New approaches for simulation of wafer fabrication: the use of control variates and calibration metrics

Simulation-based wafer fabrication optimization models require extensive computational time to obtain accurate estimates of output parameters. This research seeks to develop goal-driven optimization methodologies for a variety of semiconductor manufacturing problems using appropriate combinations of "resource-driven" (R-D), "job-driven" (J-D), and mixed (combination of R-D and J-D) models to reduce simulation run times. The initial phase of this research investigates two issues: (a) the use of the R-D simulation control variates for the J-D simulation and (b) development of metrics that calibrate the output from the R-D and J-D modeling paradigms. The use of the R-D model as a control variate is proposed to reduce the variance of J-D model output. Second, in order to use the R-D model output to predict the J-D model output, calibration metrics for the R-D and J-D modeling approaches were developed. Initial developments were tested using an M/M/1 queuing system and an M/D/1 queuing system.

[1]  Jin Wang,et al.  Approximation-assisted point estimation , 1997, Oper. Res. Lett..

[2]  James R. Wilson,et al.  Control variates for stochastic network simulation , 1990, 1990 Winter Simulation Conference Proceedings.

[3]  Bruce W. Schmeiser,et al.  Time-dependent queueing network approximations as simulation external control variates , 1994, Oper. Res. Lett..

[4]  R. Syski,et al.  Fundamentals of Queueing Theory , 1999, Technometrics.

[5]  Carl M. Harris,et al.  Fundamentals of queueing theory (2nd ed.). , 1985 .

[6]  Michael R. Taaffe,et al.  External control variance reduction for nonstationary simulation , 1983, WSC '83.

[7]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[8]  Stephen S. Lavenberg,et al.  Concomitant Control Variables Applied to the Regenerative Simulation of Queuing Systems , 1979, Oper. Res..

[9]  Bruce W. Schmeiser,et al.  Biased control-variate estimation , 2001 .

[10]  Stephen S. Lavenberg,et al.  Statistical Results on Control Variables with Application to Queueing Network Simulation , 1982, Oper. Res..

[11]  Stephen S. Lavenberg,et al.  A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations , 1981 .

[12]  Dennis Schaeffer,et al.  Efficient Monte-Carlo simulation of a product-form model for a cellular system with dynamic resource sharing , 1995, TOMC.

[13]  Barry L. Nelson,et al.  Analytic and External Control Variates for Queueing Network Simulation , 1988 .

[14]  Reuven Y. Rubinstein,et al.  Efficiency of Multivariate Control Variates in Monte Carlo Simulation , 1985, Oper. Res..

[15]  Lee W. Schruben,et al.  Resource graphs for modeling large-scale, highly congested systems , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).