The invention relates to a method for controlling a combustion in a furnace (100) which is heated by a burner (160) with at least one oxygen lance (120), wherein a fuel is supplied via a fuel supply (110) of the burner (110) and oxygen is supplied at least in part with a high speed of 100 m/s or more by the at least one oxygen lance (120), and wherein oxygen in an overstoichiometric range is supplied. The invention further relates to a furnace (100) for carrying out said method.

Controlling circumferential variability in a blast furnace may include generating a predictive model that sets up a relationship between a standard deviation of a selected state variable, state variables and one or more control variables in blast furnace operation for predicting the standard deviation. A number of circumferential sections of the blast furnace is defined, and the predictive model associated with the selected state variable for each of the circumferential sections is trained based on process data of the blast furnace. A plurality trained predictive models is generated associated with different circumferential sections and different selected state variables. One or more future control variable set points that minimize a sum of the plurality of predictive models, is determined. One or more future control variable set points is transmitted to a control system to control the blast furnace operation.

Controlling circumferential variability in a blast furnace may include generating a predictive model that sets up a relationship between a standard deviation of a selected state variable, state variables and one or more control variables in blast furnace operation for predicting the standard deviation. A number of circumferential sections of the blast furnace is defined, and the predictive model associated with the selected state variable for each of the circumferential sections is trained based on process data of the blast furnace. A plurality trained predictive models is generated associated with different circumferential sections and different selected state variables. One or more future control variable set points that minimize a sum of the plurality of predictive models, is determined. One or more future control variable set points is transmitted to a control system to control the blast furnace operation.

A blast furnace control system may include a hardware processor that generates a deep learning based predictive model for forecasting hot metal temperature, where the actual measured HMT data is only available sparsely, and for example, measured at irregular interval of time. HMT data points may be imputed by interpolating the HMT measurement data. HMT gradients are computed and a model is generated to learn a relationship between state variables and the HTM gradients. HMT may be forecasted for a time point, in which no measured HMT data is available. The forecasted HMT may be transmitted to a controller coupled to a blast furnace, to trigger a control action to control a manufacturing process occurring in the blast furnace.

A blast furnace control system may include a hardware processor that generates a deep learning based predictive model for forecasting hot metal temperature, where the actual measured HMT data is only available sparsely, and for example, measured at irregular interval of time. HMT data points may be imputed by interpolating the HMT measurement data. HMT gradients are computed and a model is generated to learn a relationship between state variables and the HTM gradients. HMT may be forecasted for a time point, in which no measured HMT data is available. The forecasted HMT may be transmitted to a controller coupled to a blast furnace, to trigger a control action to control a manufacturing process occurring in the blast furnace.

A blast furnace control system may include a hardware processor that generates a deep learning based predictive model for forecasting hot metal temperature, where the actual measured HMT data is only available sparsely, and for example, measured at irregular interval of time. HMT data points may be imputed by interpolating the HMT measurement data. HMT gradients are computed and a model is generated to learn a relationship between state variables and the HTM gradients. HMT may be forecasted for a time point, in which no measured HMT data is available. The forecasted HMT may be transmitted to a controller coupled to a blast furnace, to trigger a control action to control a manufacturing process occurring in the blast furnace.

A surface profile detection apparatus of a burden in a blast furnace includes a rotating plate mounted immediately above an opening part of the blast furnace and configured to rotate about an opening center of the opening part as a central axis, a rotating means for rotating the rotating plate, and a transmission and reception means for transmitting a detection wave such as a microwave or a millimeter wave in a linear shape along a diametrical direction of the rotating plate and receiving the detection wave. The surface profile detection apparatus performs transmission and reception in a direction orthogonal to a rotating direction of the rotating plate while rotating the rotating plate in synchronization with turning of the shooter so that transmission of the detection wave is not interrupted.

A fine ratio measuring device that measures the fine ratio of fines adhering to the surface of the material in the form of lumps includes: an illumination unit that illuminates the material in the form of lumps; an imaging unit that captures an image of the material in the form of lumps and produces image data; and an arithmetic unit including a computation unit that computes a characteristic quantity of the image data produced by the imaging unit and a conversion unit that converts the characteristic quantity computed by the computation unit to the fine ratio.

A method of manufacturing a steel product into at least two different steelmaking units wherein an expected level of CO2 emissions for the manufacturing of said product in each respective steelmaking unit is calculated.

A method to manufacture a steel product in a steelmaking plant including several different tools, the method including the definition of at least two manufacturing routes using different tools and the calculation of the expected level of CO2 emissions associated to each of this defined manufacturing routes.