Fault Tree

Fault tree analysis (FTA) is a widely used technique for assessing system reliability and risk by graphically representing potential failure causes and their relationships. Current research focuses on extending FTA's capabilities, particularly by incorporating fuzzy logic to handle uncertainty in data and by developing automated methods using machine learning algorithms (like decision trees and evolutionary algorithms) to construct fault trees from large datasets, such as sensor data from industrial systems. These advancements aim to improve the efficiency and accuracy of risk assessment in various domains, including predictive maintenance, medical device safety, and industrial process control, moving beyond traditional manual construction methods.