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The integration of simulation and response surface methodology for the optimization of IC processes
10 references·1 citing·27 second hop
The integration of simulation and response surface methodology for the optimization of IC processes (1994)The integration of simulation and respons…Empirical Model Building and Response Surface (1998)Empirical Model Building and …Response Surface Methodology (1996)Response Surface MethodologyQuality Engineering Using Robust Design (1991)Quality Engineering Using Rob…Statistical equipment modeling for VLSI manufacturing: an application for LPCVD (1990)Statistical equipment modelin…Quality Engineering Using Robust Design (1990)Quality Engineering Using Rob…Response Surface Methodology: 1966-1988 (1989)Response Surface Methodology:…Quality Engineering using Design of Experiments (1989)Quality Engineering using Des…Empirical Model Building and Response Surfaces (1988)Empirical Model Building and …Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building. (1979)Statistics for Experimenters:…Statistics for experimenters. An introduction to design, data analysis, and model building. (1978)Statistics for experimenters.…Comparison of optimization by response surface methodology with neurofuzzy methods (2000)Comparison of optimization by…Statistics for Experimenters (1979)Response Surfaces: Designs and Analyses (1997)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data (2014)Simultaneous Optimization of Several Response Variables (1980)Designing Environmental Field Studies (1991)Optimization via simulation: A review (1994)Experimental design and response surface methodology in energy applications: A tutorial review (2017)The Sequential Generation of $D$-Optimum Experimental Designs (1970)Modeling, optimization and control of spatial uniformity in manufacturing processes (1993)Using qualitative observations for process tuning and control [IC manufacture] (1997)THE DESIGN OF OPTIMUM MULTIFACTORIAL EXPERIMENTS (1946)Experimental Design: Review and Comment (1984)Signal-to-Noise Ratios, Performance Criteria, and Transformations (1988)The Taguchi methodology as a statistical tool for biotechnological applications: A critical appraisal (2008)Taguchi's Parameter Design: A Panel Discussion (1992)Response Surface Methodology: A Retrospective and Literature Survey (2004)Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design (2004)A review of techniques for parameter sensitivity analysis of environmental models (1994)Multi-response simulation optimization using genetic algorithm within desirability function framework (2005)Are computational models of any use to psychiatry? (2011)The use and importance of design of experiments (DOE) in process modelling in food science and technology (2013)Response surface methodology (2010)Robust Design: An Overview (2006)Design and Analysis of Experiments (1998)Model-based design of experiments for parameter precision: State of the art (2007)Necessary Condition Analysis (NCA) (2015)
this work references cited by second hop

References

  • 1988Empirical Model Building and Response Surfaces5,235 cited
  • 1978Statistics for experimenters. An introduction to design, data analysis, and model building.4,021 cited
  • 1996Response Surface Methodology3,819 cited
  • 1991Quality Engineering Using Robust Design3,458 cited
  • 1990Quality Engineering Using Robust Design2,125 cited
  • 1979Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building.2,003 cited
  • 1989Quality Engineering using Design of Experiments596 cited
  • 1989Response Surface Methodology: 1966-1988594 cited
  • 1998Empirical Model Building and Response Surface282 cited
  • 1990Statistical equipment modeling for VLSI manufacturing: an application for LPCVD62 cited

Cited by

  • 2000Comparison of optimization by response surface methodology with neurofuzzy methods31 cited

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