Interactive and Intelligent Root Cause Analysis in Manufacturing with Causal Bayesian Networks and Knowledge Graphs

The article discusses the development of an interactive and intelligent tool for Root Cause Analysis (RCA) in the manufacturing of electric vehicles. Traditionally, RCA is conducted manually, which can be laborious and time-consuming. The new tool uses machine learning and expert knowledge to make the process more efficient. It makes use of a large-scale Knowledge Graph and Causal Bayesian Networks to reason over the manufacturing process. The tool allows process experts to interact and provide feedback, thereby reducing the learning time and improving the accuracy of the RCA.

Publication date: 2 Feb 2024
Project Page: Not provided
Paper: https://arxiv.org/pdf/2402.00043