Comparer des méthodes

	Analyse de la capabilité robuste des processus	Analyse de la Capabilité des Processus (Cp, Cpk)
Domaine	Plans d'expériences	Statistique
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s–2000s	1986
Auteur d'origine	Extended from classical PCA (Kane, 1986; Juran, 1974) via robust statistics (Huber, 1981); formalized for capability indices by Tong & Chen (1998) and Pearn & Kotz (1994)	Victor Kane
Type	Quantitative quality engineering method	Quantitative process evaluation index
Source fondatrice	Maravelakis, P. E., Bersimis, S., Panaretos, J., & Psarakis, S. (2004). Identifying the out of control variable in a multivariate control chart. Communications in Statistics - Theory and Methods, 33(10), 2499–2510.	Kane, V. E. (1986). Process capability indices. Journal of Quality Technology, 18(1), 41–52.
Alias	Robust PCA, Robust Capability Indices, Outlier-Resistant Capability Analysis, Robust Cpk Analysis	Process Capability Indices, Capability Study, Süreç Yeterlilik Analizi, Process Performance Analysis
Apparentées	6	2
Résumé	Robust process capability analysis extends classical capability indices (Cp, Cpk, Ppk) by replacing the sample mean and standard deviation with robust location and scale estimators — such as the median, trimmed mean, MAD, or IQR-based spread — so that outliers and non-normal process distributions do not inflate or distort the capability estimate. The result is a more reliable assessment of whether a manufacturing or service process can consistently meet specification limits.	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.