Salīdzināt metodes

	Six Sigma DMAIC	Metodoloģija virsmas atbildes (RSM)
Nozare	Kvalitātes vadība	Eksperimentu plānošana
Saime	Process / pipeline	Hypothesis test
Izcelsmes gads	2014	1951
Autors	Motorola; Pyzdek & Keller	George E. P. Box & K. B. Wilson
Tips	Structured process improvement methodology	Second-order polynomial response surface model
Pirmavots	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9	Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45.
Citi nosaukumi	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC	RSM, Central Composite Design, Box-Behnken Design, CCD
Saistītās	3	7
Kopsavilkums	Six Sigma DMAIC is a data-driven, five-phase process improvement methodology — Define, Measure, Analyze, Improve, and Control — used to reduce defects and process variation to fewer than 3.4 defects per million opportunities. Originating at Motorola in the 1980s and systematized by practitioners including Pyzdek and Keller, it is widely adopted in manufacturing, healthcare, finance, and service industries seeking sustained quality gains.	Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics.