Advanced MRO Processes in Industry 4.0 with Proactive Asset Administration Shell and Digital Product Passport
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Published
Oct 21, 2025
Marco Weiss
Alexander Kamtsiuris
Florian Raddatz
Gerko Wende
Abstract
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.
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Keywords
Industry 4.0, Predictive Maintenance, Asset Administration Shell, Digital Product Passport, Maintenance Repair Overhaul, Prognostics and Health Management, Aircraft Systems
References
Ajdinović, S., Strljic, M., Lechler, A., & Riedel, O. (Hrsg.). (2024). Interoperable Digital Product Passports: An Event-Based Approach to Aggregate Production Data to Improve Sustainability and Transparency in the Manufacturing Industry. 2024 IEEE/SICE International Symposium on System Integration (SII) (S. 729-734). IEEE. doi:10.1109/SII58957.2024.10417487
Bhat, D., Muench, S., & Roellig, M. (2023). Application of machine learning algorithms in prognostics and health monitoring of electronic systems: A review. e-Prime - Advances in Electrical Engineering, Electronics and Energy, 4. doi:10.1016/j.prime.2023.100166
Cachada, A. e. (2018). Maintenance 4.0: Intelligent and Predictive Maintenance System Architecture. Emerging Technologies and Factory Automation (ETFA) (S. 139-146). Turin, Italy: IEEE. doi:10.1109/ETFA.2018.850248
Cavalieri, S., & Salafia, M. (2020). A Model for Predictive Maintenance Based on Asset Administration Shell. sensors, 20. doi:10.3390/s20216028
CIRPASS-2. (n.d.). CIRPASS-2. Abgerufen am 6. January 2025 von https://cirpass2.eu/
Crespi, N., Drobot, A., & Minerva, R. (2023). The Digital Twin: What and Why? In The Digital Twin. Springer, Cham. doi:10.1007/978-3-031-21343-4_1
Diedrich, C., Schroeder, T., & Belyaev, A. (2022). Interoperabilität von Cyber Physical Systems. In J. Jasperneite, Kommunikation und Bildverarbeitung in der Automation (Bd. 14, S. 99-115). Springer Vieweg. doi:10.1007/978-3-662-64283-2_8
DIN EN IEC 63278. (kein Datum). DIN EN IEC 63278-1 VDE 0810-781:2022-07 Asset Administration Shell for industrial applications. VDE Standards. Berlin: VDE Verlag.
DJI. (2024). MATRICE 350 RTK Maintenance Manual. Shenzhen, China: SZ DJI TECHNOLOGY CO.,LTD.
Donghan, W., Wei, D., Xiangyu, D., & Yan, L. (2021). Applications and Analysis of Digital Twin in Prognostic and Health Management. IEEE 11th International Conference on Electronics Information and Emergency Communication, (S. 200-203). Beijing. doi:10.1109/ICEIEC51955.2021.9463843
ECLASS. (January 2025). (E. e.V., Herausgeber) Von ECLASS data standard for products & services: https://eclass.eu/en/ abgerufen
EU 2024/1781. (2024). Regulation (EU) 2024/1781 of the European Parliament and of the Council. Abgerufen am 6. January 2025 von http://data.europa.eu/eli/reg/2024/1781/oj
Gleich, K., Behrendt, S., Hörger, M., Benfer, M., & Lanza, G. (October 2024). An Asset Administration Shell-Based Digital Product Passport as a Gaia-X Service. Procedia CIRP, 127, S. 224-229. doi:10.1016/j.procir.2024.07.039
Grunau, S., Redeker, M., Göllner, D., & Wisniewski, L. (2022). The Implementation of Proactive Asset Administration Shells: Evaluation of Possibilities and Realization in an Order Driven Production. Kommunikation und Bildverarbeitung in der Automation. Technologien für die intelligente Automation (S. 131-144). Springer Vieweg. doi:10.1007/978-3-662-64283-2_10
IDTA. (April 2023a). Specification of the Asset Administration Shell Part 1: Metamodel. Frankfurt am Main: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (June 2023b). Specification of the Asset Administration Shell Part 2: Application Programming Interfaces. Frankfurt am Main: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (March 2023c). Specification of the Asset Administration Shell Part 3a: Data Specification – IEC 61360. Frankfurt am Main, Germany: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (April 2023d). Specification of the Asset Administration Shell Part 5: Package File Format (AASX). Frankfurt am Main, Germany: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (2023e). IDTA Service Request Notification. Germany: Industrial Digital Twin Association.
