Influence of the Scanning Strategy on the Microstructure and Mechanical Properties in Selective Electron Beam Melting of Ti–6Al–4V

Scharowsky, T.; Juechter, Vera; Singer, Robert F.; Körner, Carolin

doi:10.1002/adem.201400542

Cited by 66 publications

(28 citation statements)

References 21 publications

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“…For example, the α lamellar spacing can vary significantly along the build direction [13,14], since the local thermal conditions are affected by the position within the part relative to the heat flux through the build plate. Scharowsky et al have also shown that in EBM the lamellar plate spacing increases with the energy volume density of the heat source [30].…”

Section: Introductionmentioning

confidence: 96%

“…In contrast, in finer scale AM processes like EBM the transformation microstructure is considered to be more homogeneous because of greater thermal field overlap between multiple tracks and, particularly in the case of EBM, where high build temperatures are used [7,12,8]. However, it is still known to be sensitive to the part geometry [7,11], beam scan control algorithms [11,14,30] build temperature [12] and height [7,13,14]. For example, the α lamellar spacing can vary significantly along the build direction [13,14], since the local thermal conditions are affected by the position within the part relative to the heat flux through the build plate.…”

Section: Introductionmentioning

confidence: 99%

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Automated image mapping and quantification of microstructure heterogeneity in additive manufactured Ti6Al4V

Zhao

Davis

et al. 2019

Materials Characterization

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In Additive Manufacturing AM, each volume of material experiences a complex thermal history due to both short-range effects, from the repeated overlap of the thermal field from each heat source pass, and long-range variation in the thermal boundary conditions, related to the part geometry and build height. With an  +  alloy, like Ti64, this can lead to significant local variation in the transformation microstructure, which can contribute to heterogeneity in the mechanical properties of a component. In order to better understand the transformation microstructure variability in AM parts, an automated microstructure analysis tool has been developed, and tested against independently measured data, that can accurately map the inter-lamellar spacing of the  phase and spheroidicity of the  phase, at both high resolution and over large distances. The approach used was based on automated batch image analysis of thousands of image tiles obtained using a mapping function in a high-resolution SEM with a scanning stage. Within a practical operating range of drift in the microscope parameters (e.g. working distance, detector contrast) the errors in the measurements were found to be minimal (< 3%). Results are discussed from applying the method to two example case studies from different ends of the AM spectrum; selective Electron Beam Melting (EBM) and Wire-Arc Additive Manufactured (WAAM). In the former case this revealed considerable drift in the microstructure with build height and geometry, but little short-range variation, whereas with the WAAM process more severe short range microstructural gradients associated with HAZ banding were fully quantified.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Automated image mapping and quantification of microstructure heterogeneity in additive manufactured Ti6Al4V

Zhao

Davis

et al. 2019

Materials Characterization

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“…Li et al (2012) showed that increasing the energy density (high power and low scan speed) allows mitigating or avoiding this kind of defect. Regarding EBM, different authors (Scharowsky et al (2015), Zaeh and Kahnert (2009), Puebla et al (2012), Tammas-Williams et al (2015) and Biamino et al (2011) studied the importance of process parameters and scanning strategy of part density, pore morphology and part performances.…”

Section: Processmentioning

confidence: 99%

Process defects andin situmonitoring methods in metal powder bed fusion: a review

Grasso

Colosimo

2017

Meas. Sci. Technol.

617

246

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Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and stability still represents a barrier for the industrial breakthrough. The most relevant metal AM applications currently involve industrial sectors (e.g., aerospace and bio-medical) where defects avoidance is fundamental. Because of this, there is the need to develop novel in-situ monitoring tools able to keep under control the stability of the process on a layer-by-layer basis, and to detect the onset of defects as soon as possible. On the one hand, AM systems must be equipped with in-situ sensing devices able to measure relevant quantities during the process, a.k.a. process signatures. On the other hand, in-process data analytics and statistical monitoring techniques are required to detect and localize the defects in an automated way. This paper reviews the literature and the commercial tools for insitu monitoring of Powder Bed Fusion (PBF) processes. It explores the different categories of defects and their main causes, the most relevant process signatures and the in-situ sensing approaches proposed so far. Particular attention is devoted to the development of automated defect detection rules and the study of process control strategies, which represent two critical fields for the development of future smart PBF systems.

