Abstract
A multi-objective parameter has been optimized aimed at integral impeller high speed cutting based on genetic algorithm. Productivity, production cost and the surface roughness linearly weighted, a different weighting coefficient is set for the roughing and finishing stages of the integral impeller. For rough machining, productivity and production costs are the main optimization goals; for finish machining, the surface roughness is a major optimization goal. Cross-encoding variables are coded according to the schema theorem. The results show that: using the optimized cutting parameters in high speed milling hardened aluminum alloy LY12, processing time and production costs are shortened in rough machining stage and surface roughness is improved in the finishing stage.
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