השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| מתודולוגיית משטח התגובה בסיוע סימולציה× | תכנון מרכזי מורכב – תכנון ניסויי של משטח תגובה× | |
|---|---|---|
| תחום | תכנון ניסויים | תכנון ניסויים |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1951 (RSM); simulation integration widely adopted from 1980s onward | 1951 |
| הוגה השיטה≠ | Box & Wilson (RSM foundation); Kleijnen and others for simulation-based extensions | George E. P. Box and K. B. Wilson |
| סוג≠ | Experimental optimization method | Response surface experimental design |
| מקור מכונן≠ | 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: 978-1118916025 | 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 ↗ |
| כינויים | SA-RSM, simulation-based RSM, computer simulation RSM, metamodel-assisted RSM | CCD, Box-Wilson design, central composite response surface design, rotatable central composite design |
| קשורות≠ | 6 | 3 |
| תקציר≠ | Simulation-assisted response surface methodology (SA-RSM) combines computer simulation models — such as finite element analysis, computational fluid dynamics, or discrete-event simulation — with the statistical framework of response surface methodology to efficiently map, model, and optimize system responses. Instead of running physical experiments, the researcher executes simulation runs at design points prescribed by an RSM design, fits a polynomial metamodel (surrogate) to the simulation outputs, and uses that metamodel to locate optimal factor settings. | 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. |
| ScholarGateמערך נתונים ↗ |
|
|