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| Thiết kế toàn yếu tố có hỗ trợ tối ưu hóa× | Thiết kế Thí nghiệm× | |
|---|---|---|
| Lĩnh vực | Thiết kế thí nghiệm | Thiết kế thí nghiệm |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1980s–1990s (formalized with desirability functions by Derringer & Suich, 1980) | 1935 |
| Người khởi xướng≠ | Integrated from D. C. Montgomery (DoE) and classical optimization literature | Ronald A. Fisher |
| Loại≠ | Hybrid experimental-optimization workflow | Experimental planning framework |
| Công trình gốc≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Tên gọi khác | OA-FFD, full factorial with optimization, full factorial design with response optimization, DoE-optimization hybrid | DOE, experimental design, factorial experimentation, planned experimentation |
| Liên quan | 3 | 3 |
| Tóm tắt≠ | Optimization-assisted full factorial design is a structured engineering workflow that runs a complete full factorial experiment — covering every combination of factor levels — and then applies a formal optimization method to identify the factor settings that best satisfy one or more performance targets. It combines the exhaustive data coverage of full factorial design with numerical or analytical optimization to turn experimental results into actionable optimal configurations. | 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. |
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