Vertaile menetelmiä

	Hybridikokeiden suunnittelu	Keskiarvokeskeinen suunnittelu
Tieteenala	Koesuunnittelu	Koesuunnittelu
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	1989–2000s	1951
Kehittäjä	Multiple contributors; notably Sacks, Welch, Mitchell & Wynn (computer experiments); broader hybrid concept developed across 1980s–2000s	George E. P. Box and K. B. Wilson
Tyyppi	Combined experimental design strategy	Response surface experimental design
Alkuperäislähde	Santner, T. J., Williams, B. J., & Notz, W. I. (2003). The Design and Analysis of Computer Experiments. Springer. ISBN: 978-1441929921	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.
Rinnakkaisnimet	hybrid DOE, combined experimental design, mixed experimental design, hybrid experimental strategy	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Liittyvät	4	3
Tiivistelmä	Hybrid design of experiments (hybrid DOE) combines two or more experimental design strategies within a single study to exploit the complementary strengths of each. Common combinations include factorial or fractional-factorial arrays paired with computer simulation runs, space-filling Latin hypercube designs merged with response surface augmentations, or Taguchi orthogonal arrays integrated with response surface methodology. The approach is widely used when a single design type cannot efficiently cover all phases of an engineering investigation — from screening through to optimization.	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.