Compara mètodes

	Anàlisi de Causes Fonamentals Assistida per Simulació	Anàlisi de Causes Fonamentals
Camp	Disseny experimental	Gestió de la qualitat
Família	Process / pipeline	Process / pipeline
Any d'origen	1990s–2000s (widespread adoption in engineering reliability contexts)	1986
Autor original	Evolved from root cause analysis practice (Kepner & Tregoe, 1960s) integrated with simulation methods (1990s–2000s in reliability engineering)	Kaoru Ishikawa
Tipus	Analytical / diagnostic engineering method	Structured causal-inference tool
Font seminal	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
Àlies	Sim-RCA, simulation-based RCA, virtual root cause analysis, computational root cause analysis	Cause-and-Effect Analysis, Fishbone Analysis, Ishikawa Diagram, Kök Neden Analizi
Relacionats	6	3
Resum	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.