An agentic LLM framework with multi-agent workflow, digital process plant twin, and Graph RAG on CPSMod ontology generates and validates fault recovery actions in simulation for discrete batch and continuous stirred-tank processes.
2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), 2024 , year =
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A semantic framework uses a knowledge graph on modular alignment ontology plus constrained LLM to generate C&E logic, narratives, and SWRL rules, shown on a modular process plant with claimed reduction in manual effort.
Integrates multi-head attention with SAC for faster convergence in optimizing additive manufacturing parameters to minimize porosity, outperforming DQN, PPO, TD3, and vanilla SAC.
A TPSR-based framework with four LLM roles integrates language model reasoning into industrial automation via digital twins, achieving high task executability in case studies.
A systematic literature review defines self-explainability, proposes a taxonomy and levels framework, and reports that most approaches are conceptual with no standard evaluation method.
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