Salīdzināt metodes

	Simulācijas atbalstīta Six Sigma DMAIC	Six Sigma DMAIC
Nozare	Eksperimentu plānošana	Kvalitātes vadība
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2000s–present (systematic integration of simulation with DMAIC)	2014
Autors	Integration practice emerged from industrial engineering and operations research communities; DMAIC framework originates with Motorola/GE Six Sigma (1980s–1990s)	Motorola; Pyzdek & Keller
Tips	Hybrid process-improvement methodology	Structured process improvement methodology
Pirmavots	Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). John Wiley & Sons. ISBN: 978-0470169926	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Citi nosaukumi	Sim-DMAIC, Simulation-integrated DMAIC, Six Sigma with simulation, DMAIC simulation modeling	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Saistītās	6	3
Kopsavilkums	Simulation-assisted Six Sigma DMAIC embeds discrete-event or Monte Carlo simulation models inside the classic DMAIC cycle (Define, Measure, Analyze, Improve, Control) to test process changes virtually before committing to physical implementation. By running thousands of simulated scenarios, teams quantify variation, identify bottlenecks, and verify improvement hypotheses at low cost and with minimal disruption to live operations.	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.