ISO 13374-1. (2003). Condition monitoring and diagnostics of machines - Data processing, communication and presentation - Part 1: General guidelines. Switzerland: ISO.
Jensen. (kein Datum). Digital product passports for a circular economy: Data needs for product life cycle decision-making.
Jensen, S., Kristensen, J., Adamsen, S., Christensen, A., & Waehrens, B. (May 2023). Digital product passports for a circular economy: Data needs for product life cycle decision-making. Sustainable Production and Consumption, 37, S. 242-255. doi:10.1016/j.spc.2023.02.021.
Kebede, R., Moscati, A., Tan, H., & Johansson, P. (2024). A modular ontology modeling approach to developing digital product passports to promote circular economy in the built environment. Sustainable Production and Consumption, 48, S. 248-268. doi:10.1016/j.spc.2024.05.007
Leitão, P., Queiroz, J., & Sakurada, L. (2022). Collective Intelligence in Self-Organized Industrial Cyber-Physical Systems. Electronics, 11(19). doi:10.3390/electronics11193213
Plociennik, C., Pourjafarian, M., Nazeri, A., Windholz, W., Knetsch, S., Rickert, J., . . . Ruskowski, M. (2022). Towards a Digital Lifecycle Passport for the Circular Economy. Procedia CIRP, 105, S. 122-127. doi:10.1016/j.procir.2022.02.021
Pourjafarian, M., Plociennik, C., Rimaz, M., Stein, P., Vogelgesang, M., Li, C., . . . Ruskowski, M. (2023). A Multi-Stakeholder Digital Product Passport Based on the Asset Administration Shell. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) (S. 1-8). Sinaia: IEEE. doi:10.1109/ETFA54631.2023.10275715
Rahal, J., Schwarz, A., Sahelices, B., Weis, R., & Antón, S. (2023). The asset administration shell as enabler for predictive maintenance: a review. Journal of Intelligent Manufacturing, 2025(1), S. 19-33. doi:10.1007/s10845-023-02236-8
Sakurada, L., Prieta, F., & Leitao, P. (2023). A Methodology for Integrating Asset Administration Shells and Multi-agent Systems. IEEE International Symposium on Industrial Electronics. doi:10.1109/ISIE51358.2023.10227964
Sapel, P., & Hopmann, C. (2023). Towards an ontology-based dictionary for production planning and control in the domain of injection molding as a basis for standardized asset administration shells. (Elsevier, Hrsg.) Journal of Industrial Information Integration, 35. doi:10.1016/j.jii.2023.100488
Shaheen, B., & Németh, I. (24. 10 2022). Integration of Maintenance Management System Functions with Industry 4.0 Technologies and Features - A Review. Processes. doi:10.3390/pr10112173
Timjerdine, M., Taibi , S., & Moubachir, Y. (2024). Leveraging AI and Industry 4.0 in Aircraft Maintenance: Addressing Challenges and Improving Efficiency. International Conference on Global Aeronautical Engineering and Satellite Technology (S. 1-6). Marrakesh: IEEE. doi:10.1109/GAST60528.2024.10520779
VDI2193-1. (4 2020). VDI/VDE 2193 Part 1:2020-04 Language for I4.0 components. Structure of messages. Düsseldorf, Germany: VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik.
VDI2193-2. (4 2022). VDI/VDE 2193 Part 2:2020-01 Language for I4.0 components. Interaction protocol for bidding procedures. 36. Germany: VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik.
