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Dynamic Response Surface Models: A Data-Driven Approach for the Analysis of Time-Varying Process Outputs
5 references·4 citing·29 second hop
Dynamic Response Surface Models: A Data-Driven Approach for the Analysis of Time-Varying Process Outputs (2016)Dynamic Response Surface Models: A Data-D…Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes (2013)Design of Dynamic Experiments…Design and Analysis of Experiments (2012)Design and Analysis of Experi…Modeling and optimization I: Usability of response surface methodology (2006)Modeling and optimization I: …Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response Surface Methodology:…Empirical Model Building and Response Surfaces (1988)Empirical Model Building and …Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development (2021)Automation Technologies to En…Uniting laboratory automation, DoE data, and modeling techniques to accelerate chemical process development (2019)Uniting laboratory automation…Opportunities and Challenges for Statisticians in Advanced Pharmaceutical Manufacturing (2019)Opportunities and Challenges …Kinetic and Data-Driven Reaction Analysis for Pharmaceutical Process Development (2019)Kinetic and Data-Driven React…Statistics for Experimenters (1979)Book Review: Statistical Principles in Experimental Design (1992)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)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)Response surface methodology: A neural network approach (1997)Response surface methodology (RSM) as a tool for optimization in analytical chemistry (2008)Applications of Response Surface Methodology in the Food Industry Processes (2017)Experimental design and response surface methodology in energy applications: A tutorial review (2017)Designing robust optimal dynamic experiments (2002)Response Surfaces, Mixtures, and Ridge Analyses (2006)Intensified design of experiments for upstream bioreactors (2016)Multivariate Analysis and Statistics in Pharmaceutical Process Research and Development (2017)GPdoemd: A Python package for design of experiments for model discrimination (2019)Book Review: Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building (1979)Design and Optimization in Organic Synthesis (1992)Positioning and Power in Academic Publishing: Players, Agents and Agendas (2016)Statistics for Spatial Data (1993)The Design and Analysis of Computer Experiments (2003)Design and Modeling for Computer Experiments (2005)Response surface methodology using Gaussian processes: Towards optimizing the trans-stilbene epoxidation over Co2+–NaX catalysts (2009)An Example of Utilizing Mechanistic and Empirical Modeling in Quality by Design (2010)High-Throughput Automated Design of Experiment (DoE) and Kinetic Modeling to Aid in Process Development of an API (2017)Analysis of Design of Experiments with Dynamic Responses (2015)Design and Analysis of Experiments (1998)Response surface methodology (2010)Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study (2016)Design of experiments (DoE) in pharmaceutical development (2017)A review of machine learning for the optimization of production processes (2019)
this work references cited by second hop

References

  • 1996Response Surface Methodology: Process and Product Optimization Using Designed Experiments9,554 cited
  • 1988Empirical Model Building and Response Surfaces5,253 cited
  • 2006Modeling and optimization I: Usability of response surface methodology2,169 cited
  • 2012Design and Analysis of Experiments2,037 cited
  • 2013Design of Dynamic Experiments: A Data-Driven Methodology for the Optimization of Time-Varying Processes77 cited

Cited by

  • 2019Uniting laboratory automation, DoE data, and modeling techniques to accelerate chemical process development28 cited
  • 2019Kinetic and Data-Driven Reaction Analysis for Pharmaceutical Process Development27 cited
  • 2021Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development24 cited
  • 2019Opportunities and Challenges for Statisticians in Advanced Pharmaceutical Manufacturing5 cited

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