Towards autonomous system: flexible modular production system enhanced with large language model agents

In this paper, we present a novel framework that combines large language models (LLMs), digital twins and industrial automation system to enable intelligent planning and control of production processes. Our approach involves developing a digital twin system that contains descriptive information about the production and retrofitting the automation system to offer unified interfaces of fine-granular functionalities or skills executable by automation components or modules. Subsequently, LLM-Agents are designed to interpret descriptive information in the digital twins and control the physical system through RESTful interfaces. These LLM-Agents serve as intelligent agents within an automation system, enabling autonomous planning and control of flexible production. Given a task instruction as input, the LLM-agents orchestrate a sequence of atomic functionalities and skills to accomplish the task. We demonstrate how our implemented prototype can handle un-predefined tasks, plan a production process, and execute the operations. This research highlights the potential of integrating LLMs into industrial automation systems for more agile, flexible, and adaptive production processes, while also underscoring the critical insights and limitations for future work.