Сравнение методов

	Робастный Six Sigma DMAIC	Планирование эксперимента
Область	Планирование эксперимента	Планирование эксперимента
Семейство	Process / pipeline	Process / pipeline
Год появления	1990s–2000s (integration period)	1935
Автор метода	Motorola (Six Sigma, 1986); Taguchi robust design integrated into DMAIC by quality engineering practitioners in the 1990s–2000s	Ronald A. Fisher
Тип	Hybrid process improvement and robust engineering methodology	Experimental planning framework
Основополагающий источник	Antony, J. (2006). Six Sigma for service processes. Business Process Management Journal, 12(2), 234–248.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Другие названия	Robust DMAIC, Six Sigma with Robust Design, Taguchi-integrated DMAIC, R-DMAIC	DOE, experimental design, factorial experimentation, planned experimentation
Связанные	4	3
Сводка	Robust Six Sigma DMAIC embeds Taguchi's robust design philosophy within the classic Define-Measure-Analyze-Improve-Control framework. Rather than optimizing a process only for average performance, this hybrid approach simultaneously minimizes process variation caused by noise factors — environmental shifts, material lot differences, operator variability — so that the outcome remains near target even when uncontrollable conditions change. The result is a process that is both capable and insensitive to real-world disturbances.	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.