DocumentCode :
1763986
Title :
Feasibility Evaluation of Virtual Metrology for the Example of a Trench Etch Process
Author :
Roeder, G. ; Winzer, Sirko ; Schellenberger, Martin ; Jank, Stefan ; Pfitzner, Lothar
Author_Institution :
Fraunhofer Inst. for Integrated Syst. & Device Technol. (IISB), Erlangen, Germany
Volume :
27
Issue :
3
fYear :
2014
fDate :
Aug. 2014
Firstpage :
327
Lastpage :
334
Abstract :
In semiconductor manufacturing, the implementation of advanced process control systems has become essential for cost effective manufacturing at high product quality. In addition to established process control methods, new control techniques such as virtual metrology, where post-process quality parameters are predicted from process and wafer state information need to be developed and implemented for critical process steps. This requires a fab-wide approach due to the objectives of VM, which are to supplement or replace stand-alone and in-line metrology operations, to support fault detection and classification, run-to-run control, or other new control entities such as predictive maintenance. Virtual metrology is typically based on statistical learning methods, and a large variety of potentially applicable algorithms are available. A key challenge of the virtual metrology application is proving its capability to produce precise predictions even in complex semiconductor manufacturing processes. In addition, virtual metrology applications need to be implementable into the specific automation and control environment already present in the respective fab. In this paper, the approach and results of a feasibility study toward the development and implementation of virtual metrology applications in a logic fab are presented. The feasibility study was performed for the prediction of trench depth after a complex dry etch process as the specific use case studied.
Keywords :
etching; fault diagnosis; integrated circuit manufacture; statistical analysis; advanced process control systems; complex dry etch process; complex semiconductor manufacturing processes; cost effective manufacturing; fault classification; fault detection; high product quality; in-line metrology operations; post-process quality parameters; predictive maintenance; run-to-run control; statistical learning methods; trench depth prediction; trench etch process; virtual metrology feasibility evaluation; wafer state information; Boosting; Data models; Metrology; Prediction algorithms; Predictive models; Process control; Training; Advanced process control; manufacturing data processing; stochastic gradient boosting; virtual metrology;
fLanguage :
English
Journal_Title :
Semiconductor Manufacturing, IEEE Transactions on
Publisher :
ieee
ISSN :
0894-6507
Type :
jour
DOI :
10.1109/TSM.2014.2321192
Filename :
6808539
Link To Document :
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