| 基于DOE和BP神经网络对Al线键合工艺优化 |
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| 引用本文： | 毕向东,谢鑫鹏,胡俊,李国元.基于DOE和BP神经网络对Al线键合工艺优化[J].半导体技术,2010,35(9):894-898. |
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| 作者姓名： | 毕向东 谢鑫鹏 胡俊 李国元 |
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| 作者单位： | 广东省粤晶高科股份有限公司,广州,510663;华南理工大学电子与信息学院,广州,510641 |
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| 摘 要： | Al丝超声引线键合工艺被广泛地应用在大功率器件封装中,以实现大功率芯片与引 线框架之间的电互连.Al丝引线键合的质量严重影响功率器件的整体封装水平,对其工艺参数的优化具有重要工业应用意义.利用正交实验设计方法,对Al丝引线键合工艺中的三个最重要影响因数(超声功率P/DAC、键合时间t/ms、键合压力F/g)进行了正交实验设计,实验表明拉力优化后的工艺参数为:键合时间为40 ms,超声功率为25 DAC,键合压力为120g;剪切推力优化的工艺参数为:键合时间为50 ms,超声功率为40 DAC,键合压力为120 g.基于BP神经网络系统,建立了铝丝超声引线键合工艺的预测模型,揭示了Al丝超声键合工艺参数与键合质量之间的内在联系.网络训练结果表明训练预测值与实验值之间符合很好,检验样本的结果也符合较好,其误差基本控制在10%以内.
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| 关 键 词： | 铝丝键合 实验设计 BP神经网络 工艺优化 微电子封装 |
Process Optimization for Aluminum Wire Bonding Based on DOE and BP Neural Network |
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| Bi Xiangdong,Xie Xinpeng,Hu Jun,Li Guoyuan.Process Optimization for Aluminum Wire Bonding Based on DOE and BP Neural Network[J].Semiconductor Technology,2010,35(9):894-898. |
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| Authors: | Bi Xiangdong Xie Xinpeng Hu Jun Li Guoyuan |
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| Affiliation: | Bi Xiangdong1,Xie Xinpeng2,Hu Jun1,Li Guoyuan2(1.Guangdong Yuejing High-Tech Co.,Ltd.,Guangzhou 510663,China,2.School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510063,China) |
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| Abstract: | Aluminum wire bonding process is widely employed in high power devices packaging to realize electrical connection between chip and lead frame.The quality of aluminum wire bonding seriously influences on the reliability of power device packaging and process parameter optimizations is quite significant to the industry manufacturing.Based on orthogonal experimental design method,the three parameters of ultrasonic power,bonding time and bonding pressure were used to construct the orthogonal experimental table,a... |
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| Keywords: | aluminum wire bonding design of experiment(DOE) error back-propagation neural network(BPNN) process optimization microelectronic packaging |
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