方法对比
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| 过程能力分析的敏感性分析× | 蒙特卡洛模拟× | |
|---|---|---|
| 领域≠ | 实验设计 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1986–2000s (Cp/Cpk indices from Kane 1986; integration formalized in Six Sigma era) | 1949 |
| 提出者≠ | Synthesized from work by V. E. Kane (process capability indices) and A. Saltelli (sensitivity analysis); integrated in Six Sigma and quality engineering practice | Metropolis, N., Ulam, S. |
| 类型≠ | Quantitative engineering analysis | Robustness wrapper — Monte Carlo uncertainty propagation |
| 开创性文献≠ | Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| 别名≠ | Sensitivity-Capability Analysis, PCA with Sensitivity Analysis, Process Capability Sensitivity Study, Cp/Cpk Sensitivity Analysis | — |
| 相关≠ | 5 | 0 |
| 摘要≠ | 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. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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