Comparar métodos

	Control Estadístico de Procesos Basado en Riesgos	Six Sigma DMAIC
Campo	Diseño experimental	Gestión de la calidad
Familia	Process / pipeline	Process / pipeline
Año de origen	1920s (SPC foundations); risk-based integration formalized in 2000s–2010s	2014
Autor original	Integrated from SPC (Shewhart, 1920s; Deming, 1950s) and risk analysis frameworks (FDA ICH Q10, ISO 31000)	Motorola; Pyzdek & Keller
Tipo	Hybrid quality-risk engineering method	Structured process improvement methodology
Fuente seminal	Montgomery, D. C. (2020). Introduction to Statistical Quality Control (8th ed.). Wiley. ISBN: 978-1119399308	Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill. ISBN: 978-0-07-184053-9
Alias	Risk-based SPC, RBSPC, risk-prioritized SPC, risk-informed process monitoring	DMAIC Framework, Six Sigma Process Improvement Cycle, Define-Measure-Analyze-Improve-Control, Altı Sigma DMAIC
Relacionados	6	3
Resumen	Risk-based statistical process control (Risk-based SPC) is an engineering quality method that integrates formal risk analysis — typically FMEA or a risk matrix — with statistical process monitoring to focus control chart resources on the process parameters that pose the greatest risk to product quality or system safety. Rather than applying control charts uniformly across all variables, risk-based SPC directs tighter monitoring toward high-risk, high-impact process characteristics identified through structured hazard prioritization.	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.