Simulation-assisted statistical process control
Simulation-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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. · ISBN 978-0470169926
- Jensen, W. A., Jones-Farmer, L. A., Champ, C. W., & Woodall, W. H. (2006). Effects of parameter estimation on control chart properties: A literature review. Journal of Quality Technology, 38(4), 349–364. · URL
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