Voulgaridis, K., Lagkas, T., Angelopoulos, C., Boulogeorgos, A., Argyriou, V., & Sarigiannidis, P. (April 2024). Digital product passports as enablers of digital circular economy: a framework based on technological perspective. Telecommunication Systems, 85(4), S. 699–715. doi:10.1007/s11235-
024-01104-x
Watson, K., Patzer, F., Schöppenthau, F., & Schnebel, B. (April 2023). Achieving a Sustainable Economy with Digital Product Passports. IIC Journal of Innovation(22), S. 22-45. doi:10.24406/publica-1287
Weiss, M., Pakala, H., Wicke, K., Gill, M., & Wende, G. (2023). MaSiMO - Development and Research of Industry 4.0 Components with a Focus on Experimental Applications of Proactive Asset Administration Shells in Data-Driven Maintenance Environments. DLRK 2023. Stuttgart: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/610125
Weiss, M., Raddatz, F., & Wende, G. (2024). MaSiMO – Digital Product Passport and Autonomous Event Management of Industry 4.0 Components with Proactive AAS in Data-Driven Aviation Maintenance and Production. Deutscher Luft- und Raumfahrtkongress 2024 (S. 17). Hamburg: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/630084
Weiss, M., Wicke, K., & Wende, G. (2022). MaSiMO - A Hybrid Experimental Platform for the Simulation and Evaluation of Data-Driven Maintenance Enterprises. DLRK2022 - NETZPUBLIKATIONEN. Dresden: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/570154
Wiesner, M., Moreira, J., Guizzardi, R., & Scholz, P. (2024). A Reference Architecture for Digital Product Passports at Batch Level to Support Manufacturing Supply Chains. In Research Challenges in Information Science (S. 307-323). Springer, Cham. doi:10.1007/978-3-031-59465-6_19
Winkler, D., Gill, M., & Fay, A. (2022). The Asset Administration Shell as a Solution Concept for the Realisation of Interoperable Digital Twins of Aircraft Components in Maintenance, Repair and Overhaul. DLRK. Dresden: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/570274
Zeid, A., Sundaram, S., Moghaddam, M., Kamarthi, S., & Marion, T. (2019). Interoperability in Smart Manufacturing: Research Challenges. Machines, 7(2). doi:10.3390/machines7020021
Zhao, Z., Wu, J., Li, T., Sun, C., Yan, R., & Chen, X. (2021). Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review. Chinese Journal of Mechanical Engineering volume, 34(56). doi:10.1186/s10033-021-00570-7
Zio, E. (2021). Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice. (Elsevier, Hrsg.) Reliability Engineering & System Safety, 218(Part A). doi:10.1016/j.ress.2021.108119
Zonta, T., da Costa, C., & da Rosa, R. (2020). Predictive maintenance in the Industry 4.0: A systematic literature review. Computers & Industrial Engineering, 150. doi:10.1016/j.cie.2020.106889
Bhat, D., Muench, S., & Roellig, M. (2023). Application of machine learning algorithms in prognostics and health monitoring of electronic systems: A review. e-Prime - Advances in Electrical Engineering, Electronics and Energy, 4. doi:10.1016/j.prime.2023.100166
Cachada, A. e. (2018). Maintenance 4.0: Intelligent and Predictive Maintenance System Architecture. Emerging Technologies and Factory Automation (ETFA) (S. 139-146). Turin, Italy: IEEE. doi:10.1109/ETFA.2018.850248
Cavalieri, S., & Salafia, M. (2020). A Model for Predictive Maintenance Based on Asset Administration Shell. sensors, 20. doi:10.3390/s20216028
CIRPASS-2. (n.d.). CIRPASS-2. Abgerufen am 6. January 2025 von https://cirpass2.eu/
Crespi, N., Drobot, A., & Minerva, R. (2023). The Digital Twin: What and Why? In The Digital Twin. Springer, Cham. doi:10.1007/978-3-031-21343-4_1
Diedrich, C., Schroeder, T., & Belyaev, A. (2022). Interoperabilität von Cyber Physical Systems. In J. Jasperneite, Kommunikation und Bildverarbeitung in der Automation (Bd. 14, S. 99-115). Springer Vieweg. doi:10.1007/978-3-662-64283-2_8
DIN EN IEC 63278. (kein Datum). DIN EN IEC 63278-1 VDE 0810-781:2022-07 Asset Administration Shell for industrial applications. VDE Standards. Berlin: VDE Verlag.
DJI. (2024). MATRICE 350 RTK Maintenance Manual. Shenzhen, China: SZ DJI TECHNOLOGY CO.,LTD.
Donghan, W., Wei, D., Xiangyu, D., & Yan, L. (2021). Applications and Analysis of Digital Twin in Prognostic and Health Management. IEEE 11th International Conference on Electronics Information and Emergency Communication, (S. 200-203). Beijing. doi:10.1109/ICEIEC51955.2021.9463843
ECLASS. (January 2025). (E. e.V., Herausgeber) Von ECLASS data standard for products & services: https://eclass.eu/en/ abgerufen
EU 2024/1781. (2024). Regulation (EU) 2024/1781 of the European Parliament and of the Council. Abgerufen am 6. January 2025 von http://data.europa.eu/eli/reg/2024/1781/oj
Gleich, K., Behrendt, S., Hörger, M., Benfer, M., & Lanza, G. (October 2024). An Asset Administration Shell-Based Digital Product Passport as a Gaia-X Service. Procedia CIRP, 127, S. 224-229. doi:10.1016/j.procir.2024.07.039
Grunau, S., Redeker, M., Göllner, D., & Wisniewski, L. (2022). The Implementation of Proactive Asset Administration Shells: Evaluation of Possibilities and Realization in an Order Driven Production. Kommunikation und Bildverarbeitung in der Automation. Technologien für die intelligente Automation (S. 131-144). Springer Vieweg. doi:10.1007/978-3-662-64283-2_10
IDTA. (April 2023a). Specification of the Asset Administration Shell Part 1: Metamodel. Frankfurt am Main: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (June 2023b). Specification of the Asset Administration Shell Part 2: Application Programming Interfaces. Frankfurt am Main: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (March 2023c). Specification of the Asset Administration Shell Part 3a: Data Specification – IEC 61360. Frankfurt am Main, Germany: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (April 2023d). Specification of the Asset Administration Shell Part 5: Package File Format (AASX). Frankfurt am Main, Germany: Industrial Digital Twin Organization. Von https://industrialdigitaltwin.org/ abgerufen
IDTA. (2023e). IDTA Service Request Notification. Germany: Industrial Digital Twin Association.
ISO 13374-1. (2003). Condition monitoring and diagnostics of machines - Data processing, communication and presentation - Part 1: General guidelines. Switzerland: ISO.
Jensen. (kein Datum). Digital product passports for a circular economy: Data needs for product life cycle decision-making.
Jensen, S., Kristensen, J., Adamsen, S., Christensen, A., & Waehrens, B. (May 2023). Digital product passports for a circular economy: Data needs for product life cycle decision-making. Sustainable Production and Consumption, 37, S. 242-255. doi:10.1016/j.spc.2023.02.021.
Kebede, R., Moscati, A., Tan, H., & Johansson, P. (2024). A modular ontology modeling approach to developing digital product passports to promote circular economy in the built environment. Sustainable Production and Consumption, 48, S. 248-268. doi:10.1016/j.spc.2024.05.007
Leitão, P., Queiroz, J., & Sakurada, L. (2022). Collective Intelligence in Self-Organized Industrial Cyber-Physical Systems. Electronics, 11(19). doi:10.3390/electronics11193213
Plociennik, C., Pourjafarian, M., Nazeri, A., Windholz, W., Knetsch, S., Rickert, J., . . . Ruskowski, M. (2022). Towards a Digital Lifecycle Passport for the Circular Economy. Procedia CIRP, 105, S. 122-127. doi:10.1016/j.procir.2022.02.021
Pourjafarian, M., Plociennik, C., Rimaz, M., Stein, P., Vogelgesang, M., Li, C., . . . Ruskowski, M. (2023). A Multi-Stakeholder Digital Product Passport Based on the Asset Administration Shell. 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) (S. 1-8). Sinaia: IEEE. doi:10.1109/ETFA54631.2023.10275715
Rahal, J., Schwarz, A., Sahelices, B., Weis, R., & Antón, S. (2023). The asset administration shell as enabler for predictive maintenance: a review. Journal of Intelligent Manufacturing, 2025(1), S. 19-33. doi:10.1007/s10845-023-02236-8
Sakurada, L., Prieta, F., & Leitao, P. (2023). A Methodology for Integrating Asset Administration Shells and Multi-agent Systems. IEEE International Symposium on Industrial Electronics. doi:10.1109/ISIE51358.2023.10227964
Sapel, P., & Hopmann, C. (2023). Towards an ontology-based dictionary for production planning and control in the domain of injection molding as a basis for standardized asset administration shells. (Elsevier, Hrsg.) Journal of Industrial Information Integration, 35. doi:10.1016/j.jii.2023.100488
Shaheen, B., & Németh, I. (24. 10 2022). Integration of Maintenance Management System Functions with Industry 4.0 Technologies and Features - A Review. Processes. doi:10.3390/pr10112173
Timjerdine, M., Taibi , S., & Moubachir, Y. (2024). Leveraging AI and Industry 4.0 in Aircraft Maintenance: Addressing Challenges and Improving Efficiency. International Conference on Global Aeronautical Engineering and Satellite Technology (S. 1-6). Marrakesh: IEEE. doi:10.1109/GAST60528.2024.10520779
VDI2193-1. (4 2020). VDI/VDE 2193 Part 1:2020-04 Language for I4.0 components. Structure of messages. Düsseldorf, Germany: VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik.
