Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Пълнофакторен експериментален план× | Метод на Тагучи (ортогонални масиви, съотношение сигнал/шум)× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Hypothesis test | Hypothesis test |
| Година на възникване≠ | 1926 | 1987 |
| Създател≠ | R. A. Fisher | Genichi Taguchi |
| Тип≠ | Parametric factorial experiment | Parametric robust design methodology |
| Основополагащ източник≠ | Box, G. E. P., Hunter, J. S., & Hunter, W. G. (2005). Statistics for Experimenters: Design, Innovation, and Discovery (2nd ed.). Wiley. ISBN: 978-0471718130 | Taguchi, G. (1987). System of Experimental Design. UNIPUB/Kraus. ISBN: 978-0527916312 |
| Други названия | factorial experiment, 2^k factorial, full factorial, Faktöriyel Deneme Deseni (Full Factorial, 2^k) | Taguchi robust design, orthogonal array design, S/N ratio method, Taguchi Yöntemi (Ortogonal Dizi, S/N Oranı) |
| Свързани≠ | 5 | 3 |
| Резюме≠ | A full factorial design is a parametric experimental method in which every combination of factor levels is tested simultaneously, enabling the estimation of all main effects and all interaction effects in a single study. Rooted in R. A. Fisher's foundational work on designed experiments (1926) and systematically developed by Box, Hunter, and Hunter (2005) and Montgomery (2017), the 2^k form tests k two-level factors across 2^k experimental runs and is the benchmark against which all other factorial designs are measured. | The Taguchi Method is a robust design methodology developed by Genichi Taguchi, first systematized in his 1987 work, that uses orthogonal arrays to study many control factors in a minimum number of experimental runs while quantifying product or process quality through Signal-to-Noise (S/N) ratios. Its central goal is to design products and processes that are insensitive — or robust — to uncontrollable noise factors such as environmental variation, material inconsistency, or user behavior. |
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