摘要
为改善Al_(2)O_(3)陶瓷基板切割过程中的背崩问题,通过选取金刚石划片刀划切过程中会对背崩产生显著影响的磨料粒度、磨料浓度、结合剂硬度和冷水槽数量等4个特征参数作为关键因子,将陶瓷基板背崩尺寸作为响应变量,利用正交试验设计在因子可行域内选择样本数据,并采用高斯过程回归模型进行建模,最后用粒子群算法进行寻优。结果表明:该方法对电镀结合剂金刚石划片刀选型有较好的指导意义,验证结果与算法寻优结果仅相差0.5μm。
To solve the back-chipping in the cutting process of Al_(2)O_(3)ceramic substrates,four characteristic parameters with significant impact on back chipping during the cutting process with diamond blade were selected as key factors,including abrasive particle size,abrasive concentration,binder hardness and the number of cold water tanks.The back chipping size of ceramic substrates was taken as the response variable.Sample data were selected within the feasible domain of factors by orthogonal experimental design.Gaussian process regression model was used for modeling and particle swarm optimization algorithm was used for optimization.The results show that this method has good guiding significance for the selection of diamond blade with electroplated binder,and the difference between the verification results and the optimization results of the algorithm is only 0.5μm.
作者
佘凤芹
张迪
王战
SHE Fengqin;ZHANG Di;WANG Zhan(School of Management,Zhengzhou University,Zhengzhou 450001,China;Zhengzhou Baochi Di Technology Co.,Ltd.,Zhengzhou 450001,China;Zhengzhou Research Institute for Abrasives&Grinding Co.,Ltd.,Zhengzhou 450001,China)
出处
《超硬材料工程》
CAS
2024年第4期15-19,35,共6页
Superhard Material Engineering
关键词
LED封装
氧化铝陶瓷基板
电镀结合剂
正交试验设计
粒子群优化算法
LED packaging
Alumina Ceramic substrate
electroplated binder
orthogonal experimental design
particle swarm optimization algorithm