A Dynamic Control Method and System for Industrial Production Processes

Abstract

The present invention relates to a method and system for dynamically controlling an industrial production process. The method includes: constructing different meta-operation units according to different process operations; selecting a production control process composed of multiple meta-operation units; constructing an end-state prediction model according to the production control process; receiving the state information of the industrial production raw materials entering the station, calculating dynamic control parameters; sending the production control process to the industrial production control equipment; conducting real-time monitoring of industrial production control, and dynamically adjusting the dynamic control parameters when entering the dynamic control step; after the production control process is executed, comparing and analyzing the target state with the actual end state, and optimizing the correlation coefficients used for calculating the dynamic control parameters according to the comparison result. The present invention can realize the dynamic adjustment of the dynamic control parameters in the production process, and can avoid the influence of problems suddenly occurring in the intermediate process of the actual production process on the overall production.

Description

Technical Field

[0001] The present invention relates to the field of industrial production, and in particular, to a method and system for dynamically controlling an industrial production process. Background Art

[0002] The following technical problems exist in existing industrial production:

[0003] (1) Some production operations are manual or semi-automated.

[0004] (2) Production operations completely rely on the production experience of the operation team, and the product quality is prone to fluctuations.

[0005] (3) The production operation process is not standardized, which is not conducive to lean management.

[0006] (4) A single mathematical model is calculated offline and then set manually, and does not directly participate in production control.

[0007] (5) Various process mathematical models cannot be effectively integrated, are relatively scattered, and do not consider the influence relationship between each other.

[0008] (6) Dynamic control parameters in the production process need to be determined manually. Summary of the Invention

[0009] In order to solve the above problems, the present invention proposes a method and system for dynamically controlling an industrial production process.

[0010] The specific solutions are as follows:

[0011] A method for dynamically controlling an industrial production process includes the following steps:

[0012] S1: Construct different meta-operation units according to different process operations in the industrial production process, and store all the meta-operation units in a meta-operation library;

[0013] S2: According to the different types of industrial production products, select a production control process composed of multiple meta-operation units that meet the industrial production operation process of the corresponding type of industrial production products from the meta-operation library, and configure the execution timing and static control parameters of each step in the production control process;

[0014] S3: Construct an end-state prediction model according to the production control process;

[0015] S4: Receive the status information of the incoming industrial production raw materials, and calculate the dynamic control parameters according to the status information of the industrial production raw materials;

[0016] S5: Send the production control process to the industrial production control device;

[0017] S6: The industrial production control device performs industrial production according to the production control process, and during the production process, it monitors in real time whether the industrial production enters the dynamic control step. If it enters the dynamic control step, based on the dynamic control input corresponding to this dynamic control step, it predicts the end state after all steps executed according to the production control process based on this dynamic control input through the end state prediction model, determines whether the end state meets the requirements. If so, it enters the monitoring of the next dynamic control step; otherwise, it adjusts the dynamic control parameters included in all steps after this dynamic control step, and predicts again through the end state prediction model the end state after all steps executed according to the production control process based on this dynamic control input until the end state meets the requirements and then enters the monitoring of the next dynamic control step;

[0018] S7: When all steps in the production control process are completed, compare and analyze the target state of the industrial production product with the actual end state after all steps in the production control process are completed, and optimize the correlation coefficients used to calculate the dynamic control parameters according to the comparison result.

[0019] Furthermore, the attributes of the meta-operation unit include the identifier of whether to perform dynamic control, the control target, and the dynamic control input.

[0020] Furthermore, the industrial production control process is molten steel smelting, and the industrial production raw material is molten steel.

[0021] Furthermore, the types of the state prediction model include the temperature prediction model and the composition prediction model.

[0022] Furthermore, the state information of the molten steel includes: the initial composition, initial temperature, initial oxygen, initial weight, target composition, and target temperature of the molten steel.

[0023] Furthermore, the condition for executing the next step in the industrial production of step S6 is: when the static control parameters and dynamic control parameters are met during the execution of the previous step, and the execution duration of the step meets the execution time sequence corresponding to the previous step, enter the next step.

[0024] An industrial production process dynamic control system, characterized in that: it includes a terminal device and an industrial production control device, and the terminal device is communicatively connected to the industrial production control device; the system implements the steps in the method described in the embodiments of the present invention.

[0025] Adopting the above technical solution, the present invention can realize the dynamic adjustment of the dynamic control parameters in the production control process as the steps proceed, and can avoid the impact of problems suddenly occurring in the intermediate process of the actual production process on the overall production. Description of the Drawings

[0026] Figure 1 The figure shows a flowchart of the first embodiment of the present invention.

[0027] Figure 2 The figure shows a schematic diagram of the configuration interface of the meta-operation unit in this embodiment.

[0028] Figure 3 The figure shows a schematic diagram of the production control process configuration interface in this embodiment.

