Comparer des méthodes

	Maîtrise Statistique des Procédés	Six Sigma DMAIC
Domaine	Plans d'expériences	Gestion de la qualité
Famille	Process / pipeline	Process / pipeline
Année d'origine	1924–1931	2014
Auteur d'origine	Walter A. Shewhart	Motorola; Pyzdek & Keller
Type	Process monitoring and quality control method	Structured process improvement methodology
Source fondatrice	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Alias	SPC, statistical quality control, process control charting, Shewhart control	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Apparentées	6	3
Résumé	Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers.	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.