Generative Artificial Intelligence for Intent-Based Industrial Automation

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Abstract
The evolution of consumer electronics is increasingly driven by advancements in industrial automation, where generative artificial intelligence (AI) plays a pivotal role, particularly in intent-based systems. This study presents a comprehensive framework for integrating generative AI into intent-based industrial automation, which aims to align high-level business goals with precise operational tasks on the factory floor. The proposed architecture synergistically combines three main components: Business Intents, the Intent Layer and the Factory Floor Shop. This framework leverages foundation models such as the most prominent large language models (LLMs) and advanced communication technologies to translate strategic business intents — such as cost optimization, order management and market adaptation — into actionable tasks to improve operational efficiency, responsiveness and strategic alignment. We also propose a process of fine-tuning LLMs to optimize their interaction flow within the intent-based system, highlighting the augmentation techniques employed to adapt LLMs for industrial contexts. Numerical results demonstrate the effectiveness of the proposed framework and show percentage improvements compared to pre-trained LLM models.

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