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dc.contributor.authorWakjira, Melesse Workneh-
dc.contributor.authorAltenbach, Holm-
dc.contributor.authorPerumalla, Janaki Ramulu-
dc.date.accessioned2021-05-19T12:26:44Z-
dc.date.available2021-05-19T12:26:44Z-
dc.date.issued2019-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/36871-
dc.identifier.urihttp://dx.doi.org/10.25673/36639-
dc.description.abstractThe aim of this research paper is to investigate the machinability of CSN 12050 carbon steel bars using carbide insert tool in order to utilize the optimum cutting parameters by employing Taguchi approach. Experiments have been performed under dry cutting condition using an optimization approach according to Taguchi’s 𝐿9(34) orthogonal arrays; signal-to-noise ratio tests are designed. Analysis of variance (ANOVA) was performed to determine the importance of machining parameters on thematerial removal rate (MRR).The results were analyzed using signal-to-noise ratios (S/N); 3D surface graphs, main effect graphs of mean, and predictive equations are employed to study the performance characteristics.The optimal parameters resulted as 𝐴3𝐵2𝐶3 (i.e., cutting speed 275 (m/min), depth of cut 0.35 (mm), and feed rate 0.25 (mm/rev), respectively). In the present study, there is an improvement of 5.22 dB at optimal cutting conditions for each significant MRR response parameters such as cutting speed, depth of cut, and feed rate.With these proposed optimal parameters, it is possible to optimize machinability for product sustainability.eng
dc.description.sponsorshipDFG-Publikationsfonds 2019-
dc.language.isoeng-
dc.relation.ispartofhttps://doi.org/10.1155/3962-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectTaguchi techniqueeng
dc.subjectCarbon Steeleng
dc.subjectDry turning processeng
dc.subjectProduct sustainabilityeng
dc.subject.ddc621.8-
dc.titleAnalysis of CSN 12050 carbon steel in dry turning process for product sustainability optimization using taguchi techniqueeng
dc.typeArticle-
dc.identifier.urnurn:nbn:de:gbv:ma9:1-1981185920-368712-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleJournal of Engineering-
local.bibliographicCitation.volume2019-
local.bibliographicCitation.pagestart1-
local.bibliographicCitation.pageend10-
local.bibliographicCitation.publishernameHindawi Publishing-
local.bibliographicCitation.publisherplaceNew York, NY-
local.bibliographicCitation.doi10.1155/2019/7150157-
local.openaccesstrue-
dc.identifier.ppn1662869959-
local.bibliographicCitation.year2019-
cbs.sru.importDate2021-05-19T12:20:18Z-
local.bibliographicCitationEnthalten in Journal of Engineering - New York, NY : Hindawi Publishing, 2013-
local.accessrights.dnbfree-
Enthalten in den Sammlungen:Fakultät für Maschinenbau (OA)

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