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	Contrôle Statistique des Processus Robuste	Diagramme de contrôle
Domaine	Plans d'expériences	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1989–1990s (formalized in peer-reviewed literature)	1924 (first use); 1931 (seminal book)
Auteur d'origine	Rocke, D. M.; Tatum, L. G. (key contributors)	Walter A. Shewhart (Bell Labs)
Type	Robust statistical monitoring framework	Statistical monitoring and control technique
Source fondatrice	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.
Alias	Robust SPC, Resistant SPC, Outlier-robust process monitoring, Robust process surveillance	Shewhart chart, process-behavior chart, SPC chart, quality control chart
Apparentées	5	6
Résumé	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.