Porównaj metody

	Statystyczne sterowanie procesem oparte na ryzyku	Six Sigma DMAIC
Dziedzina	Planowanie eksperymentów	Zarządzanie jakością
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1920s (SPC foundations); risk-based integration formalized in 2000s–2010s	2014
Twórca	Integrated from SPC (Shewhart, 1920s; Deming, 1950s) and risk analysis frameworks (FDA ICH Q10, ISO 31000)	Motorola; Pyzdek & Keller
Typ	Hybrid quality-risk engineering method	Structured process improvement methodology
Źródło pierwotne	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
Inne nazwy	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
Pokrewne	6	3
Podsumowanie	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.