Bandingkan metode

	Kontrol Proses Statistik Berbasis Risiko	Six Sigma DMAIC
Bidang	Desain Eksperimen	Manajemen Mutu
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	1920s (SPC foundations); risk-based integration formalized in 2000s–2010s	2014
Pencetus	Integrated from SPC (Shewhart, 1920s; Deming, 1950s) and risk analysis frameworks (FDA ICH Q10, ISO 31000)	Motorola; Pyzdek & Keller
Tipe	Hybrid quality-risk engineering method	Structured process improvement methodology
Sumber perintis	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
Terkait	6	3
Ringkasan	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.