Methoden vergleichen

	Multi-Response Failure Mode and Effects Analysis (MR-FMEA)	Statistische Prozesslenkung (SPC)
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1990s–2000s	1924–1931
Urheber	Extended from classical FMEA (MIL-P-1629, 1949; Ford Motor Company, 1970s); multi-response integration developed in quality engineering literature from the 1990s onward	Walter A. Shewhart
Typ	Risk analysis and quality engineering method	Process monitoring and quality control method
Wegweisende Quelle	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762
Aliasnamen	MR-FMEA, multi-response FMEA, multi-criteria FMEA, multi-objective FMEA	SPC, statistical quality control, process control charting, Shewhart control
Verwandt	6	6
Zusammenfassung	Multi-response FMEA extends classical Failure Mode and Effects Analysis to systems or processes where each failure mode produces effects across multiple quality characteristics or response variables simultaneously. Rather than assigning a single Risk Priority Number (RPN), it evaluates severity, occurrence, and detectability for each response dimension, then integrates these ratings — often via multi-criteria scoring or weighted aggregation — to obtain a holistic risk ranking that captures the full consequence profile of each failure mode.	Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers.