Performance of uncoated cutting tools when machining mild steel and aluminium alloy

This 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...

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Bibliographic Details
Main Author: Mohd Fahmi, Md Yusuf
Format: Undergraduates Project Papers
Language:English
Published: 2010
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/1836/
http://umpir.ump.edu.my/id/eprint/1836/
http://umpir.ump.edu.my/id/eprint/1836/1/Mohd_Fahmi_Md_Yusuf_%28_CD_4948_%29.pdf
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Summary:This 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