NN-GA Based Printing Parameters Optimization for 3DP
With the rapid printing speed and low cost,Three Dimensional Printing (3DP) is widely used.However,the dimensional accuracy of components are not perfect due to the shrinkage and deformation of component after the printing and post-processing.This study analyzes the factors affect the printing accuracy in 3DP and determines the range of shrinkage of the printing process.Neural Network (NN) is used to describe the complicated relationship between the dimensional accuracy of component and printing parameters.In order to minimizing dimensional error of specimen,Genetic Algorithm (GA) is used to optimize the 3DP print parameters such as binder saturation,the layer thickness and shrinkage compensation in X,Y and Z directions respectively.The four experiments with default parameters,the limits in the range of print parameters,and parameters from NN-GA are conducted,and the results show that the dimensional error is much lower using the printing parameters from NN-GA,and also show that the NN-GA is capable to promote the dimensional accuracy of 3DP and provide the reference for other forms AM technology.
Three Dimensional Printing (3DP) Neural Network (NN) Genetic Algorithm (GA) Parameters Optimization Dimensional Accuracy
Shujuan Li Wenbin Chen Fu Liu Yan Li
School of Mechanical and Instrument Engineering Xian University of Technologyl Xian 710048, China
国际会议
2013 International Symposium on Assembly and Manufacturing(2013装配与制造国际专题会议)
西安
英文
160-162
2013-07-01（万方平台首次上网日期，不代表论文的发表时间）