Advanced MRO Processes in Industry 4.0 with Proactive Asset Administration Shell and Digital Product Passport

As industries enhance efficiency, reliability, and sustainability in Maintenance, Repair, and Overhaul (MRO) operations, digitalization plays a pivotal role. In this context, Industry 4.0 technologies are transforming maintenance into autonomous, data-driven systems, improving performance and reducing costs. Within this shift, Prognostics and Health Management (PHM) provides a structured approach to organizing condition monitoring, event diagnosis, prediction and instruction. However, its implementation remains complex due to the heterogeneous nature of the assets, the large number of potential events (e.g. anomalies), the quality and incompleteness of the data, and the missing standardized data exchange. In this regard, the paper explores how PHM can be effectively implemented using proactive Asset Administration Shells (AAS) and Digital Product Passports (DPPs), enabling smart, self-managed maintenance ecosystems on a common ground. Thus, the integration of AAS and DPPs facilitates PHM by enabling autonomous event detection, prediction, and service negotiation while translating predictive insights into actionable maintenance workflows. They also consolidate lifecycle data, ensuring regulatory compliance, traceability, and circular economy integration. An experimental setup utilizing an Unmanned Aircraft System (UAS) and a robotic MRO station verifies this approach. The system integrates Z-factor statistical analysis, multi-tiered predictive modeling, and structured event-task mapping to automate maintenance actions and optimize decision-making. Results demonstrate improved failure detection, extended asset lifetimes, and reduced material waste and operational downtime.