Optimization of Injection Molding Process of Bearing Stand Based on BP Network Method  

作　　者：虞俊波 周小林 邓常乐 刘军 王骥 

机构地区：[1]School of Mechanical Engineering & Mechanics, Ningbo University, Ningbo, 315211, P.R. China [2]Ningbo Furja Industrial Corporation Limited, Ningbo, 315400, P.R. China

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2014年第2期180-185,共6页南京航空航天大学学报（英文版）

基　　金：supported by a grant from the Ningbo Furja Industrial Corporation Limited

摘　　要：The quality of injection plastic molded parts relates to precise geometry,smooth surface,strength,durability,and other indicators that are associated with the mold,materials,injection process,and service environment.The warpage is one of main defects of injection products,which cost much time and materials.In order to minimize warpage to ensure the precise shape of molded parts,it needs to combine design,service conditions,process parameters,material properties,and other factors in the design and manufacturing.Finite element tools and material database are used to analyze the occurrence of warpage,and analysis results contribute to the improvement and optimization of injection molding process of typical parts.To find the optimal process parameters in the solution space,experimental data are used to establish backpropagation(BP)network for predicting warpage of a bearing stand based on analysis with Moldflow.With a proper transfer function and the BP network architecture,results from the BP network method satisfiy the criteria of accuracy.The optimal solutions are searched in the BP network by the genetic algorithm with the finding that the optimization method based on the BP network is efficient.The quality of injection plastic molded parts relates to precise geometry, smooth surface, strength, dura- bility, and other indicators that are associated with the mold, materials, injection process, and service environ- ment. The warpage is one of main defects of injection products, which cost much time and materials. In order to minimize warpage to ensure the precise shape of molded parts, it needs to combine design, service conditions, process parameters, material properties, and other factors in the design and manufacturing. Finite element tools and material database are used to analyze the occurrence of warpage, and analysis results contribute to the improve- ment and optimization of injection molding process of typical parts. To find the optimal process parameters in the solution space, experimental data are used to establish backpropagation （BP） network for predicting warpage of a bearing stand based on analysis with Moldflow. With a proper transfer function and the BP network architecture, results from the BP network method satisfiy the criteria of accuracy. The optimal solutions are searched in the BP network by the genetic algorithm with the finding that the optimization method based on the BP network is effi- cient.

关 键 词：injection molding orthogonal test MOLDFLOW BP neural network warpage deflection 

分 类 号：TQ320.66[化学工程—合成树脂塑料工业]