Methoden vergleichen

	Vollfaktorielle Versuchsplanung in industriellen Anwendungen	Statistische Prozesslenkung (SPC)
Fachgebiet	Versuchsplanung	Versuchsplanung
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1926 (foundational); industrially systematized by Box, Hunter & Hunter ~1950s–1978	1924–1931
Urheber	Ronald A. Fisher	Walter A. Shewhart
Typ	Experimental design / factorial experiment	Process monitoring and quality control method
Wegweisende Quelle	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
Aliasnamen	industrial FFD, full factorial experiment, complete factorial design, 2^k factorial design	SPC, statistical quality control, process control charting, Shewhart control
Verwandt	3	6
Zusammenfassung	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.