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| Πειραματικός Σχεδιασμός Κλασματικού Παραγοντικού Πειράματος× | Μεθοδολογία Επιφανειών Απόκρισης (RSM)× | |
|---|---|---|
| Πεδίο | Πειραματικός Σχεδιασμός | Πειραματικός Σχεδιασμός |
| Οικογένεια≠ | Process / pipeline | Hypothesis test |
| Έτος προέλευσης≠ | 1945 (Finney); broader development 1950s–1970s by Box, Hunter | 1951 |
| Δημιουργός≠ | D. J. Finney (formal development); foundations in Ronald Fisher's factorial design work | George E. P. Box & K. B. Wilson |
| Τύπος≠ | Quantitative experimental design | Second-order polynomial response surface model |
| Θεμελιώδης πηγή≠ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley-Interscience. ISBN: 978-0471718130 | 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. link ↗ |
| Εναλλακτικές ονομασίες≠ | fractional factorial design, FFD, 2^(k-p) design, fractional replication | RSM, Central Composite Design, Box-Behnken Design, CCD |
| Συναφείς≠ | 4 | 7 |
| Σύνοψη≠ | A fractional factorial experiment is a resource-efficient experimental design that tests only a carefully chosen fraction of all possible factor-level combinations. By exploiting the principle that high-order interactions are usually negligible, it identifies the main effects and low-order interactions of k factors using far fewer runs than a full factorial design — making it the workhorse of industrial and engineering screening experiments. | Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics. |
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