Intelligent Energy Utilization in Heat Treatment

Abstract Energy costs are the biggest expense factor in industrial heat treatment. Increasing efficiency and saving energy are therefore the focus of the further development of heat treatment plants. The increasing share of renewable energy in the power grid offers the opportunity to use cheap electricity with low CO 2 emissions. The fluctuating availability of renewable energy must be countered by intelligent process planning. To make this possible, numerical models are presented that can be used to forecast the power requirements of heat treatment processes. In particular, the modeling of thermal interactions within the heating chamber is explained. Targeted model simplifications enable short calculation times and practice-oriented parameterization. The results are validated using real process data. It is shown how simulation can be used in process planning to reduce emissions and costs and to make heat treatment processes more sustainable.