Optimization Study on Dimensional Accuracy of SLM Forming of GH3625 Superalloy Based on Integrated RSM and NSGA-Ⅱ
In order to improve the dimensional accuracy of SLM-formed parts,this study proposed an integrated response surface methodology(RSM)and non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)approach to optimize the dimensional accuracy of SLM-formed GH3625 superalloy.Firstly,a model of SLM process parameters with dimensional errors in X,Y and Z directions was developed by RSM,and then the model was optimized by NSGA-Ⅱ for multi-objective optimization.The results show that the model constructed by RSM has high prediction accuracy,and the correlation coefficients R2 are 0.9456,0.9842,and 0.9704 in order.The optimization algorithm is able to obtain the optimal interval of the processing parameters at 1500 iterations:the laser power is 250.8-310 W,the scanning speed is 1028-1400 mm/s,the hatching space is 0.071-0.084 mm.The experimental validation results show the high reliability of the integrated method with ARE of 5.95％,4.92％and 3.97％for dimensional errors in X,Y and Z directions,respectively.
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