smart_process_quality_control
Autonomous AI-Driven Quality Control System
A real-time process monitoring system that bridges the gap between Operational Technology (OT) and Information Technology (IT). This project automates industrial quality assurance by monitoring telemetry via MQTT and using AI Agents to trigger intelligent decisions.
Features
- Real-Time Monitoring: Streams live sensor telemetry via MQTT (Mosquitto), triggering events based on predefined process thresholds.
- AI-Driven Decision Making: Features a Google Gemini AI Agent that analyzes technical datasheets and laboratory reports to automatically verify product compliance.
- Automated Workflow: Built with n8n, the system autonomously coordinates departmental notifications via Gmail API, moving the production to the next stage without manual intervention.
Tech Stack
- Orchestration: n8n
- IoT Protocol: MQTT / Mosquitto
- AI Framework: Google Gemini AI
- Environment: Docker (Containerized deployment)
Fail-safe AI Logic & Reliability
To ensure industrial-grade reliability, the system incorporates a Fail-safe AI Logic.
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Zero-Risk Classification: The AI Agent is programmed to prioritize safety; if any telemetry data or laboratory report is ambiguous or suggests a potential deviation, the system defaults to a GENERAL (Manual Review) status rather than risking a false “Approved” signal.
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Human-in-the-Loop: This logic ensures that all critical quality decisions are either explicitly confirmed by AI or flagged for human intervention, bridging the gap between autonomous automation and operational security.
### Screenshots
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Workflow Machine Simulator and Logic
### 🚀 How to Run
1. **Import the Workflow:** Download and import the `.json` files into n8n.
2. **Setup MQTT Broker:** Run a local Mosquitto broker (using Docker).
3. **Configure Credentials:** Set up your Google Gemini AI API key.