Comparer des méthodes

	Analyse des causes profondes bayésienne	Analyse des causes profondes
Domaine	Plans d'expériences	Gestion de la qualité
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s–2000s	1986
Auteur d'origine	Rooted in Pearl's Bayesian network theory (Judea Pearl, 1988); applied to RCA in process/reliability engineering from the 1990s onward	Kaoru Ishikawa
Type	Probabilistic causal inference method	Structured causal-inference tool
Source fondatrice	Pourret, O., Naim, P., & Marcot, B. (Eds.). (2008). Bayesian Networks: A Practical Guide to Applications. Wiley. ISBN: 978-0470060308	Ishikawa, K. (1986). Guide to Quality Control (2nd ed.). Asian Productivity Organization. ISBN: 978-92-833-1036-7
Alias	Bayesian RCA, Bayesian causal analysis, probabilistic root cause analysis, BN-RCA	Cause-and-Effect Analysis, Fishbone Analysis, Ishikawa Diagram, Kök Neden Analizi
Apparentées	6	3
Résumé	Bayesian Root Cause Analysis (Bayesian RCA) integrates Bayesian network theory with structured root cause investigation to quantify the probability that each candidate cause is responsible for an observed failure or undesired event. Unlike deterministic RCA methods, it propagates uncertainty through the causal graph, updates beliefs as evidence accumulates, and ranks competing hypotheses by posterior probability — providing a principled, auditable basis for corrective action.	Root Cause Analysis (RCA) is a structured, systematic method for identifying the fundamental causes of defects, failures, or undesirable outcomes rather than treating surface-level symptoms. Popularised by Japanese quality engineer Kaoru Ishikawa in the 1960s–1980s, and formally codified in his 1986 Guide to Quality Control, RCA combines the Ishikawa (fishbone) diagram with the iterative 5 Whys questioning technique to trace causal chains back to their origin.