Advanced studies of selection schemes for dual virtual-metrology outputs

Wei Ming Wu, Fan-Tien Cheng, Tung Ho Lin, Deng Lin Zeng, Jyun Fang Chen, Min Hsiung Hung

研究成果: Conference contribution

摘要

Advanced Studies of selection schemes between neural-network (NN) and multiple-regression (MR) outputs of a virtual metrology system (VMS) are presented in this paper. Both NN and MR are applicable algorithms for implementing VM conjecture models. But a MR algorithm may achieve better accuracy only with a stable process, whereas a NN algorithm may has superior accuracy when equipment property drift or shift occurs. To take advantage of the merits of both MR and NN algorithms, the simple-selection scheme (SS-scheme) was proposed in CASE 2008 to enhance virtual-metrology (VM) conjecture accuracy. This SS-scheme simply selects either NN or MR output. Recently, with advanced studies, a weighted-selection scheme (WS-scheme), which computes the VM output with a weighted sum of NN and MR results, has been developed. Besides the example with the CVD process of fifth generation TFT-LCD used in the CASE 2008 paper, a new example with the photo process is also adopted in this paper to test and compare the conjecture accuracy among solo NN, solo MR, SS-scheme, and WS-scheme. One-hidden-layered back-propagation neural network (BPNN-I) is adopted for establishing the NN conjecture model. Test results show that the conjecture accuracy of the WS-scheme is the best among those of solo NN, solo MR, SS-scheme, and WS-scheme algorithms.

原文English
主出版物標題2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
頁面421-426
頁數6
DOIs
出版狀態Published - 2009 十一月 12
事件2009 IEEE International Conference on Automation Science and Engineering, CASE 2009 - Bangalore, India
持續時間: 2009 八月 222009 八月 25

出版系列

名字2009 IEEE International Conference on Automation Science and Engineering, CASE 2009

Other

Other2009 IEEE International Conference on Automation Science and Engineering, CASE 2009
國家/地區India
城市Bangalore
期間09-08-2209-08-25

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 電腦科學應用
  • 軟體

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