Comparer des méthodes

	Diagramme de contrôle bayésien	Analyse de la Capabilité des Processus (Cp, Cpk)
Domaine	Plans d'expériences	Statistique
Famille	Process / pipeline	Process / pipeline
Année d'origine	Formally developed in the 1990s–2000s; roots in Shewhart (1924)	1986
Auteur d'origine	Ulrich Menzefricke and others building on Shewhart (1924) and Bayesian inference (Bayes, 1763)	Victor Kane
Type	Statistical process monitoring / quality control	Quantitative process evaluation index
Source fondatrice	Menzefricke, U. (2002). On the evaluation of control chart limits based on predictive distributions. Communications in Statistics — Theory and Methods, 31(8), 1423–1440.	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Alias	Bayesian SPC chart, Bayesian monitoring chart, posterior control chart, Bayesian Shewhart chart	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Apparentées	6	2
Résumé	A Bayesian control chart integrates prior knowledge about a process — such as historical mean and variance — with incoming measurement data to produce dynamically updated control limits. Unlike classical Shewhart charts that fix limits from a Phase-I baseline, Bayesian charts update the posterior distribution of process parameters after each sample, yielding limits that adapt to accumulated evidence and are better calibrated under small sample sizes or non-stationary processes.	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.