Wind Farm Maintenance Scheduling Workflow

This n8n workflow automates the planning and logging of wind farm maintenance activities using AI-powered analysis and data storage. The process begins with a webhook trigger that receives maintenance requests or updates. It then segments incoming data into manageable parts with a text splitter, preparing it for further analysis. These segments are transformed into embeddings via Hugging Face’s API, creating rich, searchable representations stored in a Weaviate vector database. When new data or previous maintenance records need to be referenced, queries retrieve relevant information from the database. The workflow employs a language model (OpenAI) to generate insights or recommendations based on the context, stored in a memory buffer. An agent uses the prompt and gathered data to define maintenance actions or notes, which are then logged into a Google Sheets document for record-keeping. This automation helps optimize maintenance scheduling, enhance data-driven decision-making, and streamline communication for wind farm operations.