Ask Your Factory Floor Anything: Structuring Industrial Data for AI Agents

A Unified Namespace (UNS) is proposed as a solution for integrating time-series data and equipment context in industrial settings, allowing for streamlined data querying without the need for complex cross-system integration. By using a single PostgreSQL instance with TimescaleDB, both datasets share a query planner, enabling efficient contextualization of industrial data. The UNS schema provides a structured hierarchy for data storage, with specific tables for mapping the ISA-95 hierarchy and storing time-series readings. The database enforces data quality at the schema level, ensuring reliable data analysis and facilitating complex queries that can be used by AI agents. This approach eliminates the need for middleware or application-layer stitching, allowing manufacturers to efficiently query and contextualize data such as equipment usage and performance metrics through simple SQL queries. The architecture supports scalability and operational efficiency, providing a robust foundation for AI-enabled industrial data analysis and decision-making.

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