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Анализ на възможностите на процеса, подпомогнат от симулация×Монте Карло симулация×
ОбластПланиране на експериментаВземане на решения
СемействоProcess / pipelineMCDM
Година на възникване1980s–1990s (mature practice by mid-1990s)1949
СъздателDeveloped through integration of Monte Carlo simulation with classical capability indices (Juran, Kane, Kotz and colleagues)Metropolis, N., Ulam, S.
ТипQuantitative engineering quality methodRobustness wrapper — Monte Carlo uncertainty propagation
Основополагащ източникKotz, 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 ↗
Други названияMonte Carlo process capability, simulation-based Cpk analysis, stochastic capability analysis, virtual process capability study
Свързани60
РезюмеSimulation-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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  2. 2 Източници
  3. PUBLISHED
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  2. 1 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Simulation-assisted process capability analysis · MONTE-CARLO-SIMULATION. Извлечено на 2026-06-15 от https://scholargate.app/bg/compare