Based on BP network terminal quality prediction for BOF steelmaking process

The aspect of impact on the quality of steel is considered, according to the actual production process data in a refinery, BP neural network is applied to establish the steel quality forecasting model, which would improve steel making rate as a target. Based on existing Manage Information System of steelmaking factory, the factors which impact to hit ratio of steel´s kinds are investigated in details. A quality control model for the appropriate steelmaking process is studied, and the black box model of BOF steelmaking terminal prediction and process optimization is established. The results show that the steel pre-evaluation system is designed based on BP neural network to benefit for steel quality evaluation.