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Response Ant Colony Optimization of end milling surface roughness
K Kadirgama1, M M Noor, Ahmed N Abd Alla
1Faculty of Mechanical Engineering, University Malaysia Pahang, Kuantan, 26300 UMP, Malaysia. kumaran@ump.edu.my
This study optimizes surface roughness in milling aluminum alloys using Response Ant Colony Optimization (RACO). Feedrate was identified as the most significant factor influencing surface quality.
Area of Science:
- Manufacturing Engineering
- Materials Science
- Computational Intelligence
Background:
- Increasing consumer demand for high-quality metal products necessitates improvements in metal cutting processes.
- Achieving precise tolerances and superior surface roughness is critical for product performance and market competitiveness.
Purpose of the Study:
- To determine optimal machining parameters for minimizing surface roughness in milling aluminum alloy (AA6061-T6).
- To identify the most influential variables affecting surface roughness in the specified metal cutting process.
Main Methods:
- Utilized Response Surface Method (RSM) combined with Ant Colony Optimization (ACO) for parameter optimization.
- Employed Response Ant Colony Optimization (RACO) to analyze milling process variables.
Main Results:
- The study successfully identified optimized parameters for achieving desired surface roughness.
- Analysis revealed that feedrate is the most dominant variable impacting surface roughness in milling AA6061-T6.
Conclusions:
- The RACO approach effectively optimizes surface roughness in milling aluminum alloys.
- Feedrate control is paramount for enhancing surface quality in these manufacturing operations.
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