Failure Mode and Effects Analysis (FMEA) is a systematic method used to identify and address potential failures in products or industrial processes. This project demonstrates how Large Language Models (LLMs) can significantly enhance the traditional FMEA process, automating it to ensure higher safety, quality, and reliability while reducing the dependency on extensive expert input and labor-intensive analyses.
- Demo: Access the runnable demo https://llm-fmea-assistant-v2-yawjvp4zbq-ew.a.run.app.
This repository contains demonstrations of LLM-assisted FMEA in distinct applications:
In this demonstration, we apply an LLM to analyze the brake-by-wire system, a critical component in modern vehicles. The model identifies potential failure modes and suggests risk mitigation strategies, facilitating a more resilient design.
Yuchen Xia is a PhD candidate specializing in LLM agents, digital twins, and industrial automation since 2021. You can find more about his work, publications and projects on his personal website.