Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Control statistic asistat de simulare× | Controlul Statistic al Proceselor× | |
|---|---|---|
| Domeniu | Design experimental | Design experimental |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1980s–present | 1924–1931 |
| Autorul original≠ | Walter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onward | Walter A. Shewhart |
| Tip≠ | Hybrid quantitative method | Process monitoring and quality control method |
| Sursa seminală≠ | Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| Denumiri alternative | Simulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPC | SPC, statistical quality control, process control charting, Shewhart control |
| Înrudite | 6 | 6 |
| Rezumat≠ | 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. | Statistical Process Control (SPC) is a data-driven quality method that uses statistical techniques — primarily control charts — to monitor a manufacturing or service process over time. By distinguishing natural process variation (common cause) from unusual, actionable variation (special cause), SPC enables practitioners to maintain processes in a stable, predictable state and to detect problems early, before defective output reaches customers. |
| ScholarGateSet de date ↗ |
|
|