Comparar métodos

	Control Estadístico de Procesos Robusto	Análisis Modal de Fallos y Efectos (AMFE)
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Process / pipeline
Año de origen	1989–1990s (formalized in peer-reviewed literature)	1949 (military); widespread industrial adoption 1970s–1980s
Autor original	Rocke, D. M.; Tatum, L. G. (key contributors)	U.S. Military / NASA (formalized by MIL-P-1629, 1949)
Tipo	Robust statistical monitoring framework	Proactive risk analysis technique
Fuente seminal	Tatum, L. G. (1997). Robust estimation of the process standard deviation for control charts. Technometrics, 39(2), 127–141.	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989
Alias	Robust SPC, Resistant SPC, Outlier-robust process monitoring, Robust process surveillance	FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis
Relacionados	5	6
Resumen	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.	Failure Mode and Effects Analysis (FMEA) is a structured, proactive risk management technique used to identify potential failure modes in a system, process, or product design, evaluate their consequences, and prioritize corrective actions before failures occur. Originally developed for the U.S. military in 1949 and later adopted by NASA, automotive, and manufacturing industries, FMEA is now a cornerstone quality-engineering tool embedded in standards such as AIAG-VDA and ISO 9001-aligned processes.