LLM-Based Modelling of AAS-Compliant Digital Twins to Describe Capabilities in Manufacturing-as-a-Service

Disruptions threaten supply chains, creating a need for more resilient manufacturing networks. Manufacturing-as-a-Service (MaaS) has emerged as a promising Industry 4.0 approach to address this challenge. Yet, its effectiveness relies on interoperable digital twins (DTs), enabling the standardized exchange of manufacturing capabilities across organizational boundaries. The Asset Administration Shell (AAS) standards can be used to meet this requirement. However, modeling AAS-compliant DTs is considered challenging due to the standard’s complexity. This paper, therefore, investigates the automatic generation of AAS-compliant DTs for representing manufacturing capabilities. Requirements from MaaS use cases in two research projects reveal limitations in current approaches. To address these limitations, this paper introduces an automated, LLM-supported generation process that leverages ontologies as a domain-specific knowledge base. The approach is operationalized in a modular software architecture and demonstrated through two use cases.