OPTIMIZATION OF THE MODELING OF PROCESS MODELS

• US 20200133209A1
• Filed: 04/10/2018
• Published: 04/30/2020
• Est. Priority Date: 04/18/2017
• Status: Active Grant

• Current Assignee: Primetals Technologies Germany GmbH (Siemens AG)
• Original Assignee: Primetals Technologies Germany GmbH (Siemens AG)
• Inventors: KURZ, Matthias, MIELE, Marco, THEKALE, Alexander
• Granted Patent: US 11,493,891 B2
• Time in Patent Office: Days
• CPC Class Codes: B21B 37/28 Control of flatness or profile during rolling of strip, sheets or plates
• CPC Class Codes: B21B 37/58 Roll-force control; Roll-gap control B21B38/105 takes precedence
• CPC Class Codes: B23P 17/02 Single metal-working processes; Machines or apparatus therefor
• CPC Class Codes: G05B 13/042 in which a parameter or coefficient is automatically adjusted to optimise the performance

Abstract

A model (8) is based on mathematical-physical equations. The model models the production of a particular output product (1) from at least one input product (2) supplied in each case to an installation in the raw materials industry on the basis of operation (B) of the installation. During production of the output products (1), the installation is controlled by a control device (5) in such a manner that particular actual operation (B) of the installation corresponds as far as possible to particular desired operation (B*) of the installation. The desired operation (B*) is determined by the control device (5) using the model (8) of the installation. The model (8) is parameterized according to a number of first model parameters (P1) for the purpose of modelling the installation. After a multiplicity of output products (1) have been produced in each case, actual sizes (A) of the output products (1) in the particular multiplicity are compared with expected sizes (A′) of the output products (1) in the particular multiplicity. On the basis of the comparison, the first model parameters (P1) are newly determined and the model (8) in the control device (5) is newly parameterized according to the new values of the first model parameters (P1). After this time, the desired operation (B*) is determined by the control device (5) using the newly parameterized model (8) of the installation in the raw materials industry. The expected sizes (A′) are determined by means of the model (8), wherein the determination of the expected sizes (A′) is based on the actual operation (B) of the installation.

Claims

1. An optimization method for a model

wherein the model is based on mathematical-physical equations and models the production of a respective output product from at least one input product supplied in each case to a facility of a raw material industry dependent on a mode (B) of the facility of the raw material industry,

controlling the facility of the raw material industry during the production of the output products by a control unit such that a respective actual mode (B) of the facility of the raw material industry corresponds as much as possible to a respective target mode (B*) of the facility of the raw material industry;

ascertaining the target mode (B*) by the control unit using the model of the facility of the raw material industry;

parameterizing the model for modeling the facility of the raw material industry in accordance with a number of first model parameters (P1),

in each case after the production of a plurality of output products, actual variables (A) of the output products of the respective plurality are compared to expected variables (A′

) of the output products of the respective plurality, re-ascertaining the first model parameters (P1) on the basis of the comparison, and re-parameterizing the model of the control unit in accordance with the new values of the first model parameters (P1) and ascertaining the target mode (B*) by the control unit from this point in time using the re-parameterized model of the facility of the raw material industry;

wherein the expected variables (A′

) are ascertained by means of the model; and

wherein the ascertainment of the expected variables (A′

) is based on the actual mode (B) of the facility of the raw material industry.

2. The optimization method as claimed in claim 1, further comprising implementing an optimizer by supplying input variables (E) describing the input products, the actual mode (B) of the facility of the raw material industry, and the actual variables (A) in each case to the optimizer for the re-ascertainment of the first model parameters (P1) for the respective plurality of output products, and ascertaining the first model parameters (P1) by the optimizer.

3. The optimization method as claimed in claim 1, further comprising:

pluralities of the output products, each plurality of the output products comprise multiple groups of the output products, and each group of the output products comprise at least one of the output products; and

in each case after the production of one of the groups of the output products, comparing the actual variables (A) of the output products of the respective group to expected variables (A′

) of the output products of the respective group, re-ascertaining a number of second model parameters (P2) is on the basis of the comparison, and re-parameterizing the model in accordance with the new values of the second model parameters (P2).

4. The optimization method as claimed in claim 3, wherein each group of the output products is equal to one output product.

5. The optimization method as claimed in claim 1, wherein the facility of the raw material industry is a rolling mill, and the production of the output product is the rolling of a flat rolling stock, and the actual variables (A) of the output products comprise the profile (P) and/or the contour (K) and/or the planarity (F) of the rolled flat rolling stock.

