A supervisor-specialist multi-agent system with structured artifact reuse and dynamic replanning improves planning effectiveness by 54.5% and task completion by 37.8% over baseline for industrial maintenance QA while cutting tool time share from 47.3% to 26.3%.
AssetOpsBench: AI Agents for Industrial Asset Operations and Maintenance
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Towards Multi-Turn Dialog Systems for Industrial Asset Operations and Maintenance
A supervisor-specialist multi-agent system with structured artifact reuse and dynamic replanning improves planning effectiveness by 54.5% and task completion by 37.8% over baseline for industrial maintenance QA while cutting tool time share from 47.3% to 26.3%.