Confronta i metodi

	Controllo Statistico di Processo Bayesiano	Analisi di Capacità di Processo (Cp, Cpk)
Campo	Disegno sperimentale	Statistica
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	1950s (foundations); formalized 1990s–2000s	1986
Ideatore	Various (Girshick & Rubin 1952 early signal detection; Menzefricke 2002 Bayesian control chart framework)	Victor Kane
Tipo	Bayesian process monitoring technique	Quantitative process evaluation index
Fonte seminale	Menzefricke, U. (2002). On the evaluation of control chart factors for monitoring the process mean and variance. Journal of Quality Technology, 34(2), 167–178.	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Alias	Bayesian SPC, Bayesian process monitoring, B-SPC, Bayesian control charting	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Correlati	5	2
Sintesi	Bayesian Statistical Process Control (Bayesian SPC) extends classical SPC by replacing fixed, frequentist control limits with a probabilistic framework that incorporates prior knowledge about the process. Rather than waiting for a run of points to exceed a pre-set 3-sigma boundary, Bayesian SPC continuously updates the probability that the process has shifted given the incoming data, enabling earlier and more informed detection of out-of-control states while formally accounting for uncertainty in process parameters.	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.