Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ чувствительности, интегрированный с методологией поверхности отклика× | Центральное композиционное планирование× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1990s–2000s (integration practice) | 1951 |
| Автор метода≠ | Box & Wilson (RSM, 1951); Saltelli et al. (global SA framework, 1990s–2000s) | George E. P. Box and K. B. Wilson |
| Тип≠ | Hybrid experimental-analytical method | Response surface experimental design |
| Основополагающий источник≠ | 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: 978-1118916018 | 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 ↗ |
| Другие названия | SA-RSM, RSM with sensitivity analysis, sensitivity-augmented RSM, response surface methodology with factor screening | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| Связанные≠ | 5 | 3 |
| Сводка≠ | Sensitivity analysis-integrated RSM couples a structured experimental design with a formal sensitivity analysis of the fitted response surface model. After estimating a polynomial surrogate from designed experiments, global or local sensitivity indices are computed to quantify each input factor's relative contribution to output variability. This allows practitioners to identify which factors truly drive the response before committing to full optimization, reducing cost and improving the reliability of the final optimum. | 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 данных ↗ |
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