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“…Changing process parameters such as laser power and scanning parameters, specifically scanning speed and its effects on energy density, has been shown to cause a considerable change in the grain structure (Gong et al, 2014b), the phases present (including the promotion of metastable phase formation), their distribution within the microstructure (Scharowsky et al, 2015), and tendencies for defect generation (Zhong et al 2015) in AM parts (Liang et al, 2014a(Liang et al, , 2014b. The variation in the temperature gradient in the melt pool result in variation in the solidification rate, resulting in concurrent variations in microstructure, including phase stability (Marya et al, 2015).…”

Section: Anisotropy and Phase Stabilitymentioning

confidence: 99%

Powder-based additive manufacturing - a review of types of defects, generation mechanisms, detection, property evaluation and metrology

Taheri

Shoaib

Koester³

et al. 2017

IJASMM

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Powder-based additive manufacturing (AM) technologies have been evaluated for use in different fields of application (aerospace, medical, etc.). Ideally, AM parts should be at least equivalent, or preferably better quality than conventionally produced parts. Manufacturing defects and their effects on the quality and performance of AM parts are a currently a major concern. It is essential to understand the defect types, their generation mechanisms, and the detection methodologies for mechanical properties evaluation and quality control. We consider the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder based AM parts in this work. Methods of in-situ non-destructive evaluation and the influence of defects on mechanical properties and design considerations are also reviewed. Together, these provide a framework to understand the relevant machine and material parameters, optimise the process and production, and select appropriate characterisation methods.Abstract: Powder-based additive manufacturing (AM) technologies have been evaluated for use in different fields of application (aerospace, medical, etc.). Ideally, AM parts should be at least equivalent, or preferably better quality than conventionally produced parts. Manufacturing defects and their effects on the quality and performance of AM parts are a currently a major concern. It is essential to understand the defect types, their generation mechanisms, and the detection methodologies for mechanical properties evaluation and quality control. We consider the various types of microstructural features or defects, their generation mechanisms, their effect on bulk properties and the capability of existing characterisation methodologies for powder based AM parts in this work. Methods of in-situ non-destructive evaluation and the influence of defects on mechanical properties and design considerations are also reviewed. Together, these provide a framework to understand the relevant machine and material parameters, optimise the process and production, and select appropriate characterisation methods.Reference to this paper should be made as follows: Taheri, H., Shoaib, M.R.M., Koester, L., Bigelow, T.A., Collins, P.C. and Bond, L.J. (2017) 'Powder-based additive manufacturing -a review of types of defects, generation mechanisms, detection, property evaluation and metrology', Int. Institute of Aviation Technology conducting research on UAVs and designing and printing 3D parts for UAVs. His research interest areas include engineering mechanics, additive manufacturing and non-destructive testing.Lucas W. Koester received his PhD from the University of Nebraska at Lincoln studying wave propagation and scattering in polycrystalline media. His current and past research interests include wave propagation in polycrystalline media, defect scattering, and modelling with emphasis on additive manufacturing processes and materials.Powder-based additive...

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Influence of the Scanning Strategy on the Microstructure and Mechanical Properties in Selective Electron Beam Melting of Ti–6Al–4V

Cited by 66 publications

References 21 publications

Automated image mapping and quantification of microstructure heterogeneity in additive manufactured Ti6Al4V

Automated image mapping and quantification of microstructure heterogeneity in additive manufactured Ti6Al4V

Process defects andin situmonitoring methods in metal powder bed fusion: a review

Powder-based additive manufacturing - a review of types of defects, generation mechanisms, detection, property evaluation and metrology

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