Comparar métodos

	Control Estadístico de Procesos Multirrespuesta	Análisis Modal de Fallos y Efectos (AMFE)
Campo	Diseño experimental	Diseño experimental
Familia	Process / pipeline	Process / pipeline
Año de origen	1947 (Hotelling's T²); mature multivariate SPC framework 1980s–2000s	1949 (military); widespread industrial adoption 1970s–1980s
Autor original	Harold Hotelling (T² statistic); extended by Alt, Lowry, Montgomery, Mason & Young	U.S. Military / NASA (formalized by MIL-P-1629, 1949)
Tipo	Multivariate quality-monitoring procedure	Proactive risk analysis technique
Fuente seminal	Lowry, C. A., & Montgomery, D. C. (1995). A review of multivariate control charts. IIE Transactions, 27(6), 800–810.	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989
Alias	Multivariate SPC, MSPC, Multi-response SPC, Multivariate statistical process control	FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis
Relacionados	6	6
Resumen	Multi-response statistical process control (multivariate SPC) extends classical univariate control charting to processes where two or more correlated quality characteristics must be monitored simultaneously. By treating all responses as a joint distribution, it detects shifts that would be invisible when each response is charted independently, reducing false alarms and improving the sensitivity of process monitoring in manufacturing and service contexts.	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.