On optimization of surface roughness of selective laser melted stainless steel parts: A statistical study

Journal article


Alrbaey, K., Wimpenny, D., Tosi, R., Manning, W. and Moroz, A. 2014. On optimization of surface roughness of selective laser melted stainless steel parts: A statistical study. Journal of Materials Engineering and Performance. 23 (6), pp. 2139-2148. https://doi.org/10.1007/s11665-014-0993-9
AuthorsAlrbaey, K., Wimpenny, D., Tosi, R., Manning, W. and Moroz, A.
Abstract

In this work, the effects of re-melting parameters for postprocessing the surface texture of Additively Manufactured parts using a statistical approach are investigated. This paper focuses on improving the final surface texture of stainless steel (316L) parts, built using a Renishaw SLM 125 machine. This machine employs a fiber laser to fuse fine powder on a layer-by-layer basis to generate three-dimensional parts. The samples were produced using varying angles of inclination in order to generate range of surface roughness between 8 and 20 µm. Laser re-melting (LR) as post-processing was performed in order to investigate surface roughness through optimization of parameters. The re-melting process was carried out using a custom-made hybrid laser re-cladding machine, which uses a 200 W fiber laser. Optimized processing parameters were based on statistical analysis within a Design of Experiment framework, from which a model was then constructed. The results indicate that the best obtainable final surface roughness is about 1.4 µm ± 10%. This figure was obtained when laser power of about 180 W was used, to give energy density between 2200 and 2700 J/cm2 for the re-melting process. Overall, the obtained results indicate LR as a post-build process has the capacity to improve surface finishing of SLM components up to 80%, compared with the initial manufactured surface.

KeywordsMechanical Engineering; General Materials Science; Mechanics of Materials
Year2014
JournalJournal of Materials Engineering and Performance
Journal citation23 (6), pp. 2139-2148
PublisherSpringer Science and Business Media LLC
ISSN1059-9495
1544-1024
Digital Object Identifier (DOI)https://doi.org/10.1007/s11665-014-0993-9
Web address (URL)https://link.springer.com/article/10.1007%2Fs11665-014-0993-9
hdl:10545/624534
Output statusPublished
Publication dates22 Apr 2014
Publication process dates
Deposited04 Mar 2020, 16:26
Accepted09 Jan 2014
ContributorsDe Montfort Univerisity and MTC Coventry
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File Access Level
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