- Titel
- Energy-adaptive production systems through AI-supported forecasting, consumption analysis, and energy-adaptive detailed planning
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:l189-qucosa2-1026149
- Konferenz
- 22. AALE-Konferenz. Rosenheim, 25. Februar - 27. Februar 2026
- Quellenangabe
- Tagungsband AALE 2026
; Mechatronische Systeme für die Automatisierung: Fortschritt durch Präzision und Qualität
Herausgeber: Hochschule für Technik, Wirtschaft und Kultur Leipzig
Erscheinungsort: Leipzig
Erscheinungsjahr: 2026
Seiten: 159-165
ISBN: 978-3-910103-08-5 - Erstveröffentlichung
- 2026
- DOI
- https://doi.org/10.33968/2026.16
- Abstract (EN)
- This paper describes the increasing shift in the importance of energy as a strategic production factor in industry, caused by volatile electricity markets, rising energy prices, and the growing share of renewable energies. Traditional production and energy management approaches are reaching their limits, as energy and production systems are usually considered separately. The DIANEpro research project addresses this gap with a data-driven approach to energy-adaptive production. At the heart of the project is the integration of AI-based forecasts of renewable energy generation (LSTM models) and non-intrusive load monitoring (NILM) for transparent recording of industrial energy consumption. The results are consolidated in a cloud-based demand response platform and linked to existing ERP, MES, and APS systems. DIANEpro demonstrates that energy-adaptive production planning is technically feasible and industrially viable, especially for SMEs. In the long term, the approach enables dynamic detailed production planning that takes energy into account as an explicit optimization variable, thus making an important contribution to the sustainable and resilient transformation of industrial production systems.
- Freie Schlagwörter (DE)
- 22. Konferenz für Angewandte Automatisierungstechnik in Lehre und Entwicklung an Hochschulen (AALE)
- Freie Schlagwörter (EN)
- Industrial transformation, Industrial energy management, Energy-adaptive production
- Herausgeber (Institution)
- Hochschule für Technik, Wirtschaft und Kultur Leipzig, Leipzig
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:l189-qucosa2-1026149
- Veröffentlichungsdatum Qucosa
- 25.02.2026
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- English
- Lizenz / Rechtehinweis
CC BY 4.0