Simulation-assisted root cause analysis
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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Latino, R. J., & Latino, K. C. (2006). Root Cause Analysis: Improving Performance for Bottom-Line Results (3rd ed.). CRC Press. · ISBN 978-0849338267
- Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. · ISBN 978-0136062127
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.