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| Analisi dei Modi di Guasto e dei loro Effetti assistita dall'Ottimizzazione× | Controllo Statistico di Processo× | |
|---|---|---|
| Campo | Disegno sperimentale | Disegno sperimentale |
| Famiglia | Process / pipeline | Process / pipeline |
| Anno di origine≠ | 1949 (FMEA origin); optimization-assisted variants: 1990s–2000s | 1924–1931 |
| Ideatore≠ | Extension of FMEA (U.S. Military, MIL-STD-1629, 1949); optimization integration developed in reliability and quality engineering literature from the 1990s onward | Walter A. Shewhart |
| Tipo≠ | Reliability and risk analysis technique with embedded optimization | Process monitoring and quality control method |
| Fonte seminale≠ | 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 |
| Alias | Optimization-assisted FMEA, FMEA with optimization, OA-FMEA, Optimized risk priority ranking | SPC, statistical quality control, process control charting, Shewhart control |
| Correlati | 6 | 6 |
| 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. | 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. |
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