Energy-optimal control of autoclaving processes using artificial intelligence
Project description
In the E|OptiKlav research project, a methodology is being investigated to support the energy-optimal operation of autoclave systems by using artificial intelligence, using the production of calcium silicate bricks as an example.
The European Green Deal requires the realisation of energy-saving potential, both from a societal perspective and due to the associated CO2 costs for SMEs in the calcium silicate brick industry. The behaviour of the steam system is plant-specific. Due to the high process complexity and system dynamics—especially during transition phases—fully algorithmic modelling can only be achieved with extensive experimental effort. As a result, the correct operating parameters for the plants can only be estimated from experience and are often controlled manually. Energy efficiency is frequently sacrificed in favour of throughput.
This research project therefore aims to investigate a less resource-intensive methodology, using hybrid AI methods, for achieving energy-optimal operation of autoclave systems. To this end, the plant-specific behaviour of the steam systems is learned from historical data and coupled with thermodynamic-physical modelling and expert knowledge. From this, operating recommendations can be derived and provided for energy-optimal system operation.
The project goal is to develop a solution that enables producers to save energy without additional investment or loss of productivity and that can be applied to other plants with minimal effort.
Associated partners:
UNIKA Kalksandsteinwerke Südbayern GmbH & Co. KG, Kalksandsteinwerk Wemding, Zapfwerke GmbH & Co. KG
Funded by:
