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Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting

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dc.contributor.author Nzengue, ACB
dc.contributor.author Khumbulani, Mpofu, K
dc.contributor.author Mathe, Ntombizodwa R
dc.contributor.author Muvunzi, R
dc.date.accessioned 2024-07-10T07:55:08Z
dc.date.available 2024-07-10T07:55:08Z
dc.date.issued 2023-12
dc.identifier.citation Nzengue, A., Khumbulani, M., Mathe, N.R. & Muvunzi, R. 2023. Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting. <i>Journal of Materials Research and Technology.</i> http://hdl.handle.net/10204/13706 en_ZA
dc.identifier.issn 2238-7854
dc.identifier.issn 2214-0697
dc.identifier.uri https://doi.org/10.1016/j.jmrt.2023.11.233
dc.identifier.uri http://hdl.handle.net/10204/13706
dc.description.abstract Selective laser melting (SLM) SLM has gained interest in processing lightweight metals like aluminium alloys. The SLM processing remains challenging in finding the appropriate process parameters for the desired mechanical properties. Previous studies have used energy density formulas and heat treatment to improve the mechanical properties of materials in different ways. However, the holistic approach to studying the physical and mechanical properties has less been reported. Therefore, this article presents the optimisation of the processing window of the AlSi12 aluminium alloy produced by the SLM process. The design of the experiment (DoE) was carried out using the Response Surface Methodology (RSM) implemented in the Design Expert 2018 environment. It involved two process factors in the following range of scan speed (500–2500 mm/s) and laser power (50–300 W). The combination of a scan speed of 500 mm/s and a laser power of 300 W resulted in a relative density of 97.4 %, an ultimate tensile strength (UTS) of 418 MPa and a hardness of 132.6 HV. The microstructure and fracture analysis provided evidence of reduced defects with the combination of parameters mentioned above. Thus, this study contributes to adding a new set of data to existing work for more comprehensive parameter calibration. This study helps industries that produce aluminium alloys from SLM processes obtain the optimal range of process parameters that produce parts with the desired mechanical properties. en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri https://www.sciencedirect.com/science/article/pii/S2238785423030065?dgcid=rss_sd_all en_US
dc.source Journal of Materials Research and Technology en_US
dc.subject Selective laser melting en_US
dc.subject Lightweight metals en_US
dc.subject Aluminium alloys en_US
dc.title Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting en_US
dc.type Article en_US
dc.description.pages 1062-1073 en_US
dc.description.note © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). en_US
dc.description.cluster Manufacturing en_US
dc.description.impactarea Laser Enabled Manufacturing en_US
dc.identifier.apacitation Nzengue, A., Khumbulani, M., Mathe, N. R., & Muvunzi, R. (2023). Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting. <i>Journal of Materials Research and Technology</i>, http://hdl.handle.net/10204/13706 en_ZA
dc.identifier.chicagocitation Nzengue, ACB, Mpofu Khumbulani, Ntombizodwa R Mathe, and R Muvunzi "Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting." <i>Journal of Materials Research and Technology</i> (2023) http://hdl.handle.net/10204/13706 en_ZA
dc.identifier.vancouvercitation Nzengue A, Khumbulani M, Mathe NR, Muvunzi R. Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting. Journal of Materials Research and Technology. 2023; http://hdl.handle.net/10204/13706. en_ZA
dc.identifier.ris TY - Article AU - Nzengue, ACB AU - Khumbulani, Mpofu, K AU - Mathe, Ntombizodwa R AU - Muvunzi, R AB - Selective laser melting (SLM) SLM has gained interest in processing lightweight metals like aluminium alloys. The SLM processing remains challenging in finding the appropriate process parameters for the desired mechanical properties. Previous studies have used energy density formulas and heat treatment to improve the mechanical properties of materials in different ways. However, the holistic approach to studying the physical and mechanical properties has less been reported. Therefore, this article presents the optimisation of the processing window of the AlSi12 aluminium alloy produced by the SLM process. The design of the experiment (DoE) was carried out using the Response Surface Methodology (RSM) implemented in the Design Expert 2018 environment. It involved two process factors in the following range of scan speed (500–2500 mm/s) and laser power (50–300 W). The combination of a scan speed of 500 mm/s and a laser power of 300 W resulted in a relative density of 97.4 %, an ultimate tensile strength (UTS) of 418 MPa and a hardness of 132.6 HV. The microstructure and fracture analysis provided evidence of reduced defects with the combination of parameters mentioned above. Thus, this study contributes to adding a new set of data to existing work for more comprehensive parameter calibration. This study helps industries that produce aluminium alloys from SLM processes obtain the optimal range of process parameters that produce parts with the desired mechanical properties. DA - 2023-12 DB - ResearchSpace DP - CSIR J1 - Journal of Materials Research and Technology KW - Selective laser melting KW - Lightweight metals KW - Aluminium alloys LK - https://researchspace.csir.co.za PY - 2023 SM - 2238-7854 SM - 2214-0697 T1 - Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting TI - Optimising a processing window for the production of aluminium silicon-12 samples via selective laser melting UR - http://hdl.handle.net/10204/13706 ER - en_ZA
dc.identifier.worklist 27309 en_US
dc.identifier.worklist SLM en_US


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