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Potential approach towards effective topography characterization of 316L stainless steel components produced by selective laser melting process
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). (Functional Surfaces)ORCID-id: 0000-0002-8364-202x
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). RISE, Research Institutes of Sweden, Borås, Sweden.ORCID-id: 0000-0001-7501-8318
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). (Functional Surfaces)ORCID-id: 0000-0002-2330-0597
Chalmers University of Technology, Gothenburg, Sweden .
Vise andre og tillknytning
2018 (engelsk)Inngår i: European Society for Precision Engineering and Nanotechnology, Conference Proceedings - 18th International Conference and Exhibition, EUSPEN 2018, Bedford: euspen , 2018, s. 259-260Konferansepaper, Poster (with or without abstract) (Fagfellevurdert)
Abstract [en]

In this paper, an attempt is made to explain the surface texture of Selective Laser Melting (SLM) parts more satisfyingly than the existing methods. Investigations were carried out on the 316L stainless steel SLM samples. To account for most of the surface conditions, a truncheon artefact was employed for the analysis. A Stylus Profilometer was employed as a metrology tool for obtaining the 3D surface measurements. A methodology is proposed to extract and characterize the topographic features of Additive Manufactured (AM) surfaces. Here, the overall roughness of the surface is segregated into the roughness of the powder particles and the waviness due to thermal and the “staircase” effects. Analyzing these features individually results in an increased understanding of the AM process and an opportunity to optimize machine settings.

sted, utgiver, år, opplag, sider
Bedford: euspen , 2018. s. 259-260
Emneord [en]
Surface Metrology, Selective Laser Melting, Profilometer, Areal Surface Parameters, Feature-based characterization
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-38126Scopus ID: 2-s2.0-85054549685ISBN: 9780995775121 (tryckt)ISBN: 0995775125 (tryckt)OAI: oai:DiVA.org:hh-38126DiVA, id: diva2:1254461
Konferanse
Euspen’s 18th International Conference & Exhibition, Venice, Italy, 4th-8th June, 2018
Tilgjengelig fra: 2018-10-09 Laget: 2018-10-09 Sist oppdatert: 2019-01-08bibliografisk kontrollert

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Vedantha Krishna, AmoghFlys, OlenaReddy, Vijeth VenkataramRosén, Bengt Göran

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