Additive manufacturing (AM), also known as 3D printing or rapid prototyping, is gaining increasing attention due to its ability to produce parts with added functionality and increased complexities in ...geometrical design, on top of the fact that it is theoretically possible to produce any shape without limitations. However, most of the research on additive manufacturing techniques are focused on the development of materials/process parameters/products design with different additive manufacturing processes such as selective laser melting, electron beam melting, or binder jetting. However, we do not have any guidelines that discuss the selection of the most suitable additive manufacturing process, depending on the material to be processed, the complexity of the parts to be produced, or the design considerations. Considering the very fact that no reports deal with this process selection, the present manuscript aims to discuss the different selection criteria that are to be considered, in order to select the best AM process (binder jetting/selective laser melting/electron beam melting) for fabricating a specific component with a defined set of material properties.
Selective laser melting (SLM) is widely gaining popularity as an alternative manufacturing technique for complex and customized parts. SLM is a near net shape process with minimal post processing ...machining required dependent upon final application. The fact that SLM produces little waste and enables more optimal designs also raises opportunities for environmental advantages. The use of aluminium (Al) alloys in SLM is still quite limited due to difficulties in processing that result in parts with high degrees of porosity. However, Al alloys are favoured in many high-end applications for their exceptional strength and stiffness to weight ratio meaning that they are extensively used in the automotive and aerospace industries. This study investigates the windows of parameters required to produce high density parts from AlSi10Mg alloy using selective laser melting. A compromise between the different parameters and scan strategies was achieved and used to produce parts achieving a density of 99.8%.
Titanium alloys are an important material for several industries, despite being very energy intensive to produce. This study aims to maximize chip recyclability by adjusting the milling process and ...subsequent processing steps. The results show that the chip morphology determines the recyclability significantly. Also, a cleaning process is established to reduce chemical contamination. Based on the results a closed-loop material cycle for Ti–6Al–4V powder for additive manufacturing is presented. It is shown that the powder and material properties of printed samples are similar to those of conventional materials, while energy savings of up 77 % can be achieved.
In this paper, the recent progress on Ti6Al4V fabricated by three mostly developed additive manufacturing (AM) techniques-directed energy deposition (DED), selective laser melting (SLM) and electron ...beam melting (EBM)-is thoroughly investigated and compared. Fundamental knowledge is provided for the creation of links between processing parameters, resultant microstructures and associated mechanical properties. Room temperature tensile and fatigue properties are also reviewed and compared to traditionally manufactured Ti6Al4V parts. The presence of defects in as-built AM Ti6Al4V components and the influences of these defects on mechanical performances are also critically discussed.
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•Recent progresses in additively manufactured Ti6Al4V were reviewed.•Laser direct deposition, selective laser melting and electron beam melting were comparatively studied.•Processing-microstructure-tensile and fatigue properties relationship were established.•Effects of defects on mechanical properties were also addressed.
Additive manufacturing (AM), particularly Selective Laser Melting (SLM) has enabled development of lattice structures with unique properties. Through control of various parameters lattice structures ...can produce unique mechanical, electrical, thermal and acoustic properties, and have received much research attention. Despite the increasing volume of published data on the mechanical response of specific SLM lattice structures, there exists no overarching analysis. This work addresses this identified deficiency by providing a comprehensive summary of the experimental data reported on the mechanical response of SLM lattice structures. The design, fabrication and performance of SLM lattice structures are reviewed and the quality of data reported is analysed to inform best-practice for future studies. This comprehensive data summary enables meta-analysis of the reported mechanical performance of SLM lattice structures, providing insight into the bounds of their technical capabilities. Correlations were identified between the relative density and mechanical properties of many unit cell topologies consistent with the predictions of the Gibson-Ashby model, indicating its usefulness in describing and predicting the behaviour of SLM lattice structures. This review provides designers with a compiled resource of experimental data and design for AM tools to inform future design applications of SLM lattice structures and facilitates their further commercial adoption.
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•A review of the design, fabrication and mechanical performance of Selective Laser Melting (SLM) lattice structures.•Reported data on the mechanical performance and properties of a broad range of SLM lattice structures is compiled.•Meta-analysis of reported data allows insights into the applicability of the Gibson-Ashby model to SLM lattice structures.
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•Critical internal defects in additive manufactured parts were detected by CT.•FE analysis of CT data is efficacious in modeling stress concentration factor.•Defects near to boundary ...cause a higher stress concentration factor.•Regional re-melting scanning strategy is proposed for fatigue applications.
Components manufactured by maturing additive manufacturing techniques like selective laser melting (SLM) find potential competence in several applications especially in automotive and aerospace industries as well as in medical applications like customized implants. The manufactured parts possess better, or at least comparable, yield strength and tensile strength values accompanied with a reduced fracture strain. Though their fatigue performance in the as-built condition is impaired due to surface roughness, it can be sufficiently improved by post-process surface treatments. Even then, there exists a high fatigue scatter due to remnant porosity. Characterization of remnant porosity is necessary for a reliable component design to be employed for cyclic applications. Computed tomography has been used in this study to evaluate the influence of porosity-incited stress concentration on the corresponding fatigue scatter. Microscopic analysis, tensile tests, fatigue tests with continuous load increase and constant amplitudes as well as finite element analysis have been used for this purpose. Critical pore characteristics and a modification in the process scanning strategy have been recommended so that the components can be reliably used in fatigue-loaded applications.
•To have consistent results an average surface Sa was selected and measured as a target.•Artificial neural network was used as an accurate tool for characterizing the interaction and effect of ...parameters on the surface of SLM parts.•The effect of SLM process parameters and heat treatment on the values of average surface were modeled accurately.
In this paper, we propose a model to predict the average surface roughness (Sa) and analyse the effect of related process parameters on laser powder bed fusion (LPBF) selective laser melting (SLM) of Ti-6Al-4 V. The additive manufacturing (AM) process has various independent parameters that affect the quality of the produced parts and is complex to analyse. Although the process parameters can be selected separately in LPBF, they do however affect each other. Therefore, large adjustments of process parameters is not possible due to the negative effect they have on each other which can lead to problems such as cracks, balling, unmelted powders, porosity, and distortion. A range of process parameters using Taguchi L25 design of experiment (DOE) with five repetitions for each sample has been selected. Then, an artificial neural network (ANN) is applied to the model to predict the value of (arithmetical mean height)/(average surface roughness) (Sa). The selected processing parameters are laser power, scan speed, hatch spacing, laser pattern increment angle, and heat treatment (HT) condition. The present work revolves around ANN modeling and using a wide parameter range and a large number of test samples under ASTM standards as well as adding HT to the DOE to analyse the simultaneous effect of HT and changing process parameters on surface characteristics. A large and precise data set with high generality and reliability obtained by 3750 profilometries on 125 samples. The contribution of this paper is using ANN as an accurate tool in surface modeling and characterizing the effective parameters on the surface of LPBF parts. The existence phenomena and governing factors were explained by introducing new parametric mechanisms in rheology of melting pool. In AM of metals, the variation of average roughness in overlap of hatches can be 5–7 times higher than the centre of the track. Therefore, Sa was selected to have consistency in the measured roughness values. Results showed heat treatment above beta phase transus leads to a local flow of material at the surface causing an increase of Sa. The ranking of influential factors on Sa from the highest to the lowest was found to be: heat treatment > laser power > scan pattern angle > hatch space > scan speed.
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