02191nam a2200229 a 4500001001400000003000700014005001700021008004100038020002200079040000800101100002200109245010300131246009900234260003400333300006400367502012300431504002700554520130900581650002201890650003501912650001401947vtls000052370KUKTEM20251114204500.0110328t2010 my a f m 000 0 eng d aTHE0005787(Local) aUMP0 aSyahrizad Muhamad10aOptimization of surface texture in milling using response surface methodology /cSyahrizad Muhamad3 aOptimization of surface texture in milling using response surface methodologyh[computer file] aKuantan, Pahang :bUMP,c2010 axvi, 67 p. :bill. (some col.) ;c30 cm. +e1 computer disc aProject paper (Bachelor of Mechanical Engineering with Manufacturing Engineering) -- Universiti Malaysia Pahang - 2010 aBibliography : p. [68]3 aThis project deals with the effects of three parameters chosen on the surface texture of Aluminum 6061 by using milling. The main objectives of this project are to investigate the parameters for surface texture in milling, to obtain the optimum surface texture using Response Surface Methodology and to recommend the best machine parameter that contributes to the optimum surface roughness value. The study of this project covers on the limitation of cutting speed range (100 to 180 mm), feed range of 0.1 to 0.2 min.mm and depth of cut range 1 to 2 tooth.mm. The 15 experiments (1 experiment consist of 1 pass that 90mm in length) are done by using manual coding of CNC Milling Machine, Perthometer for surface roughness testing and Metallurgical Microscope for surface texture testing. The result and data taken from these procedures were analyzed by using Response Surface Methodology (RSM) of Minitab Software. The model is validates through a comparison of the experimental values with their predicted counterparts. From the results, it indicates that from the RSM method, the first order gives 73.14% accuracy and the second order gives 81.43% in accuracy. The proved technique gives opportunities for better approach that could be applied to the calibration of other empirical models of machining. 0aSurface roughness 0aResponse surfaces (Statistics) 0aMachining