Ghrairi, ZiedRedecker, Marc AllanDecker, AdnréHribernik, Karl A.Thoben, Klaus-DieterGómez, Jorge MarxSonnenschein, MichaelVogel, UteWinter, AndreasRapp, BarbaraGiesen, Nils2019-09-162019-09-162014https://dl.gi.de/handle/20.500.12116/25778This paper presents an approach aiming to reduce the energy consumption during the processing of natural raw materials. Natural raw materials are processed with more energy than they actually need. This is due to uncertainties on material and energy flows and to a lack of process flexibility and inappropriate machine configuration. The proposed approach combines techniques like artificial intelligence (expert systems) with technologies for data processing in order to create real-time “action plans” containing energy reduction suggestions for compound feed manufacturers. These suggestions are based on the correlation between energy consumption, product quality and process control by influencing the grain size, the steam amount and machine parameters. Through the application of expert systems the energy consumption in energy-intensive processes could be reduced and seen as an efficient way leading to lower CO2 emissions. At the end of the paper current results are detailed and future work is presented.Text/Conference Paper