Võrdle meetodeid

	Response Surface Methodology (RSM) tööstuslikuks kasutamiseks	Katseplaneerimine
Valdkond	Katsedisain	Katsedisain
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	1951 (origin); widespread industrial adoption from 1980s onward	1935
Looja	George E. P. Box & K. B. Wilson; industrialized by Douglas Montgomery and colleagues	Ronald A. Fisher
Tüüp	Empirical optimization technique	Experimental planning framework
Algallikas	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.
Rööpnimetused	Industrial RSM, RSM for manufacturing, process optimization RSM, industrial response surface analysis	DOE, experimental design, factorial experimentation, planned experimentation
Seotud	5	3
Kokkuvõte	Industrial Applications Response Surface Methodology (RSM) applies the classical Box-Wilson response surface framework to manufacturing and process engineering problems. It builds an empirical polynomial model linking controllable process inputs — such as temperature, pressure, feed rate, or catalyst concentration — to one or more quality responses, then mathematically locates the input settings that optimize those responses. It is the de-facto standard statistical tool for process characterization and optimization in chemical, mechanical, food, materials, and pharmaceutical manufacturing.	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.