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| Statistische Prozesslenkung (SPC)× | Design of Experiments× | |
|---|---|---|
| Fachgebiet | Versuchsplanung | Versuchsplanung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1924–1931 | 1935 |
| Urheber≠ | Walter A. Shewhart | Ronald A. Fisher |
| Typ≠ | Process monitoring and quality control method | Experimental planning framework |
| Wegweisende Quelle≠ | Shewhart, W. A. (1931). Economic Control of Quality of Manufactured Product. Van Nostrand. ISBN: 978-0873890762 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Aliasnamen | SPC, statistical quality control, process control charting, Shewhart control | DOE, experimental design, factorial experimentation, planned experimentation |
| Verwandt≠ | 6 | 3 |
| Zusammenfassung≠ | 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. | Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences. |
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