6. The optimization method as claimed in claim 5, wherein the first model parameters (P1), with respect to at least one roller of a rolling stand through which the flat rolling stock passes, comprise its modulus of elasticity (EM) and/or its influence (TC, WC) caused by the temperature and/or by wear on the contour (K) of the roller and/or, with respect to at least one rolling stand through which the flat rolling stock passes, comprise parameters for a material flow model, by means of which the material flow of the flat rolling stock in the rolling stand is modeled, and/or describe an adaptation of input variables (E) of the flat rolling stock.

7. The optimization method as claimed in claim 5, wherein the actual variables (A) of the output products comprise the profile (P) and/or the contour (K) and/or the planarity (F) of the rolled flat rolling stock, and the first model parameters (P1), with respect to at least one roller of a rolling stand through which the flat rolling stock passes, comprise its grind (S).

8. The optimization method as claimed in claim 7, wherein the first model parameters (P1) for describing the grind (S) of the roller comprise the radius (R) or the diameter of the roller at the position of the respective support point for a plurality of support points along the roller crown of the roller.

9. The optimization method as claimed in claim 7, further comprising ascertaining a deviation (δ

S) of the grind (S) of the roller from a target grind (S*) of the roller, and the deviation (δ

S) of the grind (S) from the target grind (S*) is associated with a respective grinding machine, by which the grind (S) was applied to the roller.

10. The optimization method as claimed in claim 7, wherein evaluating a time (δ

T) which has passed between a removal of the roller from the rolling stand and the grinding of the roller by means of the grinding machine, and ascertaining a thermal grinding error (δ

S′

) associated with the time (δ

T).

13. A processing unit, programmed using a computer program stored on a non-transitory recording medium, wherein

the program comprises machine code processable by a processing unit, wherein the processing of the machine code by the processing unit has the effect that the processing unit,

accepts actual variables (A) of a plurality of output products, which were produced by a facility of a raw material industry from at least one input product in each case, by input variables (E) of the associated input products, and by the actual modes (B) of the facility of the raw material industry during the production of the output products from the input products from a control unit controlling a facility of the raw material industry;

using input variables (E) of the respective input products and the respective actual mode (B) of the facility of the raw material industry, the processing unit ascertains expected variables (A′

) in each case for the output products by means of a model based on mathematical-physical equations and modeling the production of the output products from the input products depending on the respective actual mode (B) of the facility of the raw material industry;

after the production of the plurality of the output products, compares the actual variables (A) of the output products of the respective plurality to the expected variables (A′

) of the output products of the respective plurality and re-ascertains first model parameters (P1) on the basis of the comparison; and

provides the re-ascertained first model parameters (P1) to a control unit controlling the facility of the raw material industry for parameterizing a model implemented in the control unit so that the processing unit executes an optimization method as claimed in claim 1.

14. The processing unit as claimed in claim 13, wherein the computer program is designed such that the processing of the machine code by the processing unit has the effect that the processing unit implements the additional steps of:

the pluralities of the output products each comprise multiple groups of the output products which each comprise at least one of the output products; and

in each case after the production of one of the groups of the output products, comparing the actual variables (A) of the output products of the respective group to expected variables (A′

) of the output products of the respective group, re-ascertaining a number of second model parameters (P2) is on the basis of the comparison, and re-parameterizing the model in accordance with the new values of the second model parameters (P2).

15. A facility of a raw material industry for producing output products from at least one respective input product supplied in each case to the facility of the raw material industry,

associating a control unit configured for setting an actual mode (B) of the facility of the raw material industry with the facility of the raw material industry for controlling the facility of the raw material industry;

wherein the control unit comprises a model of the facility of the raw material industry based on mathematical-physical equations, with the use of the equations, the control unit ascertains a target mode (B*) of the facility of the raw material industry;

wherein the model models the production of a respective output product from at least one input product supplied in each case to a facility of the raw material industry depending on a mode (B) of the facility of the raw material industry;

wherein the model for modeling the facility of the raw material industry is configured to be parameterized in accordance with a number of first model parameters (P1);

wherein the control unit controls the facility of the raw material industry during the production of the output products in such a way that a respective actual mode (B) of the facility of the raw material industry corresponds as much as possible to the respective target mode (B*) of the facility of the raw material industry;

wherein the control unit is configured as a processing unit as claimed in claim 14, which has a data connection to the control unit, which is provided in addition to the control unit.

