An automation system (1) determines control data (S), outputs same to controlled elements (5) of the facility (ANL) and thereby controls the facility (ANL). Sensor devices (2) acquire measurement data (M) of the facility (ANL) and at least partly feed same to the automation system (1) and a man-machine interface (3). Said man-machine interface (3) receives planning data (P) from a production planning system (11) and/or control data (S) and/or internal data (I) from the automation system (1). The interface outputs the data (M, S, I) to a person (4). It furthermore receives control commands (S) from the person (4) and forwards them to the automation system (1). The automation system (1) processes the measurement data (M) and the control commands (S) when determining the control data (S). An artificial intelligence unit (9) receives at least part of the measurement data (M), control data (S) and/or internal data (I) and the data output to the person (4). It also receives the control commands (S). The artificial intelligence unit (9) processes the data (M, S, I) and control demands (S) received and determines evaluation results (A) therefrom and makes the latter available to the person (4) and/or to the production planning system (11) and/or sets them for the automation system (1) in the form of control commands (5) directly or via the man-machine interface (3). The data (M, S, I) received by the artificial intelligence unit (9) are at least to some extent dimensional data. Said dimensional data (M, S, I) comprise at least one image captured by a sensor device (2) or an image output via the man-machine interface (3), part of such an image, a time sequence of such images or a time sequence of a part of such images or an acoustic oscillation or an acoustic oscillation spectrum.

A sampling unit samples an actual measurement value related to a driving result during a period of a driving under a known driving condition in order to process a material having different properties for each time zone. A driving result estimation unit obtains an estimated value related to the driving result from a value of the known driving condition and a value of an unknown driving condition. A condition estimation unit estimates the value of the unknown driving condition so that a difference between the actual measurement value related to the driving result and the estimated value related to the driving result is reduced.

In an energy-saving-operation recommending system, a total energy consumption of plural facilities during passage of one material to be rolled through a rolling line is calculated, and the total energy consumption is divided by a width and a length of the material to be rolled before rolling to calculate an energy consumption reference value that defines energy consumption per unit width and unit length of the material to be rolled. The energy consumption reference value is stored in association with a steel grade and a target post-rolling plate thickness of the material to be rolled. An energy consumption reference value corresponding to a steel grade and a target post-rolling plate thickness of a material to be next rolled on the rolling line is obtained. The energy consumption reference value is multiplied by a width and a length of the material to be next rolled to calculate predicted energy consumption.

In an energy-saving-operation recommending system, a total energy consumption of plural facilities during passage of one material to be rolled through a rolling line is calculated, and the total energy consumption is divided by a width and a length of the material to be rolled before rolling to calculate an energy consumption reference value that defines energy consumption per unit width and unit length of the material to be rolled. The energy consumption reference value is stored in association with a steel grade and a target post-rolling plate thickness of the material to be rolled. An energy consumption reference value corresponding to a steel grade and a target post-rolling plate thickness of a material to be next rolled on the rolling line is obtained. The energy consumption reference value is multiplied by a width and a length of the material to be next rolled to calculate predicted energy consumption.

An energy-saving control device for a rolling line, the energy-saving control device capable of finding rolling conditions for minimizing energy consumption for the rolling line while ensuring a quality of a product. The energy-saving control device for a rolling line includes: an energy consumption estimating unit that calculates energy consumption for the rolling line based on rolling conditions for the rolling line; and an energy consumption optimizing unit that changes a rolling condition other than a target temperature of a material to be rolled, as a manipulation item so that the energy consumption calculated by the energy consumption estimating unit is reduced while a quality of a product formed by rolling the material to be rolled is ensured.

An energy-saving control device for a rolling line, the energy-saving control device capable of finding rolling conditions for minimizing energy consumption for the rolling line while ensuring a quality of a product. The energy-saving control device for a rolling line includes: an energy consumption estimating unit that calculates energy consumption for the rolling line based on rolling conditions for the rolling line; and an energy consumption optimizing unit that changes a rolling condition other than a target temperature of a material to be rolled, as a manipulation item so that the energy consumption calculated by the energy consumption estimating unit is reduced while a quality of a product formed by rolling the material to be rolled is ensured.

A method of controlling a rolling mill production system for production of a coil-shaped end product from a slab, the production including processing the slab by sequentially arranged production units, the processing by the production units resulting in a respective strip-shaped product having physical data, the method including modeling, under consideration of the physical data, the processing of a testing product by a plurality of production units arranged downstream from a given production unit while taking into account the physical data. If the modelling shows that, under consideration of the physical data, one of the products resulting from processing by the downstream production units does not meet a predetermined quality criterion, the intended manufacture of the product is interrupted and a signal relating to the interrupting is outputted.

A method and a device for guiding and centering a metallic rolling stock in a rolling mill having at least one assembly that is arranged in a rolling line and at least one rolling mill stand for shaping the rolling stock are disclosed. The method includes the use of lateral guide means, which exert a lateral force onto the moving rolling stock at different locations of the rolling line, wherein the method further includes the process of centering the inflow of the rolling stock ahead of a first assembly and/or ahead of a first rolling mill stand of the rolling mill using first lateral guide means and the process of aligning rolling stock downstream transversely to the rolling line using second lateral guide means, wherein the process of centering the inflow includes a funnel-shaped, flat guiding of the rolling stock and a point-shaped guiding of the rolling stock.

A cold rolling mill rolling condition setting method using a prediction model being generated with an explanatory variable being first multi-dimensional data obtained by transforming past rolling performance data including pre-cold rolling data of a roll material on an entry side of the cold rolling mill into multi-dimensional data, and an objective variable being post-cold rolling data of the roll material on a delivery side of the cold rolling mill, the method includes: estimating a post-rolling shape of a roll target material by inputting, to the prediction model, second multi-dimensional data generated from information including the pre-cold rolling data of the roll target material on the entry side of the cold rolling mill and a target rolling condition of the cold rolling mill; and changing the target rolling condition of the cold rolling mill such that the estimated post-rolling shape of the roll target material satisfies a predetermined condition.

A provisional elongation strain difference distribution (x) of a metal strip during rolling is found under conditions in which out-of-plane deformation of the metal strip is restrained. A critical buckling strain difference distribution .sub.cr(x) is found based on the provisional elongation strain difference distribution (x), a strip thickness and strip width of the metal strip, and tension acting on the metal strip at exit from a rolling mill. When the provisional elongation strain difference distribution (x) exceeds the critical buckling strain difference distribution .sub.cr(x), the difference between the provisional elongation strain difference distribution (x) and the critical buckling strain difference distribution .sub.cr(x) is found, and added to the provisional elongation strain difference distribution (x) to find a true elongation strain difference distribution (x). Rolling conditions are set based on the true elongation strain difference distribution (x), and the metal strip is rolled, thereby controlling the metal strip's profile.