Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/63338
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dc.contributor.authorTamilarasan, A-
dc.contributor.authorRenugambal, A-
dc.date.accessioned2024-02-15T09:47:04Z-
dc.date.available2024-02-15T09:47:04Z-
dc.date.issued2024-02-
dc.identifier.issn0022-4456 (Print); 0975-1084 (Online)-
dc.identifier.urihttp://nopr.niscpr.res.in/handle/123456789/63338-
dc.description139-145en_US
dc.description.abstractRoller burnishing is a surface improvement technique that creates residual compressive stress in the workpiece surface layers. Compressive surface stress generation may increase surface hardness, which in turn enhances fatigue and corrosion resistance and overall surface quality. In order to optimize the process parameters in roller burnishing of brass, the present work unveils an application of Response Surface Methodology (RSM) and hybrid Water Cycle Moth Flame Algorithm (WCMFO) technique. Three input process parameters viz. burnishing speed, depth of penetration and feed rate have been investigated and modelled for Microhardness (HV) utilizing RSM based central composite design. In present experimentation, quadratic model has been suggested for surface hardness. Following validation of the model’s validity, the model was coupled with a new metaheuristic based hybrid WCMFO algorithm to optimize the burnishing parameters for maximum Microhardness. So as to prove the enhancement, the optimal burnishing parameters were tested. A substantial relationship was observed between the predicted micro hardness and the experimental values.en_US
dc.language.isoenen_US
dc.publisherNIScPR-CSIR, Indiaen_US
dc.sourceJSIR Vol.83(2) [February 2024]en_US
dc.subjectCentral composite designen_US
dc.subjectCorrosion resistanceen_US
dc.subjectResidual compressive stressen_US
dc.subjectRSMen_US
dc.subjectSurface hardnessen_US
dc.titleHybrid WCMFO Algorithm for Microhardness Improvement in Roller Burnishing of Brass (C3604)en_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.56042/jsir.v83i2.2627en_US
Appears in Collections:JSIR Vol.83(02) [February 2024]

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