Process / pipelineEngineering methods

Central Composite Design — Response Surface Experimental Design

Central Composite Design (CCD) is a second-order response surface design that allows researchers to efficiently fit a full quadratic model relating multiple continuous input factors to one or more response variables. Introduced by Box and Wilson in 1951, it combines a factorial (or fractional factorial) core, axial (star) points, and center-point replicates into a single unified design, making it the most widely used design for process optimization in engineering, chemistry, and manufacturing.

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Box, G. E. P., & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society: Series B, 13(1), 1–45. DOI: 10.1111/j.2517-6161.1951.tb00067.x ↗
Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443

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Adaptive Fractional Factorial Experiment Bayesian Box-Behnken Design Bayesian Design of Experiments Bayesian Fractional Factorial Design Bayesian Full Factorial Design Box-Behnken Design Design of experiments Hybrid Box-Behnken Design Hybrid Central Composite Design Hybrid design of experiments Hybrid Fractional Factorial Design Hybrid Full Factorial Design Hybrid Response Surface Methodology Industrial applications full factorial design Industrial Applications Response Surface Methodology Mixture Design Multi-response Design of Experiments Multi-response Response Surface Methodology Optimal Experimental Design Optimization-assisted Box-Behnken design Optimization-assisted central composite design Optimization-assisted design of experiments Optimization-assisted fractional factorial design Optimization-assisted response surface methodology Plackett-Burman Design Risk-based Box-Behnken Design Risk-based central composite design Risk-based Response Surface Methodology Robust Box-Behnken Design Robust Central Composite Design Robust Fractional Factorial Design Robust Response Surface Methodology Sensitivity Analysis with Box-Behnken Design Sensitivity analysis with central composite design Sensitivity analysis-integrated response surface methodology Simulation-assisted design of experiments Simulation-assisted fractional factorial design Simulation-assisted full factorial design Simulation-assisted response surface methodology

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