Comparer des méthodes

	Conception Hybride en Plans Fractionnaires	Méthodologie des surfaces de réponse (RSM)
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Hypothesis test
Année d'origine	1970s–1990s (formalized as a distinct design class)	1951
Auteur d'origine	Developed across the DOE community; foundational contributions by Box, Hunter & Hunter and Wu & Hamada	George E. P. Box & K. B. Wilson
Type	Experimental design	Second-order polynomial response surface model
Source fondatrice	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.
Alias	HFFD, hybrid FFD, combined fractional factorial design, mixed fractional factorial design	RSM, Central Composite Design, Box-Behnken Design, CCD
Apparentées	3	7
Résumé	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.