VDI2193-2. (4 2022). VDI/VDE 2193 Part 2:2020-01 Language for I4.0 components. Interaction protocol for bidding procedures. 36. Germany: VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik.
Voulgaridis, K., Lagkas, T., Angelopoulos, C., Boulogeorgos, A., Argyriou, V., & Sarigiannidis, P. (April 2024). Digital product passports as enablers of digital circular economy: a framework based on technological perspective. Telecommunication Systems, 85(4), S. 699–715. doi:10.1007/s11235-
024-01104-x
Watson, K., Patzer, F., Schöppenthau, F., & Schnebel, B. (April 2023). Achieving a Sustainable Economy with Digital Product Passports. IIC Journal of Innovation(22), S. 22-45. doi:10.24406/publica-1287
Weiss, M., Pakala, H., Wicke, K., Gill, M., & Wende, G. (2023). MaSiMO - Development and Research of Industry 4.0 Components with a Focus on Experimental Applications of Proactive Asset Administration Shells in Data-Driven Maintenance Environments. DLRK 2023. Stuttgart: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/610125
Weiss, M., Raddatz, F., & Wende, G. (2024). MaSiMO – Digital Product Passport and Autonomous Event Management of Industry 4.0 Components with Proactive AAS in Data-Driven Aviation Maintenance and Production. Deutscher Luft- und Raumfahrtkongress 2024 (S. 17). Hamburg: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/630084
Weiss, M., Wicke, K., & Wende, G. (2022). MaSiMO - A Hybrid Experimental Platform for the Simulation and Evaluation of Data-Driven Maintenance Enterprises. DLRK2022 - NETZPUBLIKATIONEN. Dresden: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/570154
Wiesner, M., Moreira, J., Guizzardi, R., & Scholz, P. (2024). A Reference Architecture for Digital Product Passports at Batch Level to Support Manufacturing Supply Chains. In Research Challenges in Information Science (S. 307-323). Springer, Cham. doi:10.1007/978-3-031-59465-6_19
Winkler, D., Gill, M., & Fay, A. (2022). The Asset Administration Shell as a Solution Concept for the Realisation of Interoperable Digital Twins of Aircraft Components in Maintenance, Repair and Overhaul. DLRK. Dresden: Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V. doi:10.25967/570274
Zeid, A., Sundaram, S., Moghaddam, M., Kamarthi, S., & Marion, T. (2019). Interoperability in Smart Manufacturing: Research Challenges. Machines, 7(2). doi:10.3390/machines7020021
Zhao, Z., Wu, J., Li, T., Sun, C., Yan, R., & Chen, X. (2021). Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review. Chinese Journal of Mechanical Engineering volume, 34(56). doi:10.1186/s10033-021-00570-7
Zio, E. (2021). Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice. (Elsevier, Hrsg.) Reliability Engineering & System Safety, 218(Part A). doi:10.1016/j.ress.2021.108119
Zonta, T., da Costa, C., & da Rosa, R. (2020). Predictive maintenance in the Industry 4.0: A systematic literature review. Computers & Industrial Engineering, 150. doi:10.1016/j.cie.2020.106889
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Technical Papers