Compara mètodes

	Control Estadístic de Processos	Six Sigma DMAIC
Camp	Disseny experimental	Gestió de la qualitat
Família	Process / pipeline	Process / pipeline
Any d'origen	1924–1931	2014
Autor original	Walter A. Shewhart	Motorola; Pyzdek & Keller
Tipus	Process monitoring and quality control method	Structured process improvement methodology
Font seminal	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
Àlies	SPC, statistical quality control, process control charting, Shewhart control	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Relacionats	6	3
Resum	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.