Failure Analysis

Failure analysis focuses on identifying and understanding the causes of system failures across diverse domains, aiming to improve reliability and safety. Current research emphasizes leveraging machine learning, particularly deep learning architectures like convolutional neural networks and recurrent neural networks (LSTMs), along with large language models (LLMs) for automated failure detection, diagnosis, and even predictive maintenance. These advancements are significantly impacting various fields, from robotics and software engineering to industrial prognostics and network management, by enabling more efficient and accurate failure analysis and ultimately leading to improved system resilience.