Defining Scalable Data Models for Operational Data Integration in Manufacturing Processes Within the Digital Product Passport Framework Through OPC UA and Asset Administration Shell

This paper outlines a comprehensive approach to building scalable data models for the integration of operational data within the Digital Product Passport (DPP) framework. The primary objective is to enable seamless data exchange in manufacturing processes throughout the supply chain, with a particular focus on the upcoming Manufacturing-X environment. Using key industry standards, in particular the Open Platform Communications Unified Architecture (OPC UA) and the Asset Administration Shell (AAS), this methodology aims to facilitate the active participation of companies in a substantial cross-supply-chain data collaboration. The present dilemma relates to the lack of compatibility between these standards, which requires a methodological intervention or approach. The suggested data models tackle the intricacies of various manufacturing procedures, providing a well-organised and coherent demonstration of operational data. Through the use of DPP, the digital association of manufacturing data with products facilitates seamless documentation of components and, for instance, allows the calculation of energy balances. Every participant in the supply chain should present data in a standardised format, a process that Manufacturing-X encourages. The present research showcases the implementation of key concepts and a scalable data model. The concept harmoniously integrates the manufacturing data from OPC UA into AAS. Furthermore, this study evaluates the effectiveness of this methodology in manufacturing environments, providing valuable insights into scalable data models.