পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| সিমুলেশন-সহায়তায় পূর্ণ ফ্যাক্টোরিয়াল ডিজাইন× | পরীক্ষা নকশা× | |
|---|---|---|
| ক্ষেত্র | পরীক্ষামূলক নকশা | পরীক্ষামূলক নকশা |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1990s–2000s (simulation-DOE integration formalized) | 1935 |
| প্রবর্তক≠ | Montgomery (DOE foundations); Kleijnen (simulation DOE formalization) | Ronald A. Fisher |
| ধরন≠ | Experimental design with computer simulation | Experimental planning framework |
| মৌলিক উৎস≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| অপর নাম | SA-FFD, computer simulation full factorial, virtual full factorial design, simulation-based full factorial DOE | DOE, experimental design, factorial experimentation, planned experimentation |
| সম্পর্কিত≠ | 4 | 3 |
| সারসংক্ষেপ≠ | Simulation-assisted full factorial design integrates full factorial design of experiments (DOE) with computer simulation models — such as discrete-event simulation, finite element analysis, or Monte Carlo methods — to systematically explore every combination of factor levels and quantify their effects on system responses. It enables comprehensive experimentation in contexts where physical trials would be costly, dangerous, or infeasible. | Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences. |
| ScholarGateডেটাসেট ↗ |
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