Compară metode

	Analiză de Sensibilitate-Metodologie Integrată a Suprafeței de Răspuns	Proiectarea Experimentelor
Domeniu	Design experimental	Design experimental
Familie	Process / pipeline	Process / pipeline
Anul apariției	1990s–2000s (integration practice)	1935
Autorul original	Box & Wilson (RSM, 1951); Saltelli et al. (global SA framework, 1990s–2000s)	Ronald A. Fisher
Tip	Hybrid experimental-analytical method	Experimental planning framework
Sursa seminală	Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2016). Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley. ISBN: 978-1118916018	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Denumiri alternative	SA-RSM, RSM with sensitivity analysis, sensitivity-augmented RSM, response surface methodology with factor screening	DOE, experimental design, factorial experimentation, planned experimentation
Înrudite	5	3
Rezumat	Sensitivity analysis-integrated RSM couples a structured experimental design with a formal sensitivity analysis of the fitted response surface model. After estimating a polynomial surrogate from designed experiments, global or local sensitivity indices are computed to quantify each input factor's relative contribution to output variability. This allows practitioners to identify which factors truly drive the response before committing to full optimization, reducing cost and improving the reliability of the final optimum.	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.