방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 시뮬레이션 지원 공정 능력 분석× | 몬테카를로 시뮬레이션× | |
|---|---|---|
| 분야≠ | 실험설계 | 의사결정 |
| 계열≠ | Process / pipeline | MCDM |
| 기원 연도≠ | 1980s–1990s (mature practice by mid-1990s) | 1949 |
| 창시자≠ | Developed through integration of Monte Carlo simulation with classical capability indices (Juran, Kane, Kotz and colleagues) | Metropolis, N., Ulam, S. |
| 유형≠ | Quantitative engineering quality method | Robustness wrapper — Monte Carlo uncertainty propagation |
| 원전≠ | Kotz, S., & Lovelace, C. R. (1998). Process Capability Indices in Theory and Practice. Arnold. ISBN: 978-0340691281 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| 별칭≠ | Monte Carlo process capability, simulation-based Cpk analysis, stochastic capability analysis, virtual process capability study | — |
| 관련≠ | 6 | 0 |
| 요약≠ | Simulation-assisted process capability analysis combines Monte Carlo simulation with classical capability indices (Cp, Cpk, Cpm) to evaluate whether a process can consistently meet specification limits when direct measurement is costly, dangerous, or impractical. By propagating input distributions through a process model, the analyst obtains a simulated output distribution and derives capability metrics without waiting for physical production runs. The approach is especially valuable during product design, process scale-up, and tolerance stack-up studies. | 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. |
| ScholarGate데이터셋 ↗ |
|
|