2025/06/12 by Luis Miguel Vieira da Silva, da Silva, Luis Miguel Vieira, Aljosha Köcher +3
Engineering · #Artificial Intelligence (cs.AI) #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #FOS: Electrical engineering #Flexible and Reconfigurable Manufacturing Systems #Manufacturing Process and Optimization #Scheduling and Optimization Algorithms #Software Engineering (cs.SE) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2506.11180
openalex publication_date 2025/06/12 · openalex created_date 2025/10/11 · openalex updated_date 2026/08/04
Explicit modeling of capabilities and skills -- whether based on ontologies, Asset Administration Shells, or other technologies -- requires considerable manual effort and often results in representations that are not easily accessible to Large Language Models (LLMs). In this work-in-progress paper, we present an alternative approach based on the recently introduced Model Context Protocol (MCP). MCP allows systems to expose functionality through a standardized interface that is directly consumable by LLM-based agents. We conduct a prototypical evaluation on a laboratory-scale manufacturing system, where resource functions are made available via MCP. A general-purpose LLM is then tasked with planning and executing a multi-step process, including constraint handling and the invocation of resource functions via MCP. The results indicate that such an approach can enable flexible industrial automation without relying on explicit semantic models. This work lays the basis for further exploration of external tool integration in LLM-driven production systems.