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Reducing porosity in AlSi10Mg parts processed by selective laser melting

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Aboulkhair, Nesma T., Everitt, Nicola M., Ashcroft, Ian, Tuck, Chris·2014·Additive Manufacturing

Abstract

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%.

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Metadata

Authors
Aboulkhair, N. T., Everitt, N. M., Ashcroft, I., & Tuck, C.
Venue
Additive Manufacturing
Publisher
Elsevier BV
Published
2014-10
Volume
1-4
Pages
77-86
ISSN
  • 2214-7810 (ISSN-L)
  • 2214-8604
OpenAlex
W2057031580
Cited by
1,281
References
0
FWCI
49.09
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Reducing porosity in AlSi10Mg parts processed by selective laser melting. https://app.cochat.ai/papers/10.1016/j.addma.2014.08.001
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Aboulkhair, N. T., Everitt, N. M., Ashcroft, I., & Tuck, C. (2014). Reducing porosity in AlSi10Mg parts processed by selective laser melting. Additive Manufacturing. https://doi.org/10.1016/j.addma.2014.08.001

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.