Porównaj metody

	Hybrydowy ułamkowy plan czynnikowy	Metodologia Powierzchni Odpowiedzi (RSM)
Dziedzina	Planowanie eksperymentów	Planowanie eksperymentów
Rodzina	Process / pipeline	Hypothesis test
Rok powstania	1970s–1990s (formalized as a distinct design class)	1951
Twórca	Developed across the DOE community; foundational contributions by Box, Hunter & Hunter and Wu & Hamada	George E. P. Box & K. B. Wilson
Typ	Experimental design	Second-order polynomial response surface model
Źródło pierwotne	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.
Inne nazwy	HFFD, hybrid FFD, combined fractional factorial design, mixed fractional factorial design	RSM, Central Composite Design, Box-Behnken Design, CCD
Pokrewne	3	7
Podsumowanie	A hybrid fractional factorial design (HFFD) merges two or more fractional factorial sub-designs — often involving factors at different numbers of levels or with different aliasing structures — into a single coordinated experiment. The goal is to achieve estimation capabilities (main effects, targeted two-factor interactions) that no single standard fractional design can provide within the same run count, making it especially valuable in engineering development and industrial process optimization.	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.