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	Robust Statistical Process Control	Vadības diagramma
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1989–1990s (formalized in peer-reviewed literature)	1924 (first use); 1931 (seminal book)
Autors	Rocke, D. M.; Tatum, L. G. (key contributors)	Walter A. Shewhart (Bell Labs)
Tips	Robust statistical monitoring framework	Statistical monitoring and control technique
Pirmavots	Tatum, L. G. (1997). Robust estimation of the process standard deviation for control charts. Technometrics, 39(2), 127–141.	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand.
Citi nosaukumi	Robust SPC, Resistant SPC, Outlier-robust process monitoring, Robust process surveillance	Shewhart chart, process-behavior chart, SPC chart, quality control chart
Saistītās	5	6
Kopsavilkums	Robust Statistical Process Control (Robust SPC) is an engineering quality-monitoring framework that replaces the classical mean and standard deviation estimators used in Shewhart-type control charts with outlier-resistant alternatives — such as the median, MAD, or trimmed statistics — so that isolated contaminating observations or non-normal process distributions do not inflate control limits and mask genuine process shifts.	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.