Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Plně faktorový experimentální design v průmyslových aplikacích× | Statistické řízení procesů× | |
|---|---|---|
| Obor | Plánování experimentů | Plánování experimentů |
| Rodina | Process / pipeline | Process / pipeline |
| Rok vzniku≠ | 1926 (foundational); industrially systematized by Box, Hunter & Hunter ~1950s–1978 | 1924–1931 |
| Tvůrce≠ | Ronald A. Fisher | Walter A. Shewhart |
| Typ≠ | Experimental design / factorial experiment | Process monitoring and quality control method |
| Původní zdroj≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 |
| Další názvy | industrial FFD, full factorial experiment, complete factorial design, 2^k factorial design | SPC, statistical quality control, process control charting, Shewhart control |
| Příbuzné≠ | 3 | 6 |
| Shrnutí≠ | Full factorial design (FFD) applied in industrial settings is a structured experimental methodology in which every combination of factor levels is tested, enabling engineers to quantify main effects and all interaction effects among process or product variables. Widely used in manufacturing, chemical processing, materials science, and quality engineering, it provides a complete picture of how input factors jointly influence a response variable such as yield, strength, or defect rate. | 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. |
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