Important results from the project
The project achieved its objective by delivering a pilot platform that processes shared data to guide energy-efficient equipment usage. While further validation is needed, the platform enabled production teams to begin to understand consumption patterns. It also created a foundation for future large-scale electrification efforts, inspired follow-up studies in related initiatives, and strengthened cross-functional collaboration around sustainable energy use.
Expected long term effects
The project is expected to drive a long-term change in how energy-intensive equipment is managed, by linking performance to both production and energy use. By integrating process and grid data, it supports proactive and sustainable operation and encourages industry to act as an active participant in the electricity grid. Can be coordinated with other large energy users, which can enable new collaboration models that help society address grid capacity challenges and support sustainable growth.
Approach and implementation
The developed pilot consists of a cloud platform and digital twin that uses machine learning-based forecasts of factory and city energy needs, combined with production needs, to recommend optimal start times for melting cycles that meet delivery requirements and reduce grid impact. Through close collaboration between production, software and energy experts, we have demonstrated how proactive, data-driven planning can support more sustainable and balanced industrial electricity use.
External links
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