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Study on surface texture of Fused Deposition Modeling
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). (Functional Surfaces Research Group)ORCID-id: 0000-0002-2330-0597
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Rydberglaboratoriet för tillämpad naturvetenskap (RLAS). Research Institute of Sweden, Borås, Sweden.ORCID-id: 0000-0001-7501-8318
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap.
Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap.
Vise andre og tillknytning
2018 (engelsk)Inngår i: Proceedings of the 8th Swedish Production Symposium (SPS 2018) / [ed] Mauro Onori, Lihui Wang, Xi Vincent Wang, Wei Ji, Amsterdam: Elsevier, 2018, Vol. 25, s. 8s. 389-396Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Fused Deposition Modeling (FDM) is mostly used to develop functional prototypes and in some applications for end-use parts. It is important to study the surfaces produced by FDM to understand the certainty of process. Truncheon design test artefacts are printed at different print settings and surfaces are measured using stylus profilometer. Taguchi’s design of experiments, signal-to-noise ratio and multiple regression statistics are implemented to establish a concise study of the individual and combined effect of process variables on surface texture parameters. Further, a model is developed to predict the roughness parameters and is compared with experimental values. The results suggest significant roughness parameter values decrease with increase in build inclination and increases with increase in layer thickness except the roughness peak count. © 2018 The Authors. Published by Elsevier B.V

sted, utgiver, år, opplag, sider
Amsterdam: Elsevier, 2018. Vol. 25, s. 8s. 389-396
Serie
Procedia Manufacturing, E-ISSN 2351-9789 ; 25
Emneord [en]
Additive manufacturing, Fused Deposition Modeling, Surface texture parameters, Surface roughness
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-38122DOI: 10.1016/j.promfg.2018.06.108OAI: oai:DiVA.org:hh-38122DiVA, id: diva2:1254431
Konferanse
8th Swedish Production Symposium, SPS 2018, Stockholm, Sweden, 16-18 May, 2018
Prosjekter
Digitalization of the supply chain of the Swedish Additive Manufacturing (DiSAM)Business Model Innovation
Forskningsfinansiär
VINNOVAKnowledge Foundation
Merknad

Funding: VINNOVA, Sweden’s innovation agency and Produktion2030 under the project Digitalization of the supply chain of the Swedish Additive Manufacturing (DiSAM) and Sweden’s The Knowledge Foundation under the project Business Model Innovation when adapting to Digital Production - opportunities and problems.

Tilgjengelig fra: 2018-10-09 Laget: 2018-10-09 Sist oppdatert: 2019-01-03bibliografisk kontrollert

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