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《Mechanical Science and Technology for Aerospace Engineering》 2014-11
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Optimization of the 3DP Printing Parameters Based on the Neural Networks and Genetic Algorithm

Li Shujuan;Chen Wenbin;Liu Yong;Fu Liu;School of Mechanical and Instrument Engineering,Xi'an University of Technology;  
The factors affect the printing accuracy for powdery materials is analyzed in three dimensional printing( 3DP) process,the experiment is used to determine the range of shrinkage of the printing process for the threedimensional components. The " H" type component as the test specimen,the neural network( NN) is used to describe the complicated relationship between the dimensional accuracy of component and printing processing parameters. As the goal of the minimum dimensional accuracy of specimen,the genetic algorithm( GA) is used to optimize the 3DP printing parameters such as saturation,the layer thickness and compensation in three directions X,Y and Z respectively. The comparing experiments for 3DP using default parameters of printer,the minimum and maximum value in the range of printing parameters,and the NN-GA obtained parameters are conducted,and the results show that the dimensional accuracy is the best using the printing processing parameters of the NN-GA obtained,which show that the NN-GA can predict the dimensional accuracy for 3DP printing processing and provide the reference for other similar fabrication method.
【Fund】: 国家973项目(2009CB724406);; 陕西省工业攻关项目(2012K07-25)资助
【CateGory Index】: TH16;TP18
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