Abstract
Data-driven methods are increasingly utilized in metal forming processes for monitoring and quality optimization. An adapted modeling notation DSL4DPiFS for forming processes is presented to model hardware, software, and data flow aspects to support the design and analysis of data-driven methods. DSL4DPiFS enables metal forming and automation experts to model field-level information as data sources, and the data sinks for data analysis. The notation was adapted to the requirements of selected metal forming processes and evaluated in three case studies.
| Translated title of the contribution | DSL4DPiFS - Eine Grafische Notation zur Modellierung von Daten-Pipelines in der Umformtechnik |
|---|---|
| Original language | English |
| Pages (from-to) | 232-250 |
| Number of pages | 19 |
| Journal | At-Automatisierungstechnik |
| Volume | 73 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2025 |
Keywords
- data pipeline
- data-driven methods
- forming process
- information model
- machine learning
- model-based system engineering
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