[0029] Figure 4 The figure shows a schematic diagram of the display interface of the execution timing, static control parameters, and dynamic control parameters in the production control process of this embodiment. Detailed implementation manners

[0030] To further illustrate each embodiment, the present invention provides accompanying drawings. These drawings are part of the disclosure of the present invention, mainly used to illustrate the embodiments, and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those of ordinary skill in the art should be able to understand other possible implementation manners and the advantages of the present invention.

[0031] Now, the present invention will be further described in conjunction with the accompanying drawings and specific implementation manners.

[0032] Embodiment 1:

[0033] The embodiment of the present invention provides an industrial production process dynamic control method. As Figure 1 shown, the method includes the following steps:

[0034] S1: Construct different meta-operation units according to different process operations in the industrial production process, and store all the meta-operation units in the meta-operation library.

[0035] In the construction of the meta-operation unit, it is necessary to configure each attribute of the meta-operation unit. Each attribute includes two types: basic attributes and control attributes. The basic attributes are used to identify the situation of the meta-operation unit, including: name, execution code, etc. in this embodiment. The control attributes are used to identify the process use and control object corresponding to the meta-operation unit, including: the identifier of whether dynamic control is performed, control target, and dynamic control input in this embodiment.

[0036] In this embodiment, the industrial production process is illustrated by taking the molten steel smelting process as an example. In other embodiments, the industrial production process can also be the production process of other types of industrial production raw materials, which is not limited herein.

[0037] As Figure 2The figure shows a schematic diagram of the configuration interface of the meta-operation unit in this embodiment. For example, in the OPERATION_TYPE field, a flag indicating whether dynamic control is performed is stored. 1 represents a dynamic control step, and 0 represents a non-dynamic control step; in the OPERATION_ADJUST_ELEMENT field, the control target is stored. AL indicates that the control target for aluminum composition control is aluminum, and MN indicates that the control target for manganese composition control is manganese; in the OPERATION_CONTROL_INPUT field, the dynamic control input is stored. O indicates that the input for aluminum composition control is oxygen determination, and L indicates that the input for manganese composition control is the molten steel inspection composition.

[0038] S2: According to the different types of industrial production products, select a production control process composed of multiple meta-operation units that meet the industrial production operation process of the corresponding type of industrial production products from the meta-operation library, and configure the execution timing and static control parameters of each step in the production control process.

[0039] As Figure 3 shown, on the left is the meta-operation library. After selecting meta-operation units from the meta-operation library and adding them to the right, and setting the sequence between different meta-operation units, a production control process corresponding to the molten steel smelting process is obtained. Each step in the production control process corresponds to a meta-operation unit.

[0040] After configuring the production control process, it is also necessary to make the execution of each step the same as the execution timing and execution environment in the actual production process. Therefore, it is also necessary to configure the execution timing and static control parameters of each step in the production control process. As Figure 4 shown, in this embodiment, the execution timing is the duration of each step; the static control parameters are fixed and unchangeable parameters in the production process, which are only related to the type of steel grade, such as side blowing flow rate, bottom blowing flow rate, vacuum pump level, etc.

[0041] S3: Build an end state prediction model according to the production control process.

[0042] Since it is necessary to judge from two aspects whether the molten steel finally obtained in the production control process of the molten steel smelting process meets the requirements, one aspect is temperature, and the other aspect is composition. Therefore, there are two types of state prediction models in this embodiment, namely temperature prediction model and composition prediction model.

[0043] The prediction result of the end prediction model is the final state (final temperature and final composition) obtained after executing according to the input parameters according to the production control process.

[0044] S4: Receive the state information of the incoming industrial production raw materials, and calculate the dynamic control parameters according to the state information of the industrial production raw materials.

[0045] When the industrial production raw material is molten steel in this embodiment, the corresponding state information includes: the initial composition, initial temperature, initial oxygen, initial weight, target composition, and target temperature of the molten steel. After the molten steel enters the station, its state information can be extracted.

[0046] Dynamic control parameters are parameters that need to be adjusted according to the situation during the production process. For example, the dynamic control parameter for the aluminum content control step in the composition is the input aluminum content (AL), and the dynamic control parameter for the manganese content control in the composition is the input manganese content (medium-carbon ferromanganese from the 8th feed port, indicating medium-carbon ferromanganese input from the 8th feed port), which is calculated based on the state information of the industrial production raw material.

[0047] The dynamic control parameters are calculated based on the state information of the industrial production raw material. Those skilled in the art can obtain the specific calculation model using existing calculation methods and are not limited herein.

[0048] S5: Send the production control process to the industrial production control device.

[0049] S6: The industrial production control device executes industrial production according to the production control process and monitors in real time during the production process whether the industrial production enters the dynamic control step. If it enters the dynamic control step, based on the dynamic control input corresponding to this dynamic control step, predict the end state after all steps executed according to the production control process based on this dynamic control input through the end state prediction model, and determine whether the end state meets the requirements. If so, enter the monitoring of the next dynamic control step; otherwise, adjust the dynamic control parameters included in all steps after this dynamic control step, and re-predict the end state after all steps executed according to the production control process based on this dynamic control input through the end state prediction model until the end state meets the requirements and then enter the monitoring of the next dynamic control step.

