Automate Quality Defect Classification with n8n
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This n8n workflow automates the classification of manufacturing quality defects by leveraging AI and vector databases. It processes incoming defect data, classifies it, and logs the results for analysis.
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About This Workflow
Overview
This n8n workflow is designed to automate the process of classifying quality defects in a manufacturing environment. It utilizes a combination of n8n's webhook functionality to receive defect data, Langchain nodes for natural language processing and AI-powered classification, and Redis as a vector store for efficient data retrieval and analysis. The workflow addresses the need for rapid and accurate identification of defect types, enabling quicker response times and improved quality control measures.
Key Features
- Real-time defect data ingestion via webhook.
- AI-powered classification of quality defects using Langchain.
- Efficient storage and retrieval of defect embeddings using Redis.
- Automatic logging of classified defects to a Google Sheet.
How To Use
- Set up Webhook: Configure the 'Webhook' node to receive incoming defect data.
- Split and Embed: The 'Splitter' and 'Embeddings' nodes process the incoming data and generate embeddings.
- Store Embeddings: Use the 'Insert' node to store these embeddings in a Redis vector store.
- Query and Classify: The 'Query' and 'Tool' nodes interact with the vector store and an AI agent to classify the defect.
- Log Results: The 'Agent' node processes the classification, and the 'Sheet' node logs the results to a Google Sheet.
Apps Used
Workflow JSON
{
"id": "28c188e4-1a6f-4f5a-aae8-6cacf9ef150a",
"name": "Automate Quality Defect Classification with n8n",
"nodes": 0,
"category": "Manufacturing Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 28c188e4-1a6f...
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