AI Agent for Semiconductor Manufacturing
Directed the research and development of an AI agent for a global semiconductor manufacturer. The agent leverages RAG architecture to combine real-time Manufacturing Execution System (MES) data with historical quality parameters, enabling engineers to perform natural-language root cause analysis for packaging defects.
Tech Stack
The Problem
Root cause analysis for backend packaging issues was a manual, time-intensive process requiring engineers to cross-reference multiple data sources and MES logs, often taking hours to identify the source of quality deviations.
The Solution
Built a LangChain/RAG-based agent that ingests and indexes real-time MES processing data alongside quality parameters. Trained models to correlate process variables with defect patterns, enabling conversational root cause analysis through natural language queries.
The Impact
Significantly reduced root cause analysis time for backend packaging issues, enabling faster corrective action and improving overall yield in semiconductor manufacturing.