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روش سطح پاسخ (RSM)×طراحی کسری عاملی مقاوم×
حوزهطراحی آزمایشطراحی آزمایش
خانوادهHypothesis testProcess / pipeline
سال پیدایش19511980s (Taguchi's crossed-array approach); fractional factorial roots 1935–1945
پدیدآورGeorge E. P. Box & K. B. WilsonGenichi Taguchi (robust parameter design); fractional factorial foundations by Ronald Fisher and Frank Yates
نوعSecond-order polynomial response surface modelExperimental design / robust parameter design
منبع بنیادینBox, 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 ↗Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443
نام‌های دیگرRSM, Central Composite Design, Box-Behnken Design, CCDrobust FFD, robust fractional factorial experiment, crossed-array fractional factorial, Taguchi-style fractional factorial
مرتبط72
خلاصهResponse 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.Robust fractional factorial design combines the run-count efficiency of fractional factorial arrays with Taguchi's robust parameter design philosophy. By simultaneously manipulating control factors (inner array) and noise factors (outer array) — each structured as a fractional factorial — the method identifies factor settings that minimize product or process variation due to uncontrollable conditions, without requiring a full factorial experiment.
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ScholarGateمقایسهٔ روش‌ها: Response Surface Methodology · Robust Fractional Factorial Design. بازیابی‌شده در 2026-06-19 از https://scholargate.app/fa/compare