algorithm (WOA) to search the global optimal process parameters. In the verification experiments, LPBF parts with better surface finish and dimensional accuracy were obtained with optimized process parameters which indicates that the optimized results are consistent with the experimental results.

Optimization of surface roughness and dimensional accuracy in LPBF additive manufacturing

Recent advances in Ti-6Al-4V additively manufactured by selective laser melting for biomedical implants: Prospect development

A novel approach based on the elastoplastic fatigue damage and machine learning models for life prediction of aerospace alloy parts fabricated by additive manufacturing

In this paper, we printed Ti-6Al-4V SLM parts based on Taguchi design of experiment and related standards to measure and compare hardness with different mechanical properties that were obtained in our previous research such as density, strength, elongation, and average surface. Then the effect of process parameters comprising laser power, scan speed, hatch space, laser pattern angle coupling, along with heat treatment as a post-process, in relation to hardness was analysed. The relation of measured factors with each other was also studied and related mechanisms were discussed in depth. The original contribution in this paper is in producing a large and precise dataset and the comparison with mechanical properties. Another contribution is related to the analysis of process parameters in relation to hardness and explaining them by rheological phenomena. The results showed an interesting similarity between hardness and density which is highly related to the formation of the melting pool and porosities within the process.

The effect of SLM process parameters on density, hardness, tensile strength and surface quality of Ti-6Al-4V

When reporting surface quality, the roughest surface is a reference for the measurements. In LPBF due to recoil pressure and scan movement, asymmetric surface is shaped, and surface roughness has different values in different measurement orientations. In this research, the influence of the laser powder bed fusion (LPBF) process parameters on surface tension and roughness of Ti-6AI-4 V parts in three orientations are investigated. To improve the mechanical properties, heat treatment was carried out and added to the designed matrix to generate a comprehensive data set. Taguchi design of experiment was employed to print 25 samples with five process parameters and post-processing. The effect and interaction of the parameters on the formation of surface profile comprising tension, morphology and roughness in various directions have been analysed. The main contribution of this paper is developing a model to approximate the melting pool temperature and surface tension based on the process parameters. Other contributions are an analysis of process parameters to determine the formation and variation of surface tension and roughness and explain the governing mechanisms through rheological phenomena. Results showed that the main driving factors in the variation of surface tension and formation of the surface profile are thermophysical properties of the feedstock, rheology and the temperature of the melting pool. Also, the results showed that while the value of surface tension is the same for each test case, morphology and the value of roughness are different when analysing the surface in perpendicular, parallel and angled directions to laser movement.

/pdf/a-study-on-surface-morphology-and-tension-in-laser-powder-13ef5lkj5r.pdf

A study on surface morphology and tension in laser powder bed fusion of Ti-6Al-4V

This research aims to identify how meltpool temperature is determined by process parameters in Laser-Based Powder Bed Fusion (LB-PBF) and the effect of meltpool temperature and heat treatment temperature on microstructure and tensile properties. The study illustrates how crystallographic features in 316L stainless steel were developed in response to the meltpool temperature and induced energy density of LB-PBF manufacture, and by post manufacture heat treatment. For this research, 25 samples based on a Taguchi Design of Experiments (DoE) with five parameters over five levels were printed. To improve precision, the DoE was repeated three times and a total of 75 samples were produced. A thermophysical-based analytical model was developed to measure the meltpool temperature and subsequently surface tension of the liquid in melting zones. Then, a statistical method was used to identify the effective process parameters in tensile properties including ultimate strength, fracture strain and toughness. The microstructural evaluation and crystallographic features were presented to identify the governing mechanisms for the discussed phenomena. This result verifies that the meltpool temperature is a driving factor for the microstructural evolution and observed crystallographic features. Results showed that samples with lower meltpool temperatures have smaller grain sizes, superior strength and toughness properties. The crystallographic analysis showed the weak texture and anisotropic properties are dominant by the preferred orientation growth. The geometrically necessary boundary values were also found to be a driving factor for fracture strain. The originality of this paper is identifying the effect of process parameters on meltpool temperature using an analytical model that is developed based on the thermophysical properties of the feedstock. Characterizing the effect of meltpool temperature in crystallographic features are also another contribution of this paper.

https://dro.deakin.edu.au/eserv/DU:30151664/farabi-ontheroleofprocess-2021.pdf

On the role of process parameters on meltpool temperature and tensile properties of stainless steel 316L produced by powder bed fusion

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The effect of SLM process parameters on density, hardness, tensile strength and surface quality of Ti-6Al-4V

A study on surface morphology and tension in laser powder bed fusion of Ti-6Al-4V

On the role of process parameters on meltpool temperature and tensile properties of stainless steel 316L produced by powder bed fusion