Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Simulācijas atbalstīta procesa spēju analīze× | Monte Carlo simulācija× | |
|---|---|---|
| Nozare≠ | Eksperimentu plānošana | Lēmumu pieņemšana |
| Saime≠ | Process / pipeline | MCDM |
| Izcelsmes gads≠ | 1980s–1990s (mature practice by mid-1990s) | 1949 |
| Autors≠ | Developed through integration of Monte Carlo simulation with classical capability indices (Juran, Kane, Kotz and colleagues) | Metropolis, N., Ulam, S. |
| Tips≠ | Quantitative engineering quality method | Robustness wrapper — Monte Carlo uncertainty propagation |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi≠ | Monte Carlo process capability, simulation-based Cpk analysis, stochastic capability analysis, virtual process capability study | — |
| Saistītās≠ | 6 | 0 |
| Kopsavilkums≠ | 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. |
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