Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling
Surface roughness affects the functional attributes of finished parts. Therefore, predicting the finish surface is important to select the cutting levels in order to reach the required quality. In this research an experimental investigation was conducted to predict the surface roughness in the fi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Trans Tech Publications, Switzerland
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/29225/1/Predicting_Surface_Roughness_with_Respect_to_Process_Parameters.pdf http://irep.iium.edu.my/29225/ |
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| Summary: | Surface roughness affects the functional attributes of finished parts. Therefore, predicting
the finish surface is important to select the cutting levels in order to reach the required quality. In
this research an experimental investigation was conducted to predict the surface roughness in the
finish end milling process with higher cutting speed. Twenty sets of data for finish end milling on
AISI H13 at hardness of 48 HRC have been collected based on five-level of Central Composite
Design (CCD). All the experiments done by using indexable tool holder Sandvick Coromill R490
and the insert was PVD coated TiAlN carbide. The experimental work performed to predict four
different roughness parameters; arithmetic mean roughness (Ra), total roughness (Rt), mean depth
of roughness (Rz) and the root mean square (Rq). |
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