Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Аналіз чутливості з аналізом придатності процесу× | Статистичне керування процесами× | |
|---|---|---|
| Галузь | Планування експерименту | Планування експерименту |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1986–2000s (Cp/Cpk indices from Kane 1986; integration formalized in Six Sigma era) | 1924–1931 |
| Автор методу≠ | Synthesized from work by V. E. Kane (process capability indices) and A. Saltelli (sensitivity analysis); integrated in Six Sigma and quality engineering practice | Walter A. Shewhart |
| Тип≠ | Quantitative engineering analysis | Process monitoring and quality control method |
| Основоположне джерело≠ | Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| Інші назви | Sensitivity-Capability Analysis, PCA with Sensitivity Analysis, Process Capability Sensitivity Study, Cp/Cpk Sensitivity Analysis | SPC, statistical quality control, process control charting, Shewhart control |
| Пов'язані≠ | 5 | 6 |
| Підсумок≠ | Sensitivity analysis with process capability analysis is a quantitative engineering method that combines the measurement of process performance — via capability indices such as Cp and Cpk — with systematic variation of input factors to identify which factors most strongly influence whether a process meets its specification limits. It is widely used in Six Sigma projects, manufacturing quality improvement, and Design of Experiments contexts to prioritize where corrective action will yield the greatest gain in process capability. | 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. |
| ScholarGateНабір даних ↗ |
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