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arXiv · 2602.12419

Intent-Driven Smart Manufacturing Integrating Knowledge Graphs and Large Language Models

Takoua Jradi·John Violos·Dimitrios Spatharakis·Lydia Mavraidi·Ioannis Dimolitsas·Aris Leivadeas·Symeon Papavassiliou
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Abstract

The increasing complexity of smart manufacturing environments demands interfaces that can translate high-level human intents into machine-executable actions. This paper presents a unified framework that integrates instruction-tuned Large Language Models (LLMs) with ontology-aligned Knowledge Graphs (KGs) to enable intent-driven interaction in Manufacturing-as-a-Service (MaaS) ecosystems. We fine-tune Mistral-7B-Instruct-V02 on a domain-specific dataset, enabling the translation of natural language intents into structured JSON requirement models. These models are semantically mapped to a Neo4j-based knowledge graph grounded in the ISA-95 standard, ensuring operational alignment with manufacturing processes, resources, and constraints. Our experimental results demonstrate significant performance gains over zero-shot and 3-shots baselines, achieving 89.33\% exact match accuracy and 97.27\% overall accuracy. This work lays the foundation for scalable, explainable, and adaptive human-machine

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Takoua Jradi, John Violos, Dimitrios Spatharakis, Lydia Mavraidi, Ioannis Dimolitsas, Aris Leivadeas, Symeon Papavassiliou. 2026-02-12. Intent-Driven Smart Manufacturing Integrating Knowledge Graphs and Large Language Models. https://arxiv.org/abs/2602.12419

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