Comparer des méthodes

	Contrôle statistique des processus assisté par simulation	Analyse de la Capabilité des Processus (Cp, Cpk)
Domaine	Plans d'expériences	Statistique
Famille	Process / pipeline	Process / pipeline
Année d'origine	1980s–present	1986
Auteur d'origine	Walter A. Shewhart (SPC foundations); simulation integration developed through industrial engineering literature from the 1980s onward	Victor Kane
Type	Hybrid quantitative method	Quantitative process evaluation index
Source fondatrice	Montgomery, D. C. (2009). Introduction to Statistical Quality Control (6th ed.). Wiley. ISBN: 978-0470169926	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Alias	Simulation-based SPC, Monte Carlo SPC, SA-SPC, Simulation-integrated SPC	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Apparentées	6	2
Résumé	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.	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.