An Intelligent Chatbot Assistant for Comprehensive Troubleshooting Guidelines and Knowledge Repository in Printed Circuit Board Production

Abstract

This study explores an innovative approach to improving printed circuit board (PCB) manufacturing through an intelligent chatbot assistant. Our chatbot leverages the retrieval-augmented generation (RAG) technique within the Langchain framework, integrating the capabilities of large language models (LLMs) ChatGPT and Llama 2. This combined approach empowers the chatbot to deliver not only accurate but also nuanced and detailed responses to user queries, enhancing troubleshooting and knowledge dissemination. We employ a comprehensive evaluation strategy that incorporates both quantitative and qualitative assessments. While quantitative evaluations reveal no significant differences between the models, qualitative feedback overwhelmingly favors the ChatGPT-based model. The positive user feedback, coupled with the ChatGPT chatbot's superior performance in subjective evaluations, highlights its potential to transform PCB manufacturing by minimizing delays and elevating performance standards.