Comparer des méthodes

	Analyse des causes profondes assistée par simulation	Analyse des causes profondes
Domaine	Plans d'expériences	Gestion de la qualité
Famille	Process / pipeline	Process / pipeline
Année d'origine	1990s–2000s (widespread adoption in engineering reliability contexts)	1986
Auteur d'origine	Evolved from root cause analysis practice (Kepner & Tregoe, 1960s) integrated with simulation methods (1990s–2000s in reliability engineering)	Kaoru Ishikawa
Type	Analytical / diagnostic engineering method	Structured causal-inference tool
Source fondatrice	Latino, R. J., & Latino, K. C. (2006). Root Cause Analysis: Improving Performance for Bottom-Line Results (3rd ed.). CRC Press. ISBN: 978-0849338267	Ishikawa, K. (1986). Guide to Quality Control (2nd ed.). Asian Productivity Organization. ISBN: 978-92-833-1036-7
Alias	Sim-RCA, simulation-based RCA, virtual root cause analysis, computational root cause analysis	Cause-and-Effect Analysis, Fishbone Analysis, Ishikawa Diagram, Kök Neden Analizi
Apparentées	6	3
Résumé	Simulation-assisted root cause analysis (Sim-RCA) integrates computational simulation — such as discrete-event simulation, Monte Carlo methods, or finite-element analysis — into the structured root cause analysis process to diagnose the underlying causes of complex failures or defects. By running virtual experiments on a system model, investigators can test hypothetical causal pathways safely, rapidly, and at scale, without disrupting live operations or waiting for rare failure events to recur.	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.