Utilize NLP and LLM to Automate HVM (High Volume Manufacturing) IMT Report

In collaboration with Intel, this project introduces an AI-powered solution to automate IMT reporting in semiconductor High-Volume Manufacturing (HVM). Traditional reporting is often manual, repetitive, and prone to errors, slowing down critical decision-making. Our system leverages Natural Language Processing (NLP) and Large Language Models (LLMs) to streamline this process, turning complex manufacturing data into accurate, traceable reports.

At the core is a Retrieval-Augmented Generation (RAG) pipeline supported by vector databases, enabling contextual and real-time data retrieval. Engineers can interact with the system through a conversational AI interface and visualization dashboard, allowing them to query, validate, and explore yield and defect data instantly. The backend is deployed on the cloud for scalability, ensuring secure and reliable performance.



By reducing manual effort and error rates, the project enhances traceability, consistency, and speed across reporting workflows. More than an automation tool, it lays the foundation for AI-driven manufacturing intelligence, helping engineers shift focus from repetitive tasks to deeper analysis and innovation in semiconductor production.