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| Hibrid teljes faktoros terv× | Centrális Kompozit Terv – Válaszfelszíni Kísérlettervezés× | |
|---|---|---|
| Tudományterület | Kísérlettervezés | Kísérlettervezés |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1980s–2000s (building on Fisher's 1935 factorial framework) | 1951 |
| Megalkotó≠ | Derived from classical factorial design theory (Fisher, 1935); hybrid extensions developed across engineering literature from the 1980s onward | George E. P. Box and K. B. Wilson |
| Típus≠ | Experimental design strategy | Response surface experimental design |
| Alapmű≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | 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 ↗ |
| Alternatív nevek | hybrid factorial design, mixed full factorial design, combined factorial design, HFFD | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| Kapcsolódó | 3 | 3 |
| Összefoglaló≠ | Hybrid full factorial design is an experimental strategy that applies a full factorial structure to a selected subset of factors — those believed to have the strongest interactions — while treating remaining factors with a reduced or fractional scheme. This hybrid approach balances the complete interaction information of a full factorial with the run-count efficiency of fractional designs, making it practical for studies with many factors where a pure full factorial would be prohibitively expensive. | 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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