NC process information mining based roughing tool sequence optimization and decision approach for pocket features
To effectively promote the use efficiency of roughing tools during NC machining,a NC process information mining based roughing tool sequence optimization and decision approach for pocket features was presented.The Me-dial Axis Transform(MAT)was adopted to represent the tool paths of a pocket feature,and the mapping mecha-nism between MAT and NC machining was elaborated.Based on process rules and parameters of MAT,the deeper NC process information hidden in 3D CAD models was mined.The material removal amount and cutting Consistency were considered synthetically to construct the multi-objective optimization model,and a hybrid Ant Colony Algo-rithm(ACA)and Simulated Annealing(SA)approach was presented to achieve the global optimal tool sequence.Experimental results showed that the method could achieve highly satisfactory results and promote the intelligence level of NC process planning for entertainments.
information miningpocket featuresroughing tool sequenceoptimization and decisionnumerical control machinning
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