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Многофакторен експериментален дизайн×Планиране на експерименти×
ОбластПланиране на експериментаПланиране на експеримента
СемействоProcess / pipelineProcess / pipeline
Година на възникване1980 (desirability function formalization); DoE roots from Fisher, 1920s–1930s1935
СъздателDerringer & Suich (desirability function); Montgomery (systematic DoE integration)Ronald A. Fisher
ТипExperimental optimization methodologyExperimental planning framework
Основополагащ източникDerringer, G., & Suich, R. (1980). Simultaneous optimization of several response variables. Journal of Quality Technology, 12(4), 214–219. DOI ↗Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗
Други названияMulti-response DoE, Multiple-response optimization, Multi-objective DoE, MRDoEDOE, experimental design, factorial experimentation, planned experimentation
Свързани43
РезюмеMulti-response Design of Experiments (MRDoE) extends classical DoE to situations where several response variables must be optimized simultaneously. Rather than tuning factors for a single output, the experimenter fits separate regression or response-surface models for each response, then combines them — most often via Derringer and Suich's desirability function — into a single composite score that guides the search for factor settings satisfying all response targets at once.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.
ScholarGateНабор от данни
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Multi-response Design of Experiments · Design of experiments. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare