The blast furnace ironmaking is a “black box” operation and the blast furnace hearth plays a vital role in production. In this paper, the blast furnace hearth visualisation system is based on the actual blast furnace production data and the raw data processing is completed by feature engineering. It is worth noting that firstly, based on heat transfer and finite element method, BP neural network is used to predict and simulate the erosion state of the furnace hearth. Secondly, the temperature measurement points and temperature field derived parameters of the furnace chamber area are visualised, and the XGboost algorithm is used to achieve accurate prediction of key parameters; finally, the online operation of the blast furnace hearth visualisation system is realised based on the industrial internet platform, contributing to the intelligence of blast furnace ironmaking. Finally, the online operation of the blast furnace hearth visualisation system is realised based on the industrial internet platform, contributing to the intelligence of blast furnace ironmaking.