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| Методология на повърхността на отговора, подпомогната от оптимизация× | Централен композитен дизайн× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1951 (RSM); 1980 (desirability-function optimization formalized) | 1951 |
| Създател≠ | Derringer & Suich (desirability function); Box & Wilson (RSM foundation) | George E. P. Box and K. B. Wilson |
| Тип≠ | Hybrid experimental-optimization framework | Response surface experimental design |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | 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 |
| Свързани≠ | 5 | 3 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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