Autonomous Manufacturing Defect Triager with Multi-Agent AI (Updated)

How I Automated Quality Control Routing Using LangGraph, a Structured Message Bus, and Persistent Shared State TL;DR I designed a multi-agent system to automate defect diagnosis and routing in a simulated manufacturing environment. I built it using LangGraph to manage a structured message bus and persistent shared state. I implemented an Advanced Communication Protocol (ACP) simulation to visualize the reasoning process realistically. I found that coordinating multiple specialized agents vastly improves incident response times compared to a monolithic LLM. Introduction I have often observed that in modern manufacturing pipelines, the speed at which you can diagnose an anomaly detected by an IoT sensor dictates the overall efficiency of the plant. A single faulty spindle or a batch of off-spec raw material can bottleneck production for hours if not triaged immediately. In my opinion, traditional rule-based systems are too rigid to handle the nuanced, compounding errors that occur on an