Benefits of oxygen enrichment in sponge iron rotary kiln emerging from data-driven modelling

Abstract

Optimal oxygen enrichment conditions for sponge iron rotary kiln have been successfully explored on an industrial scale using a data-driven model. A multi-objective optimisation by genetic algorithm (MOGA) is employed to find the favourable conditions. The objective function for MOGA is derived from neural networks using pre-processed operational data. From industrial experimentations guided by the optimum conditions predicted by the present model, it emerged that when the coal fines injection is maintained at 1.75 tph and the oxygen enrichment is 8 Nm³ t⁻¹ of sponge iron, a reduction in the specific air requirement from 2609 to 2150 Nm³ t⁻¹ was obtained, while the end-zone bed temperature remained under control at 1132°C. These conditions resulted in a reduction of specific coal consumption by 6%, an enhancement in the sponge iron production by 6% and an increase in the rotary kiln campaign life from 50 to 100 days.