পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ফ্র্যাকশনাল ফ্যাক্টোরিয়াল ডিজাইন সহ সংবেদনশীলতা বিশ্লেষণ× | রেসপন্স সারফেস মেথডোলজি (RSM)× | |
|---|---|---|
| ক্ষেত্র | পরীক্ষামূলক নকশা | পরীক্ষামূলক নকশা |
| পরিবার≠ | Process / pipeline | Hypothesis test |
| উদ্ভবের বছর≠ | 1935 (factorial design); 1990s–2000s (systematic SA integration) | 1951 |
| প্রবর্তক≠ | R. A. Fisher (factorial design foundations); combined with sensitivity analysis frameworks developed by A. Saltelli and colleagues | George E. P. Box & K. B. Wilson |
| ধরন≠ | Quantitative experimental screening method | Second-order polynomial response surface model |
| মৌলিক উৎস≠ | 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 ↗ |
| অপর নাম≠ | FFD sensitivity analysis, fractional factorial sensitivity screening, SA-FFD, screening design sensitivity analysis | RSM, Central Composite Design, Box-Behnken Design, CCD |
| সম্পর্কিত≠ | 1 | 7 |
| সারসংক্ষেপ≠ | Sensitivity analysis with fractional factorial design (SA-FFD) is an experimental screening method that uses a carefully chosen fraction of all possible factor combinations to identify which input variables most strongly influence a system's output. By running only 2^(k-p) experiments instead of a full 2^k factorial, it makes sensitivity ranking feasible when many factors are present. The approach is widely used in engineering, product development, simulation modeling, and process optimization. | 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. |
| ScholarGateডেটাসেট ↗ |
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