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	Analisi dei Modi di Guasto e dei loro Effetti assistita dall'Ottimizzazione	Design of Experiments
Campo	Disegno sperimentale	Disegno sperimentale
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1949 (FMEA origin); optimization-assisted variants: 1990s–2000s	1935
Ideatore	Extension of FMEA (U.S. Military, MIL-STD-1629, 1949); optimization integration developed in reliability and quality engineering literature from the 1990s onward	Ronald A. Fisher
Tipo	Reliability and risk analysis technique with embedded optimization	Experimental planning framework
Fonte seminale	Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution (2nd ed.). ASQ Quality Press. ISBN: 978-0873895989	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Alias	Optimization-assisted FMEA, FMEA with optimization, OA-FMEA, Optimized risk priority ranking	DOE, experimental design, factorial experimentation, planned experimentation
Correlati	6	3
Sintesi	Optimization-assisted FMEA extends classical Failure Mode and Effects Analysis by embedding mathematical optimization algorithms — such as linear programming, multi-objective optimization, or metaheuristics — into the risk prioritization step. Rather than relying solely on the Risk Priority Number (RPN = Severity × Occurrence × Detectability), the approach frames corrective-action selection and resource allocation as an optimization problem, enabling more defensible, constraint-aware ranking and mitigation of failure modes.	Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.