Usporedite metode

	Analiza osjetljivosti s centralnim kompozitnim dizajnom	Centralni kompozitni nacrt – eksperimentalni nacrt odzivne površine
Područje	Eksperimentalni dizajn	Eksperimentalni dizajn
Obitelj	Process / pipeline	Process / pipeline
Godina nastanka	1951 (CCD); SA integration throughout 1970s–2000s	1951
Tvorac	G. E. P. Box and K. B. Wilson (CCD); sensitivity analysis formalised within RSM by Montgomery and subsequent practitioners	George E. P. Box and K. B. Wilson
Vrsta	Quantitative experimental design with post-hoc sensitivity assessment	Response surface experimental design
Temeljni izvor	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.	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.
Drugi nazivi	SA-CCD, CCD sensitivity analysis, RSM sensitivity analysis, response surface sensitivity study	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Srodne	4	3
Sažetak	Sensitivity analysis with Central Composite Design (CCD) combines a structured, space-filling experimental layout with a systematic examination of how much each input factor drives changes in the response. CCD supports estimation of a full quadratic response surface model; sensitivity analysis then interrogates that model to rank factors by influence, identify interactions, and map the performance landscape — guiding engineers and researchers toward robust operating conditions and efficient optimisation.	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.