Módszerek összehasonlítása
Tekintse át a kiválasztott módszereket egymás mellett; az eltérő sorok kiemelve jelennek meg.
| Optimalizálással Támogatott Válaszfelület Módszer× | Centrális Kompozit Terv – Válaszfelszíni Kísérlettervezés× | |
|---|---|---|
| Tudományterület | Kísérlettervezés | Kísérlettervezés |
| Módszercsalád | Process / pipeline | Process / pipeline |
| Keletkezés éve≠ | 1951 (RSM); 1980 (desirability-function optimization formalized) | 1951 |
| Megalkotó≠ | Derringer & Suich (desirability function); Box & Wilson (RSM foundation) | George E. P. Box and K. B. Wilson |
| Típus≠ | Hybrid experimental-optimization framework | Response surface experimental design |
| Alapmű≠ | Derringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗ | 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. DOI ↗ |
| Alternatív nevek | OA-RSM, RSM with optimization, desirability-based RSM, multi-response RSM optimization | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| Kapcsolódó≠ | 5 | 3 |
| Összefoglaló≠ | Optimization-assisted RSM couples a second-order response surface model with a mathematical optimization routine — most commonly Derringer and Suich's desirability function, but also genetic algorithms or gradient-based solvers — to locate the factor settings that simultaneously satisfy multiple quality or performance objectives. The result is a data-driven recommendation for optimal process or product conditions, supported by a polynomial model fitted to a structured experimental 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. |
| ScholarGateAdatkészlet ↗ |
|
|