Σύγκριση μεθόδων

	Νόμος του Little (L = λW)	Six Sigma DMAIC
Πεδίο	Επιχειρησιακή Έρευνα	Διοίκηση Ποιότητας
Οικογένεια	Regression model	Process / pipeline
Έτος προέλευσης	1961	2014
Δημιουργός	John D. C. Little	Motorola; Pyzdek & Keller
Τύπος	Exact queueing identity	Structured process improvement methodology
Θεμελιώδης πηγή	Little, J. D. C. (1961). A proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387.	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Εναλλακτικές ονομασίες	L = λW Theorem, Little's Theorem, Little's Result, Little Yasası	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Συναφείς	3	3
Σύνοψη	Little's Law is a fundamental theorem in queueing theory that relates the long-run average number of items in a stable system (L) to the long-run average arrival rate (λ) and the long-run average time an item spends in the system (W), expressed as L = λW. Introduced and rigorously proved by John D. C. Little in 1961, the law holds for virtually any stable stochastic system, requiring no assumptions about arrival distributions, service distributions, or queue disciplines.	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.