Fault Tree Construction: A Survey of Knowledge-based, Model-Based and Data-Driven Approaches

Fault tree (FT) analysis is a widely used technique in system reliability engineering, providing a structured method for identifying the root causes of system failures.By visually representing failure pathways, FTs help engineers assess potential risks and implement preventive maintenance strategies.However, the construction of FTs remains a significant bottleneck, especially for large and complex systems due to the intricacies involved in manually modeling failure modes and capturing system behavior which increase the risk of incomplete failure analysis of the system.This paper proposes a survey of automatic construction methods of FTs.We classify related works into three wellknown categories: knowledge-based, model-based, and data-driven.Our survey highlights the formalisms used to model the system under analysis, the algorithms used to build the ft, the scope of their application, and their limitations.