| 000 | 02415nam a2200241 a 4500 | ||
|---|---|---|---|
| 001 | vtls000051499 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204410.0 | ||
| 008 | 110228t2010 my da f m 000 0 engd | ||
| 020 | _aTHE0006533(Local) | ||
| 039 | 9 |
_a201905141509 _bamirul _c201202010915 _dida _c201107131845 _dVLOAD _y201102281020 _zFida |
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| 040 | _aUMP | ||
| 090 | _aTJ1186 .F34 2010 rs Bc. | ||
| 100 | 0 | _aMohd Fahmi Md Yusuf | |
| 245 | 1 | 4 |
_aPerformance of uncoated cutting tools when machining mild steel and aluminium alloy / _cMohd Fahmi Md Yusuf |
| 246 | 3 |
_aPerformance of uncoated cutting tools when machining mild steel and aluminium alloy _h[electronic resource] |
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| 260 |
_aKuantan, Pahang : _bUMP, _c2010 |
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| 300 |
_axii, 50 p. : _bill. (some col.) ; _c30 cm. + _e1 computer discs |
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| 502 | _aProject paper (Bachelor of Mechanical Engineering) -- Universiti Malaysia Pahang -- 2010 | ||
| 520 | 3 | _aThis paper discuss of the performance of uncoated carbide cutting tools in milling by investigating through the surface roughness. Response Surface Methodology (RSM) is implemented to model the face milling process that are using four insert of uncoated carbide TiC as the cutting tool and mild steel AISI1020 and aluminium alloy AA6061 as materials due to predict the resulting of surface roughness. Data is collected from HAAS CNC milling machines were run by 15 samples of experiments for each material using DOE approach that generate by Box-Behnkin method due to table design in MINITAB packages. The inputs of the model consist of feed, cutting speed and depth of cut while the output from the model is surface roughness. Predictive value of surface roughness was analyzed by the method of RSM. The model is validated through a comparison of the experimental values with their predicted counterparts. A good agreement is found where from the RSM approaches show the 76.51% accuracy for mild steel and 79.55% accuracy for aluminium alloy which reliable to be use in Ra prediction and state the feed parameter is the most significant parameter followed by depth of cut and cutting speed influence the surface roughness. The proved technique opens the door for a new, simple and efficient approach that could be applied to the calibration of other empirical models of machining | |
| 650 | 0 | _aCarbide cutting tools | |
| 999 |
_aVIRTUA40 _c1373 _d1379 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5200*6500*9992 | ||