Predictive Models on Energy Consumption

The development of tools to predict energy consumption is very useful because it can be employed to evaluate the effect of the process variables, selection of the metallic charge, and optimize the best mixture of raw materials that minimize the total consumption of energy to produce liquid steel. This chapter describes different models. Statistical models represent the simplest case and easy to develop but are valid for specific conditions. Machine learning models and mathematical models are more general but involve more computations.