This work describes the fabrication facility (FAB)
implementation of a multivariable nonlinear model
predictive controller (NMPC) for the regulation of
critical dimensions (CD) in photolithography. The
controller is based on nonlinear empirical models
relating the stepper inputs, exposure dose and focus on
the isolated and dense CDs measured by scanning
electron microscopy. Since the adjustments are made on
the basis of the average value of five measured points
in each wafer, this is referred to as average mode
control. The optimal structure and parameters of these
empirical models were determined by genetic
programming, to closely match FAB data. The tuning and
testing of the NMPC regulator were facilitated by the
use of a simulated photolithography track, using the
KLA-Tencor-FINLE PROLITH package, suitably calibrated
to match FAB conditions. On implementation in the FAB,
the NMPC has been demonstrated to consistently maintain
the CDs close to their setpoint values, despite
unmeasured disturbances such as shifts in uncontrolled
inputs. It was also shown that adopting the
multivariable feedback regulatory strategy to regulate
the CDs results in significant improvements in the die
yield.
%0 Journal Article
%1 Grosman:2005:tSM
%A Grosman, Benyamin
%A Lachman-Shalem, Sivan
%A Swissa, Raaya
%A Lewin, D. R.
%D 2005
%J IEEE Transactions on Semiconductor Manufacturing
%K KLA-Tencor-FINLE PROLITH algorithms, average based circuit control control, controller, electron empirical enhancement fabrication facility feedback genetic implementation, inputs, integrated manufacture, microscopy, mode model modelling models, multivariable nonlinear optimal package, parameters, photolithography, predictive process programming, regulatory scanning semiconductor setpoint simulated stepper strategy, structure, systems, values, yield
%N 1
%P 86--93
%R 10.1109/TSM.2004.836654
%T Yield enhancement in photolithography through
model-based process control: average mode control
%V 18
%X This work describes the fabrication facility (FAB)
implementation of a multivariable nonlinear model
predictive controller (NMPC) for the regulation of
critical dimensions (CD) in photolithography. The
controller is based on nonlinear empirical models
relating the stepper inputs, exposure dose and focus on
the isolated and dense CDs measured by scanning
electron microscopy. Since the adjustments are made on
the basis of the average value of five measured points
in each wafer, this is referred to as average mode
control. The optimal structure and parameters of these
empirical models were determined by genetic
programming, to closely match FAB data. The tuning and
testing of the NMPC regulator were facilitated by the
use of a simulated photolithography track, using the
KLA-Tencor-FINLE PROLITH package, suitably calibrated
to match FAB conditions. On implementation in the FAB,
the NMPC has been demonstrated to consistently maintain
the CDs close to their setpoint values, despite
unmeasured disturbances such as shifts in uncontrolled
inputs. It was also shown that adopting the
multivariable feedback regulatory strategy to regulate
the CDs results in significant improvements in the die
yield.
@article{Grosman:2005:tSM,
abstract = {This work describes the fabrication facility (FAB)
implementation of a multivariable nonlinear model
predictive controller (NMPC) for the regulation of
critical dimensions (CD) in photolithography. The
controller is based on nonlinear empirical models
relating the stepper inputs, exposure dose and focus on
the isolated and dense CDs measured by scanning
electron microscopy. Since the adjustments are made on
the basis of the average value of five measured points
in each wafer, this is referred to as average mode
control. The optimal structure and parameters of these
empirical models were determined by genetic
programming, to closely match FAB data. The tuning and
testing of the NMPC regulator were facilitated by the
use of a simulated photolithography track, using the
KLA-Tencor-FINLE PROLITH package, suitably calibrated
to match FAB conditions. On implementation in the FAB,
the NMPC has been demonstrated to consistently maintain
the CDs close to their setpoint values, despite
unmeasured disturbances such as shifts in uncontrolled
inputs. It was also shown that adopting the
multivariable feedback regulatory strategy to regulate
the CDs results in significant improvements in the die
yield.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Grosman, Benyamin and Lachman-Shalem, Sivan and Swissa, Raaya and Lewin, D. R.},
biburl = {https://www.bibsonomy.org/bibtex/2de7e74f446b0ed19dd86ec08cede2b44/brazovayeye},
doi = {10.1109/TSM.2004.836654},
interhash = {340e65378fb215fe36fcbf8abe219ef9},
intrahash = {de7e74f446b0ed19dd86ec08cede2b44},
issn = {0894-6507},
journal = {IEEE Transactions on Semiconductor Manufacturing},
keywords = {KLA-Tencor-FINLE PROLITH algorithms, average based circuit control control, controller, electron empirical enhancement fabrication facility feedback genetic implementation, inputs, integrated manufacture, microscopy, mode model modelling models, multivariable nonlinear optimal package, parameters, photolithography, predictive process programming, regulatory scanning semiconductor setpoint simulated stepper strategy, structure, systems, values, yield},
month = {February},
number = 1,
pages = {86--93},
timestamp = {2008-06-19T17:40:41.000+0200},
title = {Yield enhancement in photolithography through
model-based process control: average mode control},
volume = 18,
year = 2005
}