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	Wielowymiarowa statystyczna kontrola procesu	Analiza rodzajów i skutków możliwych błędów (FMEA)
Dziedzina	Planowanie eksperymentów	Planowanie eksperymentów
Rodzina	Process / pipeline	Process / pipeline
Rok powstania	1947 (Hotelling's T²); mature multivariate SPC framework 1980s–2000s	1949 (military); widespread industrial adoption 1970s–1980s
Twórca	Harold Hotelling (T² statistic); extended by Alt, Lowry, Montgomery, Mason & Young	U.S. Military / NASA (formalized by MIL-P-1629, 1949)
Typ	Multivariate quality-monitoring procedure	Proactive risk analysis technique
Źródło pierwotne	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
Inne nazwy	Multivariate SPC, MSPC, Multi-response SPC, Multivariate statistical process control	FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis
Pokrewne	6	6
Podsumowanie	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.