Integrating Large Language Models into Digital Twins for Enhanced Manufacturing Process Control

Abstract

The rapid development of Industry 4.0 has introduced advanced technologies such as IoT, cyber-physical systems (CPS), and industrial IoT into manufacturing environments. However, traditional production management systems remain largely reactive, operating in discrete modes with fragmented interfaces. This paper presents a concept for a production management support system that integrates large language models (LLMs) that enable natural language interaction. This solution concept addresses the key challenge of data fragmentation by creating an intelligent digital twin that acts as a production expert capable of contextual reasoning, information synthesis from multiple sources, and real-time decision support. This concept demonstrates the potential to transform production management from a reactive to a proactive operating model by leveraging LLM’s capabilities in pattern recognition, predictive analysis, and automated recommendation generation. Future development directions focus on optimizing business intelligence integration, improving automated recommendation mechanisms, and standardizing natural language user interfaces for industrial applications.