面向引线焊线工艺的参数预测模型与规律分析  

Wire Bonding Process Oriented Quality Prediction Model and Parameter Relationship Analysis

作　　者：高健[1] 刘长宏[1] 陈新[1] 郑德涛[1] 

机构地区：[1]广东工业大学机电工程学院,广州510006

出　　处：《机械工程学报》2010年第15期185-190,198,共7页Journal of Mechanical Engineering

基　　金：广东省科技计划(2008A010300009;2009A091300001);广东省中国科学院全面战略合作(2009B091300057)资助项目

摘　　要：芯片封装的引线键合质量受键合温度、功率、压力、速度、时间等多参数的影响,各参数间相互耦合,存在着非线性关系,难以用准确的数学模型来表达其间的关系,影响芯片键合质量的提高。应用方差分析法开展正交试验的数据分析,得出各工艺参数对键合质量关键评价指标(剪切力和压扁球直径)的影响程度,确定描述工艺模型的6个关键参数。提出基于自适应神经模糊推理系统的焊线工艺预测模型的构建方法,并通过焊线机上的多组试验数据进行模型训练。将所建模型的预测结果与实际数据相比较,结果显示剪切力和压扁球直径预测模型所产生的平均误差分别为3.16%和1.24%。基于所建预测模型,确定关键工艺参数对键合质量的影响规律,为进一步实现焊线工艺过程的最优参数组合提供支持。In the chip wire bonding process, due to the coupling and nonlinear relationship of the multi-parameters including bonding temperature, power, pressure, speed and time, it’s very difficult to describe the relationship of these multi-parameters in a mathematics way, which affects the improvement of wire bonding quality. The result of how these parameters affecting the bonding quality in terms of shear force and squashed ball diameter is obtained through the orthogonal experiment, and six key parameters are fixed for the bonding process modeling. The prediction model of wire bonding process is proposed on the basis of adaptive neuro-fuzzy inference system（ANFIS）. The model is trained through experimental data on the bonding machine. Through the comparison of the predicted data and the real measured data, it shows that the mean error of the shear force is 3.16%, and the mean error of the squashed ball diameter is 1.24%. Based on this prediction model, the influence of key process parameters on the bonding quality is determined, which can be further used in the parameter optimization of the wire bonding process.

关 键 词：引线键合 预测模型 正交试验 神经模糊推理系统 

分 类 号：TN911.6[电子电信—通信与信息系统]