Methoden vergleichen

	Simulationsgestützte Prozessfähigkeitsanalyse	Prozessfähigkeitsanalyse (Cp, Cpk)
Fachgebiet	Versuchsplanung	Statistik
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1980s–1990s (mature practice by mid-1990s)	1986
Urheber	Developed through integration of Monte Carlo simulation with classical capability indices (Juran, Kane, Kotz and colleagues)	Victor Kane
Typ	Quantitative engineering quality method	Quantitative process evaluation index
Wegweisende Quelle	Kotz, S., & Lovelace, C. R. (1998). Process Capability Indices in Theory and Practice. Arnold. ISBN: 978-0340691281	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Aliasnamen	Monte Carlo process capability, simulation-based Cpk analysis, stochastic capability analysis, virtual process capability study	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Verwandt	6	2
Zusammenfassung	Simulation-assisted process capability analysis combines Monte Carlo simulation with classical capability indices (Cp, Cpk, Cpm) to evaluate whether a process can consistently meet specification limits when direct measurement is costly, dangerous, or impractical. By propagating input distributions through a process model, the analyst obtains a simulated output distribution and derives capability metrics without waiting for physical production runs. The approach is especially valuable during product design, process scale-up, and tolerance stack-up studies.	Process Capability Analysis quantifies how well a manufacturing or business process produces output within specified tolerance limits. Introduced formally by Victor Kane in 1986, it summarises process spread and centering into dimensionless indices — most notably Cp and Cpk — allowing engineers and quality managers to judge whether a stable process is inherently capable of meeting customer or design specifications consistently.