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基于RBF神经网络的双色LOGO塑件成型工艺优化

Optimization of Two-Color LOGO Plastic Part Forming Process Based on RBF Neural Network

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【Author】 Zhang Jun;Huang Yao;Zhou Fuzhi;Wang Leigang;School of Materials Science and Engineering, Jiangsu University;Danyang Kaixin Precision Mould Co., Ltd.;

【通讯作者】王雷刚;

【机构】江苏大学材料科学与工程学院；丹阳凯新精密模具有限公司；

【摘要】以某汽车贯穿灯LOGO塑件为研究对象，通过正交试验、计算机辅助工程(CAE)软件和径向基函数(RBF)神经网络对注塑工艺参数进行优化，并对优化结果进行生产验证，得到了满足质量要求的产品。更多还原

【Abstract】 Taking the LOGO plastic part of a certain car through light as the research object, the injection molding process parameters were optimized through orthogonal experiments, computer-aided engineering(CAE) software and radial basis function(RBF) neural network. The optimization results were verified in production, and products that meet the quality requirements were obtained.更多还原

【关键词】厚壁塑件；正交试验；径向基函数神经网络；工艺优化；
【Key words】 thick-wall plastic part； orthogonal test； radial basis function neural network； process optimization；

【文献出处】现代塑料加工应用 ,Modern Plastics Processing and Applications , 编辑部邮箱 ,2023年03期

【分类号】TQ320.662
【下载频次】6

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