Yield enhancement in photolithography through model-based process control: average mode control

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Grosman:2005:tSM,
  title =        "Yield enhancement in photolithography through
                 model-based process control: average mode control",
  author =       "Benyamin Grosman and Sivan Lachman-Shalem and 
                 Raaya Swissa and D. R. Lewin",
  journal =      "IEEE Transactions on Semiconductor Manufacturing",
  year =         "2005",
  volume =       "18",
  number =       "1",
  pages =        "86--93",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming, integrated
                 circuit manufacture, multivariable control systems,
                 nonlinear control systems, photolithography, predictive
                 control, process control, scanning electron microscopy,
                 semiconductor process modelling KLA-Tencor-FINLE
                 PROLITH package, average mode control, fabrication
                 facility implementation, genetic programming, model
                 based process control, multivariable feedback
                 regulatory strategy, multivariable nonlinear model
                 predictive controller, nonlinear empirical models,
                 optimal parameters, optimal structure, scanning
                 electron microscopy, setpoint values, simulated
                 photolithography, stepper inputs, yield enhancement",
  DOI =          "doi:10.1109/TSM.2004.836654",
  ISSN =         "0894-6507",
  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.",
}

Genetic Programming entries for Benyamin Grosman Sivan Lachman-Shalem Raaya Swissa Daniel R Lewin

Citations