ScholarGate
Asistent

Porovnat metody

Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.

Analýza způsobilosti procesu s asistencí simulace×Simulace Monte Carlo×
OborPlánování experimentůRozhodování
RodinaProcess / pipelineMCDM
Rok vzniku1980s–1990s (mature practice by mid-1990s)1949
TvůrceDeveloped through integration of Monte Carlo simulation with classical capability indices (Juran, Kane, Kotz and colleagues)Metropolis, N., Ulam, S.
TypQuantitative engineering quality methodRobustness wrapper — Monte Carlo uncertainty propagation
Původní zdrojKotz, S., & Lovelace, C. R. (1998). Process Capability Indices in Theory and Practice. Arnold. ISBN: 978-0340691281Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Další názvyMonte Carlo process capability, simulation-based Cpk analysis, stochastic capability analysis, virtual process capability study
Příbuzné60
ShrnutíSimulation-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.
ScholarGateDatová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 1 Zdroje
  3. PUBLISHED

Přejít na hledání Stáhnout prezentaci

ScholarGatePorovnat metody: Simulation-assisted process capability analysis · MONTE-CARLO-SIMULATION. Získáno 2026-06-15 z https://scholargate.app/cs/compare