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dc.contributor.authorKaushik, Yogesh
dc.contributor.authorGhosh, Tamal
dc.date.accessioned2023-03-02T15:44:38Z
dc.date.available2023-03-02T15:44:38Z
dc.date.created2022-02-23T09:05:30Z
dc.date.issued2022
dc.identifier.citationLecture Notes in Networks and Systems. 2022, 163-172.en_US
dc.identifier.issn2367-3370
dc.identifier.urihttps://hdl.handle.net/11250/3055535
dc.description.abstractThis paper presents a methodology to obtain improved quality of surface roughness during production of mobile case cover inside a cyberphysical (CP) factory using micro-CNC end milling with aluminium alloy T6 (6068). The said machining is done with different machining parameters such as cutting velocity, spindle speed and cut depth. Three profile parameters (Ra, Rz and Rzmax) are projected as response variables. Thereafter, Taguchi’s orthogonal array design is considered with smaller-is-better signal-to-noise ratio, and linear regression is performed to get optimal process parameter settings combination. This result is further verified using a particle swarm optimization (PSO) technique, and validation is done on CNC machining centre.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titlePSO Based Improved Surface Roughness Measuring Approach of Manufactured Product Within CP Factory Using T6 6068 Aluminiumen_US
dc.title.alternativePSO Based Improved Surface Roughness Measuring Approach of Manufactured Product Within CP Factory Using T6 6068 Aluminiumen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.pagenumber163-172en_US
dc.source.journalLecture Notes in Networks and Systemsen_US
dc.identifier.doi10.1007/978-981-19-2397-5_16
dc.identifier.cristin2004716
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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