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Publikation

Bridging the Qualification Gap for the Asset Administration Shell: A Modular and Role-Based Learning Framework

Daniel Büttner; Dirk Schöttke; Stephan Schäfer; Sönke Knoch; Daniel Porta; Tim Schwartz; Claudette Ocando Röhricht; Aaron Zielstorff; Andreas Bayha
In: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE International Conference on Emerging Technologies and Factory Automation (ETFA-2025), September 9-12, Porto, Portugal, Pages 1-8, IEEE, 10/2025.

Zusammenfassung

The Asset Administration Shell (AAS) provides the digital foundation for interoperable systems in Industry 4.0. However, small and medium-sized enterprises (SMEs) face critical barriers in workforce qualification due to the lack of scalable training logic that aligns organizational maturity and functional roles with structured, rule-based learning paths.This paper presents a modular training framework that combines an empirically validated maturity model with role-specific learning paths. Learners are routed into one of three tracks—Initiate, Integrate, or Anchor—based on diagnostic input that reflects their organizational readiness and functional role profiles.The framework is implemented in a configurable Learning Management System (LMS) utilizing rule-based logic, including conditional access, content visibility controls, and progression triggers. Validation is grounded in a structured survey of German SMEs, which confirms heterogeneous maturity levels and training needs.The resulting system enables differentiated, scalable upskilling strategies aligned with AAS deployment, offering a practical basis for integration into industrial qualification programs and corporate training infrastructures.

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