Evaluating reliance level of a virtual metrology system

被引:60
作者
Cheng, Fan-Tien [1 ]
Chen, Yeh-Tung [1 ]
Su, Yu-Chuan [2 ]
Zeng, Deng-Lin [1 ]
机构
[1] Natl Cheng Kung Univ, Inst Mfg Engn, Tainan 701, Taiwan
[2] Far East Univ, Dept Comp Sci & Informat Engn, Tainan 744, Taiwan
关键词
degree of similarity; global similarity index (GSI); individual similarity index (ISI); manufacturability; reliance index (RI); reliance level; virtual metrology system (VMS);
D O I
10.1109/TSM.2007.914373
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper proposes a novel method for evaluating the reliability of a virtual metrology system (VMS). The proposed method calculates a reliance index (RI) value between zero and one by analyzing the process data of production equipment to determine the reliability of the virtual metrology results. This method also defines an RI threshold. If an RI value exceeds the threshold, the conjecture result is reliable; otherwise, the conjecture result needs to be further examined. Besides the RI, the method also proposes process data similarity indexes (SIs). The SIs are defined to assess the degree of similarity between the input set of process data and those historical sets of process data used to establish the conjecture model. The proposed method includes two types of SIs: global similarity index (GSI) and individual similarity index (ISI). Both GSI and ISI are applied to-assist the RI in gauging the reliance level and locating the key parameter(s) that cause major deviation, thus resolving the VMS manufacturability problem. An illustrative example involving 300-mm semiconductor foundry etching equipment is presented. Experimental results demonstrate that the proposed method is applicable to the VMS of production equipment (such as that for semiconductor and TFT-LCD).
引用
收藏
页码:92 / 103
页数:12
相关论文
共 19 条
[1]  
[Anonymous], 2002, The Mahalanobis-Taguchi Strategy: A Pattern Technology System
[2]  
CHANG J, 2006, P 2006 IEEE INT C AU, P240
[3]  
Chang JYC, 2005, IEEE IND ELEC, P124
[4]  
Chatterjee S., 2013, Regression analysis by example
[5]   Virtual metrology: A solution for wafer to wafer advanced process control [J].
Chen, PH ;
Wu, S ;
Lin, JS ;
Ko, F ;
Lo, H ;
Wang, J ;
Yu, CH ;
Liang, MS .
ISSM 2005: IEEE International Symposium on Semiconductor Manufacturing, Conference Proceedings, 2005, :155-157
[6]   Dual-phase virtual metrology scheme [J].
Cheng, Fan-Tien ;
Huang, Hsien-Cheng ;
Kao, Chi-An .
IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, 2007, 20 (04) :566-571
[7]   Confidence interval prediction for neural network models [J].
Chryssolouris, G ;
Lee, M ;
Ramsey, A .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1996, 7 (01) :229-232
[8]  
DRURDJANOVIC D, 2003, ADV ENG INFORM, V17, P109
[9]  
HOGG RV, 2001, PROBABILITY STAT REF
[10]  
HUANG YT, 2006, P 32 ANN C IEEE IND