A new intelligent agent framework, AiInsight, is being applied to blast furnace operations, combining large language models with domain-specific skill packs, data sources, and knowledge bases. The system allows operators to use natural language for tasks such as historical diagnosis, target optimization, and production decision support. By integrating LLMs with industrial IoT data and process knowledge, the agent can perform data queries, process reasoning, script analysis, and report generation in a unified workflow. This represents a significant step in applying AI to heavy industry, where complex, high-stakes processes require both deep domain expertise and data-driven insights. The framework is designed to be extensible, potentially applicable to other industrial processes beyond steelmaking. For developers and engineers in industrial IoT, this showcases a practical architecture for building domain-specific AI agents that can handle real-world complexity.
This article presents an AI agent framework called AiInsight that integrates LLMs, skill packs, data sources, and domain knowledge to assist in blast furnace operations. It enables natural language queries for historical diagnosis, target optimization, and production decision support. This demonstrates the growing application of LLMs in heavy industry for complex, data-driven tasks.