16. The facility of the raw material industry as claimed in claim 15, wherein the facility of the raw material industry is a rolling mill, and the production of the output product (1) is the rolling of a flat rolling stock.

17. The computer program as claimed in claim 10, wherein the processing of the machine code by the processing unit has the effect that the processing unit implements the additional steps of implementing an optimizer by supplying input variables (E) describing the input products, the actual mode (B) of the facility of the raw material industry, and the actual variables (A) in each case to the optimizer for the re-ascertainment of the first model parameters (P1) for the respective plurality of output products, and ascertaining the first model parameters (P1) by the optimizer.

18. A facility of a raw material industry for producing output products from at least one respective input product supplied in each case to the facility of the raw material industry,

associating a control unit configured for setting an actual mode (B) of the facility of the raw material industry with the facility of the raw material industry for controlling the facility of the raw material industry;

wherein the control unit comprises a model of the facility of the raw material industry based on mathematical-physical equations, with the use of the equations, the control unit ascertains a target mode (B*) of the facility of the raw material industry;

wherein the model models the production of a respective output product from at least one input product supplied in each case to a facility of the raw material industry depending on a mode (B) of the facility of the raw material industry;

wherein the model for modeling the facility of the raw material industry is configured to be parameterized in accordance with a number of first model parameters (P1);

wherein the control unit controls the facility of the raw material industry during the production of the output products in such a way that a respective actual mode (B) of the facility of the raw material industry corresponds as much as possible to the respective target mode (B*) of the facility of the raw material industry;

wherein the control unit is configured as a processing unit as claimed in claim 13, which has a data connection to the control unit, which is provided in addition to the control unit.

11. A computer program stored on a non-transitory recording medium, wherein the program comprises machine code processable by a processing unit, wherein the processing of the machine code by the processing unit has the effect that the processing unit

accepts actual variables (A) of a plurality of output products, which were produced by a facility of a raw material industry from at least one input product in each case, by input variables (E) of the associated input products, and by the actual modes (B) of the facility of the raw material industry during the production of the output products from the input products from a control unit controlling a facility of the raw material industry;

using the input variables (E) of the respective input products and the respective actual mode (B) of the facility of the raw material industry, the processing unit ascertains expected variables (A′

) in each case for the output products by means of a model based on mathematical-physical equations and modeling the production of the output products from the input products depending on the respective actual mode (B) of the facility of the raw material industry;

after the production of the plurality of the output products, compares the actual variables (A) of the output products of the respective plurality to the expected variables (A′

) of the output products of the respective plurality and re-ascertains first model parameters (P1) on the basis of the comparison; and

provides the re-ascertained first model parameters (P1) to a control unit controlling the facility of the raw material industry for parameterizing a model implemented in the control unit.

12. The computer program as claimed in claim 11, wherein the processing of the machine code by the processing unit has the effect that the processing unit implements an optimization method:

wherein a model is based on mathematical-physical equations and models the production of a respective output product from at least one input product supplied in each case to a facility of a raw material industry dependent on a mode (B) of the facility of the raw material industry;

controlling the facility of the raw material industry during the production of the output products by a control unit such that a respective actual mode (B) of the facility of the raw material industry corresponds as much as possible to a respective target mode (B*) of the facility of the raw material industry;

ascertaining the target mode (B*) by the control unit using the model of the facility of the raw material industry;

parameterizing the model for modeling the facility of the raw material industry in accordance with a number of first model parameters (P1);

in each case after the production of a plurality of output products, actual variables (A) of the output products of the respective plurality are compared to expected variables (A′

) of the output products of the respective plurality, re-ascertaining the first model parameters (P1) on the basis of the comparison, and re-parameterizing the model of the control unit in accordance with the new values of the first model parameters (P1) and ascertaining the target mode (B*) by the control unit from this point in time using the re-parameterized model of the facility of the raw material industry;

wherein the expected variables (A′

) are ascertained by means of the model;

wherein the ascertainment of the expected variables (A′

) is based on the actual mode (B) of the facility of the raw material industry; and

implementing an optimizer by supplying input variables (E) describing the input products, the actual mode (B) of the facility of the raw material industry, and the actual variables (A) in each case to the optimizer for the re-ascertainment of the first model parameters (P1) for the respective plurality of output products, and ascertaining the first model parameters (P1) by the optimizer.