Surface Roughness Analysis In End Milling With Response Ant Colony Optimization
The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling pro...
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| Format: | Conference or Workshop Item |
| Language: | en |
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2009
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| Online Access: | http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf http://umpir.ump.edu.my/id/eprint/1448/ |
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| _version_ | 1831520992915095552 |
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| author | K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani |
| author_facet | K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani |
| author_sort | K., Kadirgama |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling process is one of the most fundamental metal removal operations used in the manufacturing industry. Surface roughness also affects several functional attributes of part such as contact causing surface friction, wearing, light reflection, heat transmission ability of distributing holding and lubricant, coating, or resisting fatigue. Therefore, the
desired finish surface is usually specified and the appropriate processes are select to reach the required quality.This paper presents the optimization of the surface roughness when milling Mould Aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO).
The approach is based on Response Surface Method (RSM) and Ant colony Optimization (ACO). In this work, the objectives were to find the optimized parameters and find out the most dominant variables (cutting speed, federate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factors effecting surface roughness. The optimised minimum and maximum values that predicted by RACO were 0.36 μm and 1.37 μm. |
| format | Conference or Workshop Item |
| id | my.ump.umpir.1448 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2009 |
| record_format | eprints |
| spelling | my.ump.umpir.14482018-01-22T07:24:27Z http://umpir.ump.edu.my/id/eprint/1448/ Surface Roughness Analysis In End Milling With Response Ant Colony Optimization K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani TJ Mechanical engineering and machinery The increase of consumer needs for quality metal cutting related products (more precise tolerances and better product surface roughness) has driven the metal cutting industry to continuously improve quality control of metal cutting processes. Within these metal cutting processes, the end-milling process is one of the most fundamental metal removal operations used in the manufacturing industry. Surface roughness also affects several functional attributes of part such as contact causing surface friction, wearing, light reflection, heat transmission ability of distributing holding and lubricant, coating, or resisting fatigue. Therefore, the desired finish surface is usually specified and the appropriate processes are select to reach the required quality.This paper presents the optimization of the surface roughness when milling Mould Aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant colony Optimization (ACO). In this work, the objectives were to find the optimized parameters and find out the most dominant variables (cutting speed, federate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factors effecting surface roughness. The optimised minimum and maximum values that predicted by RACO were 0.36 μm and 1.37 μm. 2009 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf K., Kadirgama and M. M., Noor and M. M., Rahman and M. S. M., Sani (2009) Surface Roughness Analysis In End Milling With Response Ant Colony Optimization. In: 6th International Conference on Numerical Analysis in Engineering (NAE2009) , 15 -16 May 2009 , Lombok Island, Mataram City, West Nusa Tenggara Province, Indonesia. . (Unpublished) (Unpublished) |
| spellingShingle | TJ Mechanical engineering and machinery K., Kadirgama M. M., Noor M. M., Rahman M. S. M., Sani Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title | Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title_full | Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title_fullStr | Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title_full_unstemmed | Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title_short | Surface Roughness Analysis In End Milling With Response Ant Colony Optimization |
| title_sort | surface roughness analysis in end milling with response ant colony optimization |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/1448/1/2009_P_NAE09_K.Kadirgama_M.M.Noor-conference-.pdf http://umpir.ump.edu.my/id/eprint/1448/ |
| url_provider | http://umpir.ump.edu.my/ |