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Simulatsioonipõhine statistiline protsessijuhtimine×Monte Carlo simulatsioon×
ValdkondKatsedisainOtsustamine
PerekondProcess / pipelineMCDM
Tekkeaasta1980s–present1949
LoojaWalter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onwardMetropolis, N., Ulam, S.
TüüpHybrid quantitative methodRobustness wrapper — Monte Carlo uncertainty propagation
AlgallikasMontgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
RööpnimetusedSimulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPC
Seotud60
KokkuvõteSimulation-assisted statistical process control (SA-SPC) combines computer simulation — typically Monte Carlo or discrete-event simulation — with classical SPC methods to design, test, and calibrate control charts and monitoring schemes before or alongside deployment on a real production process. Rather than relying solely on closed-form analytical assumptions, SA-SPC uses simulated data to evaluate chart performance under realistic, often non-normal process conditions.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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ScholarGateVõrdle meetodeid: Simulation-assisted statistical process control · MONTE-CARLO-SIMULATION. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare