ScholarGate
المساعد

قارن الطرق

راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.

تصميم عاملي كامل متعدد الاستجابات×تصميم التجارب×
المجالالتصميم التجريبيالتصميم التجريبي
العائلةProcess / pipelineProcess / pipeline
سنة النشأة1950s–1980s1935
صاحب الطريقةDouglas C. Montgomery (factorial framework); Derringer & Suich (multi-response desirability optimization)Ronald A. Fisher
النوعExperimental design with multi-objective optimizationExperimental planning framework
المصدر التأسيسيMontgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
الأسماء البديلةMRFFD, multi-response FFD, multiple-response full factorial, multi-objective full factorial designDOE, experimental design, factorial experimentation, planned experimentation
ذات صلة33
الملخصMulti-response full factorial design extends the classic full factorial experiment by measuring and jointly optimizing two or more response variables at the same time. Every combination of all factor levels is tested, providing complete main-effect and interaction information for each response. A desirability function or Pareto-front approach then reconciles competing responses into a single optimal factor setting, making this the method of choice when engineering or process goals involve trade-offs among several quality characteristics simultaneously.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.
ScholarGateمجموعة البيانات
  1. v1
  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED

انتقل إلى البحث تنزيل الشرائح

ScholarGateقارن الطرق: Multi-response full factorial design · Design of experiments. استُرجع بتاريخ 2026-06-19 من https://scholargate.app/ar/compare