基于动态MANCOVA的混合制程虚拟测量算法  

Virtual metrology based on dynamic MANCOVA for high-mixed manufacturing process

作　　者：潘天红[1] 杨一力[1] 

机构地区：[1]江苏大学电气信息工程学院,江苏镇江212013

出　　处：《控制与决策》2014年第11期2071-2075,共5页Control and Decision

基　　金：国家自然科学基金项目(61273142);江苏省自然科学基金项目(BK2011466);江苏省六大人才高峰项目(2012-DZXX-045);江苏省高校优势学科建设工程项目(PAPD)

摘　　要：在晶圆/液晶面板等批次加工过程中,产品质量的及时估计与品质管制是提高产能和降低成本的有效途径.针对"少量多样"的混合制程,利用逐步回归算法挑选该制程的关毽变量,引入产品的效益因子,建立混合制程的虚拟测量模型;为克服系统扰动对模型精度的影响,以产品效益因子为状态量建立该制程的状态方程,利用Kalman滤波器递归估计模型参数得到动态的MANCOVA模型;最后通过某湿式蚀刻制程的工程应用验证了该算法的有效性.In the semiconductor/TFT-LCD manufacturing industry,the timely quality estimation and control of products are the key solutions for the throughput improvement and cost reduction.Therefore,a virtual metrology model is present for high-mixed manufacturing processes with variety products under small quantity.By using the stepwise regression,the key variables are selected from the process variables monitored by the fault detection classification（FDC） system.Then,combined with the product-effect factors,the virtual metrology model is built for multi-products by using the analysis of variance（ANOVA） algorithm.To reduce the disturbance effect,a state estimation method based on ANOVA is developed to estimate the relative states of each product.The method is formulated in the form of a recursive state estimation by using the Kalman filter.Numerical simulations are implemented by using practical production data from a wet etching process of TFT-LCD industry.The results show that proper variable selection and dynamic MANCOVA can improve the precision of prediction models effectively.

关 键 词：多变量共变异数分析 卡尔曼滤波算法 混合制程 虚拟测量 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]