Salīdzināt metodes

	Statistiskā procesa kontrole, balstīta uz risku	Vadības diagramma
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1920s (SPC foundations); risk-based integration formalized in 2000s–2010s	1924 (first use); 1931 (seminal book)
Autors	Integrated from SPC (Shewhart, 1920s; Deming, 1950s) and risk analysis frameworks (FDA ICH Q10, ISO 31000)	Walter A. Shewhart (Bell Labs)
Tips	Hybrid quality-risk engineering method	Statistical monitoring and control technique
Pirmavots	Montgomery, D. C. (2020). Introduction to Statistical Quality Control (8th ed.). Wiley. ISBN: 978-1119399308	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand.
Citi nosaukumi	Risk-based SPC, RBSPC, risk-prioritized SPC, risk-informed process monitoring	Shewhart chart, process-behavior chart, SPC chart, quality control chart
Saistītās	6	6
Kopsavilkums	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.	A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time.