TRINEFLEX aims to transform energy-intensive process industries by integrating energy, process, and feedstock flexibility. TRINEFLEX will function as an end-to-end service managing the plants digital lifecycle and the process of transition to flexible and sustainable operation. This process will be enabled by advanced and green data acquisition, Big Data Infrastructures, process analysis, model development and finally Digital Twins with integrated multi-agent decision support systems.
The project will be implemented at five demonstration sites with unique challenges, from 4 sectors: glass, copper, aluminium and water industries.
ISENSE Group will lead the development of the Feedstock Adaptation Module which is an AI based decision support system component targeting optimization processes which are based on the qualitative characteristics of the feedstock, assuring increased feedstock sourcing flexibility and leading to the reduction of the raw materials dependency. The Feedstock Adaptation Agent will be also trained with the feedstock of the demo cases while ICCS will also define the methodology for “green ICT” as a part of the monitoring framework.
