Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza Modurilor de Defecțiune și a Efectelor (FMEA)× | Diagramă de Control× | |
|---|---|---|
| Domeniu | Design experimental | Design experimental |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1949 (military); widespread industrial adoption 1970s–1980s | 1924 (first use); 1931 (seminal book) |
| Autorul original≠ | U.S. Military / NASA (formalized by MIL-P-1629, 1949) | Walter A. Shewhart (Bell Labs) |
| Tip≠ | Proactive risk analysis technique | Statistical monitoring and control technique |
| Sursa seminală≠ | 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. link ↗ |
| Denumiri alternative | FMEA, Failure Modes and Effects Analysis, FMECA, Failure Mode Effects and Criticality Analysis | Shewhart chart, process-behavior chart, SPC chart, quality control chart |
| Înrudite | 6 | 6 |
| Rezumat≠ | 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. | A control chart is a time-series graph with statistically derived upper and lower control limits that separates the natural, random variation of a process (common cause) from unusual, assignable variation (special cause). Invented by Walter Shewhart at Bell Labs in 1924, control charts remain the foundational tool of Statistical Process Control and are used across manufacturing, healthcare, software, and service industries to monitor whether a process remains stable and predictable over time. |
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