Salīdzināt metodes

	Robust Response Surface Methodology	Centrālais kompozītais plāns
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1990	1951
Autors	G. G. Vining and Raymond H. Myers (dual response formulation)	George E. P. Box and K. B. Wilson
Tips	Experimental optimization technique	Response surface experimental design
Pirmavots	Vining, G. G., & Myers, R. H. (1990). Combining Taguchi and response surface philosophies: A dual response approach. Journal of Quality Technology, 22(1), 38–45.	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.
Citi nosaukumi	Robust RSM, dual response surface methodology, robust parameter design via RSM, mean-variance RSM	CCD, Box-Wilson design, central composite response surface design, rotatable central composite design
Saistītās	3	3
Kopsavilkums	Robust Response Surface Methodology (Robust RSM) is an experimental optimization strategy that simultaneously fits two regression models — one for the mean response and one for its variance (or standard deviation) — across a designed experiment. By jointly optimizing these dual surfaces, engineers identify factor settings that hit a performance target while minimizing process variability, combining the empirical model-building power of classical RSM with the variance-reduction goals of robust parameter design.	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.