Comparer des méthodes

	Méthodologie de surface de réponse assistée par simulation	Planification Composite Centrale
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1951 (RSM); simulation integration widely adopted from 1980s onward	1951
Auteur d'origine	Box & Wilson (RSM foundation); Kleijnen and others for simulation-based extensions	George E. P. Box and K. B. Wilson
Type	Experimental optimization method	Response surface experimental design
Source fondatrice	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916025	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	SA-RSM, simulation-based RSM, computer simulation RSM, metamodel-assisted RSM	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Apparentées	6	3
Résumé	Simulation-assisted response surface methodology (SA-RSM) combines computer simulation models — such as finite element analysis, computational fluid dynamics, or discrete-event simulation — with the statistical framework of response surface methodology to efficiently map, model, and optimize system responses. Instead of running physical experiments, the researcher executes simulation runs at design points prescribed by an RSM design, fits a polynomial metamodel (surrogate) to the simulation outputs, and uses that metamodel to locate optimal factor settings.	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.