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Wykres kontrolny odporny (Robust Control Chart)×Analiza rodzajów i skutków możliwych błędów (FMEA)×
DziedzinaPlanowanie eksperymentówPlanowanie eksperymentów
RodzinaProcess / pipelineProcess / pipeline
Rok powstania1989–1997 (foundational period)1949 (military); widespread industrial adoption 1970s–1980s
TwórcaDavid M. Rocke; L. G. Tatum (key contributors)U.S. Military / NASA (formalized by MIL-P-1629, 1949)
TypStatistical process monitoring techniqueProactive risk analysis technique
Źródło pierwotneTatum, L. G. (1997). Robust estimation of the process standard deviation for control charts. Technometrics, 39(2), 127–141. DOI ↗Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989
Inne nazwyrobust Shewhart chart, outlier-resistant control chart, robust SPC chart, distribution-free control chartFMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis
Pokrewne66
PodsumowanieA robust control chart replaces the classical mean and standard deviation estimators in a Shewhart-style chart with resistant alternatives — such as the median and median absolute deviation (MAD) — so that a small fraction of outliers or non-normal process data cannot distort the control limits. The approach preserves the real-time monitoring logic of standard control charts while protecting against inflated or deflated limits caused by contaminated Phase I reference data.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.
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ScholarGatePorównaj metody: Robust Control Chart · Failure Mode and Effects Analysis. Pobrano 2026-06-17 z https://scholargate.app/pl/compare