Primetals Technologies Austria Gmbh

Primetals Technologies Germany Gmbh

Siemens Aktiengesellschaft

Siemens Vai Metals Technologies Gmbh

Günther Winter

Klaus Weinzierl

Georg Keintzel

Kurt Herzog

Thomas Matschullat

Matthias Kurz

Johannes Dagner

Andreas Maierhofer

Michael Diez

Otto Schmid

Kai Ankermann

Thomas Kuehas

Michael Weinzinger

Arno Haschke

Hans-Juergen Zeiher

Gerhard Kurka

Norbert Moritz

Martin Lehofer

Dieter Bettinger

Martin Rössiger

Norbert Goldenberg

Sensors detect states of units of a plant for producing and/or treating a rolled product made of metal and transmit them to an automation system. The state signals (Z) are, in part, dimensional signals. The automation system determines, by taking into account the state signals (Z), control signal signals (S) for actuators associated with the units and actuates the actuators accordingly. The automation system includes at least one model-based system which models the behavior of the system and/or of the rolled product in real time. The automation system transmits the state signals (Z), the control signals (S) and/or signals derived therefrom at least in part via an open data network to a human-machine interface arranged at an operating location. The transmitted signals comprise at least one of the dimensional signals. The automation system takes specifications (V) from the human-machine interface in determining the control signals (S).

Remote control of a plant for producing and/or treating a rolled product made of metal

An automation system () determines control data (S'), outputs same to controlled elements () of the facility (ANL) and thereby controls the facility (ANL). Sensor devices () acquire measurement data (M) of the facility (ANL) and at least partly feed same to the automation system () and a man-machine interface (). Said man-machine interface () receives planning data (P) from a production planning system () and/or control data (S&#x2032;) and/or internal data (I) from the automation system (). The interface outputs the data (M, S&#x2032;, I) to a person (). It furthermore receives control commands (S) from the person () and forwards them to the automation system (). The automation system () processes the measurement data (M) and the control commands (S) when determining the control data (S&#x2032;). An artificial intelligence unit () receives at least part of the measurement data (M), control data (S&#x2032;) and/or internal data (I) and the data output to the person (). It also receives the control commands (S). The artificial intelligence unit () processes the data (M, S&#x2032;, I) and control demands (S) received and determines evaluation results (A) therefrom and makes the latter available to the person () and/or to the production planning system () and/or sets them for the automation system () in the form of control commands (&#x2033;) directly or via the man-machine interface (). The data (M, S&#x2032;, I) received by the artificial intelligence unit () are at least to some extent dimensional data. Said dimensional data (M, S&#x2032;, I) comprise at least one image captured by a sensor device () or an image output via the man-machine interface (), 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.

Use of comprehensive artificial intelligence in primary industry plants

A production planning system () for a raw materials industry plant (ANL), which determines the production planning data (Pi) thereof and specifies said data to the automation system () of the plant (ANL). A state monitoring system () determines previous and future anticipated states (Z) of components of the plant (ANL). A quality determination system () determines states (Z) of output products (Ai) produced and still to be produced by the plant (ANL) and/or past and future states (Z) of the plant (ANL) as a whole. A maintenance planning system () and/or the production planning system () receive, from the state monitoring system (), the states (Z) of the components of the plant (ANL), determined by the state monitoring system () and, from the quality determination system (), the states (Zand Z) of the output products (Ai) and/or of the plant (ANL) as a whole, determined by the quality determination system (). They consider the data received from the state monitoring system () and from the quality determination system () in the determination of maintenance planning data (W) and/or the production planning data (Pi).

Integrated planning of production and/or maintenance plans

A method is disclosed for determining the speed of a rolling stock, for example the belt speed of a rolling belt, wherein electromagnetic radiation in the microwave range is transmitted to the rolling stock by at least one transmitting and receiving device and the belt speed is determined on the basis of the reflected and received reflection signal in an evaluation device. A device for carrying out such method is also disclosed.

Method and device for measuring the speed of a rolling stock

A combined continuous casting and rolling system, a control device for such system, and a method for producing rolling stock, e.g., metal strip, using such system are disclosed. The combined continuous casting and rolling system may include a casting device for casting metal and a roll train having at least one roll stand for hot forming the rolling stock, wherein the system is operated such that the rolling stock extends continuously between the casting device and the roll train, wherein rolling stock is continually supplied to the roll train, and wherein a predetermined target thickness progression for the rolling stock is predetermined. Because the thickness progression has at least two different target thicknesses for different sections in the longitudinal direction of the rolling stock and the thickness progression is designed such that particular target thicknesses are set at least twice, longitudinally profiled rolling stock may be produced relatively inexpensively.

Method for producing rolling stock by means of a combined continuous casting and rolling system, control device for a combined continuous casting and rolling system, and combined continuous casting and rolling system

A method operates a continuous annealing line for the processing of a rolled good, in particular a metal strip. A property of the rolled good in relation to a point or a section of the rolled good is fed to a computer-aided model as an input variable. The point or the section of the rolled good is located before or in the continuous annealing line. For the purpose of precise control of the continuous annealing process, at least one material property of the rolled good after the continuous annealing process is simulated by the computer-aided model and compared with a specified target value. If the simulated material property deviates from the target value, at least one process variable of the continuous annealing process is controlled as long as the point or the section of the rolled good is located before or in the continuous annealing line.

Method for operating a continuous annealing line for the processing of a rolled good

In a rolling mill train () for processing rolling stock (), at least three rolling stands () are directly adjacent in the rolling direction and are driven by electric motors () having superconducting windings. It is thereby possible to keep the distances between the rolling stands smaller than with conventional electric drives, thus reducing energy losses during the rolling process. A combined casting and rolling station (), which is equipped with such an electric motor () in the rolling stands, is configured and/or operated efficiently in terms of the required heating power.

Energy-saving rolling mill train and energy-saving process for operating a combined casting and rolling station

Growing community of inventors

Neunkirchen/Brand, Germany

Günther Winter