পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| সেন্ট্রাল কম্পোজিট ডিজাইন সহ সংবেদনশীলতা বিশ্লেষণ× | বক্স-বেঙ্কেন ডিজাইন× | |
|---|---|---|
| ক্ষেত্র | পরীক্ষামূলক নকশা | পরীক্ষামূলক নকশা |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1951 (CCD); SA integration throughout 1970s–2000s | 1960 |
| প্রবর্তক≠ | G. E. P. Box and K. B. Wilson (CCD); sensitivity analysis formalised within RSM by Montgomery and subsequent practitioners | George E. P. Box and Donald W. Behnken |
| ধরন≠ | Quantitative experimental design with post-hoc sensitivity assessment | Response surface design (incomplete three-level factorial) |
| মৌলিক উৎস≠ | 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 ↗ | Box, G. E. P., & Behnken, D. W. (1960). Some new three level designs for the study of quantitative variables. Technometrics, 2(4), 455–475. DOI ↗ |
| অপর নাম | SA-CCD, CCD sensitivity analysis, RSM sensitivity analysis, response surface sensitivity study | BBD, Box-Behnken, Box-Behnken RSM design, three-level incomplete factorial design |
| সম্পর্কিত≠ | 4 | 3 |
| সারসংক্ষেপ≠ | Sensitivity analysis with Central Composite Design (CCD) combines a structured, space-filling experimental layout with a systematic examination of how much each input factor drives changes in the response. CCD supports estimation of a full quadratic response surface model; sensitivity analysis then interrogates that model to rank factors by influence, identify interactions, and map the performance landscape — guiding engineers and researchers toward robust operating conditions and efficient optimisation. | The Box-Behnken design (BBD) is an efficient response surface methodology design that fits a full second-order polynomial model using three levels of each factor. Introduced by Box and Behnken in 1960, it places experimental points at the midpoints of the edges of a hypercube and at the center, avoiding the corner points where all factors are simultaneously at their extreme levels. This structure makes BBD particularly attractive when extreme-level combinations are physically impossible, costly, or unsafe to test. |
| ScholarGateডেটাসেট ↗ |
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