A. Mazak, A. Lüder, S. Wolny, M. Wimmer, D. Winkler, R. Rosendahl, H. Bayanifar, S. Biffl: Model-Based Generation of Runt-Time Data Collection Systems Exploiting AutomationML, at - Automatisierungstechnik, 66 (2018), pages 819 - 833.


Production system operators need support for collecting and pre-processing data on production systems consisting of several system components, as foundation for optimization and defect detection. Traditional approaches based on hard-coded programming of such runtime data collection systems take time and effort, and require both domain and technology knowledge. In this article, we introduce the AML-RTDC approach, which combines the strengths of AutomationML (AML) data modeling and model-driven engineering, to reduce the manual effort for realizing the run-time data collection (RTDC) system. We evaluate the feasibility of the AML-RTDC approach with a demonstration case about a lab-sized production system and a use case based on real-world requirements.