Model-driven System Architectures for Data Collection in Automated Production Systems

Description

Data collection from automated production systems for data analyses requires significant implementation efforts. This thesis addresses this challenge with a model-driven approach for the development of data collection architectures. A novel graphical domain-specific language enables a subsequent automated generation of the code for data collection architectures. Case-studies and industry experts confirm significantly reduced implementation efforts compared to manual implementation, as well as good applicability of the graphical modeling language.

Period	27 Oct 2020
Work for	unbekannt/unknown