Optimization of MIM process for micro gear based on Moldex 3D and GA-BP
In order to reduce the total warpage of MIM micro-gear injection parts and find a better combination of process parameters,a method for optimizing the process parameters of metal injection molding micro-gears based on Moldex 3D and GA-BP genetic neural network is proposed.Firstly,a full factorial experiment is estab-lished considering factors such as feed temperature,mold temperature and holding time in injection molding.The total warpage of each trial is simulated by Moldex 3D software,and then the better process parameter combina-tion is determined.Subsequently,a 3-4-1 BP neural network is designed,and the minimum total warpage is used as the fitness value.Combined with the genetic algorithm,the optimized process parameter combination is obtained.Compared with the analysis results of the full factorial experiment,the optimization results of the GA-BP model are similar to it,with an accuracy of 98.09％.This method provides a new approach for optimizing MIM process parameters,contributing to the improvement of the forming quality of micro gear products.
metal injection moldingMoldex 3DBP neural networkgenetic algorithmprocess parameter opti-mization
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