Haitao Yue1, Chenguang Guo1,*, Qiang Li1, Lijuan Zhao1, Guangbo Hao2
CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 937-952, 2020, DOI:10.32604/cmes.2020.010565
Abstract To improve the milling surface quality of the Al-Li alloy thin-wall
workpieces and reduce the cutting energy consumption. Experimental research
on the milling processing of AA2195 Al-Li alloy thin-wall workpieces based
on Response Surface Methodology was carried out. The single factor and interaction of milling parameters on surface roughness and specific cutting energy were
analyzed, and the multi-objective optimization model was constructed. The Multiobjective Particle Swarm Optimization algorithm introducing the Chaos Local
Search algorithm and the adaptive inertial weight was applied to determine the
optimal combination of milling parameters. It was observed that surface roughness was mainly influenced by feed… More >
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