Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ видов и последствий отказов на основе оценки рисков (RBFMEA)× | Статистическое управление процессами× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1949 (FMEA origins); risk-prioritised RPN framework circa 1977–1980s (AIAG automotive) | 1924–1931 |
| Автор метода≠ | U.S. Department of Defense / MIL-STD-1629A; formalised in IEC 60812 | Walter A. Shewhart |
| Тип≠ | Quantitative risk-prioritisation technique | Process monitoring and quality control method |
| Основополагающий источник≠ | International Electrotechnical Commission. (2018). IEC 60812:2018 — Failure modes and effects analysis (FMEA and FMECA). IEC. link ↗ | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| Другие названия | RBFMEA, Risk-based FMEA, Risk-prioritised FMEA, Quantitative FMEA | SPC, statistical quality control, process control charting, Shewhart control |
| Связанные | 6 | 6 |
| Сводка≠ | Risk-based failure mode and effects analysis (RBFMEA) is a structured engineering technique that identifies every way a system or process can fail, assesses the risk of each failure mode using a numerical Risk Priority Number (RPN = Occurrence × Severity × Detectability), and prioritises corrective actions accordingly. Rooted in MIL-STD-1629A and standardised in IEC 60812:2018, it is the dominant proactive reliability and safety tool in aerospace, automotive, pharmaceutical, and manufacturing industries. | 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. |
| ScholarGateНабор данных ↗ |
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