Simulation-assisted control chart
Simulation-assisted control chart integrates Monte Carlo or discrete-event simulation with traditional Shewhart-type control charting to design, validate, and optimize chart parameters before deployment on a real process. Rather than relying solely on assumed distributional forms, the practitioner builds a simulation model of the process, generates virtual data under in-control and out-of-control scenarios, and uses these runs to calibrate control limits, estimate average run length (ARL), and stress-test chart sensitivity — all without interrupting production.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Woodall, W. H., & Montgomery, D. C. (1999). Research issues and ideas in statistical process control. Journal of Quality Technology, 31(4), 376–386. · DOI 10.1080/00224065.1999.11979944
- Montgomery, D. C. (2009). Statistical Quality Control: A Modern Introduction (6th ed.). Wiley. · ISBN 978-0470169926
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Related methods
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