Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/30412
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dc.contributor.authorIsmail, Mahamad Hakimi-
dc.date.accessioned2013-12-11T07:06:33Z-
dc.date.available2013-12-11T07:06:33Z-
dc.date.issued2010-05-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/30412-
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractSurface roughness is one of the aspects that are of great significance in CNC milling process as it represents the quality of the product. Thus, in order to obtain a good surface finish, optimum cutting parameters in CNC milling must be determined. This project was conducted using Taguchi method for the purpose of obtaining the optimum cutting parameters in CNC milling. The parameters chosen in this experiment are spindle speed [rpm], feed rate [mm/tooth], depth of cut [mm] and tool material. The material used in this study is cast iron. The Taguchi method is used as a tool to identify the control factor levels for optimum surface roughness. The optimum combinations of control factor levels were identified by referring to the smallest surface roughness value which is 3.118μm. The optimum parameters were proven based on the prediction by Design Expert software and also experimental run. The parameters were tool material of High Speed Steel (TiCN coated) [A3], cutting speed = 700 rpm [B3], depth of cut = 1.0 mm [C1], and feed rate = 0.1 mm/tooth [D2 ]. In conclusion, the objectives of this project to obtain the optimum cutting parameters for optimum surface roughness were achieved.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectCNC milling processen_US
dc.subjectDesign of Experiment (DOE)en_US
dc.subjectSurface roughnessen_US
dc.subjectCast ironen_US
dc.titleA study on surface roughness of cast iron using CNC milling processen_US
dc.typeLearning Objecten_US
dc.contributor.advisorMuhamad Nasir Muraden_US
dc.publisher.departmentSchool of Manufacturing Engineeringen_US
Appears in Collections:School of Manufacturing Engineering (FYP)

Files in This Item:
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Abstract, Acknowledgement.pdf98.44 kBAdobe PDFView/Open
Introduction.pdf41.98 kBAdobe PDFView/Open
Literature review.pdf456.67 kBAdobe PDFView/Open
Methodology.pdf172.84 kBAdobe PDFView/Open
Results and discussion.pdf375.44 kBAdobe PDFView/Open
Conclusion.pdf46.21 kBAdobe PDFView/Open
Reference and appendix.pdf3.78 MBAdobe PDFView/Open


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