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| Risk-based Central Composite Design× | Keskkonstandsard-koostis-disain× | |
|---|---|---|
| Valdkond | Katsedisain | Katsedisain |
| Perekond | Process / pipeline | Process / pipeline |
| Tekkeaasta≠ | 1951 (CCD); risk-based integration emerged in applied engineering literature from the 1990s onward | 1951 |
| Looja≠ | Foundational CCD: George E. P. Box & K. B. Wilson (1951); risk integration adapted from engineering risk analysis traditions | George E. P. Box and K. B. Wilson |
| Tüüp≠ | Experimental design with integrated risk assessment | Response surface experimental design |
| Algallikas | 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 ↗ | 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 ↗ |
| Rööpnimetused | Risk-informed CCD, CCD with risk assessment, Uncertainty-aware central composite design, Risk-integrated RSM | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| Seotud≠ | 5 | 3 |
| Kokkuvõte≠ | Risk-based Central Composite Design (Risk-based CCD) integrates formal risk identification and uncertainty quantification into the classical CCD framework. By coupling the rotatable second-order experimental structure of CCD with probabilistic risk metrics, engineers and scientists can simultaneously optimize process responses and characterize the risk of unacceptable outcomes — making it particularly valuable in regulated industries such as pharmaceuticals, chemical engineering, and advanced manufacturing. | 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. |
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