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Full Factorial Experimental Design×Responsytsmetodologi (RSM)×
ÄmnesområdeFörsöksplaneringFörsöksplanering
FamiljHypothesis testHypothesis test
Ursprungsår19261951
UpphovspersonR. A. FisherGeorge E. P. Box & K. B. Wilson
TypParametric factorial experimentSecond-order polynomial response surface model
UrsprungskällaBox, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130Box, 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. link ↗
Aliasfactorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k)RSM, Central Composite Design, Box-Behnken Design, CCD
Närliggande57
SammanfattningA full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured.Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics.
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ScholarGateJämför metoder: Full Factorial Design · Response Surface Methodology. Hämtad 2026-06-18 från https://scholargate.app/sv/compare