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dc.contributor.authorMuhammad Syafiq, Rahim
dc.contributor.authorAbang Annuar, Ehsan
dc.date.accessioned2021-02-23T08:39:10Z
dc.date.available2021-02-23T08:39:10Z
dc.date.issued2020-12
dc.identifier.citationInternational Journal of Nanoelectronics and Materials, vol.13(Special Issue), 2020, pages 151-158en_US
dc.identifier.issn1985-5761 (Printed)
dc.identifier.issn1997-4434 (Online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/69809
dc.descriptionLink to publisher's homepage at http://ijneam.unimap.edu.myen_US
dc.description.abstractA method is proposed for rapid prototyping of Poly (methyl methacrylate) (PMMA) microfluidic devices utilizing a micromilling machine. The present study is to investigates the influence of micromilling machining parameters which include spindle speed, feed rate, and depth of cut on the surface roughness of the machined polymer microfluidic devices. The devices have been machined on a PMMA substrate using 200 μm diameter endmill tool (Titanium Aluminum Nitride (TiAIN) coated solid carbide material). Surface roughness is considered an important parameter for influencing fluid flow at the microscale. The surface roughness has been measured using Infinite Focus Microscopy (IFM) tool. Taguchi’s method is used for designing the experiments and optimization of machining parameters. The results showed that a surface roughness of 67.3 nm has been achieved using machining parameters including spindle speed of 4000 rpm, feed rate of 10 mm/min and the depth of cut of 10 μm. Taguchi’s factor analysis on the samples showed that the depth of cut has the largest impact on the average surface roughnessen_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.relation.ispartofseriesNANOSYM, 2019;
dc.subjectMicromillingen_US
dc.subjectMicrofluidicsen_US
dc.subjectMicrochannelsen_US
dc.subjectSurface roughnessen_US
dc.titleOptimization of micromilling parameters using Taguchi Method for the fabrication of PMMA based microchannelsen_US
dc.typeArticleen_US
dc.contributor.urlaaehsan@ukm.edu.myen_US


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