[0050] The end prediction model can predict different end states according to different dynamic control inputs and different dynamic control parameters included in all steps below the dynamic control step.

[0051] When the industrial production control device executes industrial production according to the production control process, it usually executes according to the sequence of each step configured in the production control process, the execution timing of each step, static control parameters, and dynamic control parameters. However, in step S4 of this embodiment, the dynamic control parameters are continuously adjusted according to the execution sequence of the steps. For example, if the 3rd step is a dynamic control step, then all dynamic control parameters after the 3rd step (the 4th and 6th steps) are adjusted. After that, if the 5th step is a dynamic control step, then only all dynamic control parameters after the 5th step (the 6th step) are adjusted again, and the dynamic control parameters before the 5th step (the 4th step) are no longer adjusted.

[0052] In this embodiment, the condition for executing the next step in the production control process in industrial production is set as follows: when the static control parameters and dynamic control parameters are met during the execution of the previous step, and the execution duration of the step meets the execution timing corresponding to the previous step, proceed to the next step.

[0053] S7: When all steps in the production control process are completed, the target state of the industrial product is compared with the actual end state after all steps in the production control process are completed, and the correlation coefficient used to calculate the dynamic control parameters is optimized according to the comparison result.

[0054] Since the calculation model for calculating the dynamic control parameters has a correlation coefficient, when the comparison analysis results are inconsistent, it means that the correlation coefficient in the calculation model for calculating the dynamic control parameters is not accurately set, and it needs to be optimized and adjusted.

[0055] The embodiments of the present invention can realize the standardization of industrial production control processes, replace the existing manual or semi-automatic operation modes, and enable the industrial production process to be carried out according to the configured production control process, which can reduce labor quotas, improve production efficiency, and realize dynamic adjustment of dynamic control parameters in the production control process as the steps proceed, thereby avoiding the impact of sudden problems in the intermediate process during the actual production process on the overall production.

[0056] Embodiment 2:

[0057] The present invention also provides an industrial production process dynamic control system, characterized in that it includes terminal equipment and industrial production control equipment, and the terminal equipment and the industrial production control equipment are communicatively connected; the system implements the steps in the above-mentioned method embodiment of embodiment 1 of the present invention.

[0058] Although the present invention has been specifically shown and described in conjunction with the preferred embodiments, it should be understood by those skilled in the art that various changes may be made to the present invention in form and details without departing from the spirit and scope of the present invention as defined by the appended claims, all of which are within the scope of protection of the present invention.

Claims

1. A method for dynamically controlling an industrial production process, characterized in that, It includes the following steps: S1: Construct different meta-operation units according to different process operations in the industrial production process, and store all the meta-operation units in the meta-operation library; the attributes of the meta-operation units include the identification of whether to perform dynamic control, control objectives, and dynamic control inputs; S2: According to different types of industrial production products, select a production control process composed of multiple meta-operation units that meet the industrial production operation process of the corresponding type of industrial production products from the meta-operation library, and configure the execution timing and static control parameters of each step in the production control process; S3: Construct an end-state prediction model according to the production control process; S4: Receive the state information of the incoming industrial production raw materials, and calculate the dynamic control parameters according to the state information of the industrial production raw materials; S5: Send the production control process to the industrial production control equipment; S6: The industrial production control equipment performs industrial production according to the production control process, and in the production process, it monitors in real time whether the industrial production enters the dynamic control step. If it enters the dynamic control step, according to the dynamic control input corresponding to this dynamic control step, through the end-state prediction model, predict the end state after all steps are executed according to the production control process based on this dynamic control input. Judge whether the end state meets the requirements. If so, enter the monitoring of the next dynamic control step; otherwise, adjust the dynamic control parameters included in all steps after this dynamic control step, and re-predict the end state after all steps are executed according to the production control process based on this dynamic control input through the end-state prediction model until the end state meets the requirements and then enter the monitoring of the next dynamic control step; S7: When all steps in the production control process are executed, compare and analyze the target state of the industrial production product with the actual end state after all steps in the production control process are executed, and optimize the correlation coefficient used to calculate the dynamic control parameters according to the comparison result.

2. The dynamic control method for industrial production processes according to claim 1, wherein: The industrial production control process is molten steel smelting, and the industrial production raw material is molten steel.

3. The dynamic control method for industrial production processes according to claim 2, wherein: The types of the state prediction model include a temperature prediction model and a composition prediction model.

4. The dynamic control method for industrial production processes according to claim 2, wherein: The state information of the molten steel includes: the initial composition, initial temperature, initial oxygen, initial weight, target composition, and target temperature of the molten steel.

5. The dynamic control method for industrial production processes according to claim 1, characterized in that: The condition for executing the next step in the industrial production of step S6 is: when the previous step is executed, it meets the static control parameters and dynamic control parameters, and the execution duration of the step meets the execution timing corresponding to the previous step, then enter the next step.

6. An industrial production process dynamic control system, characterized in that: It includes a terminal device and an industrial production control device, and the terminal device is communicatively connected to the industrial production control device; the system implements the steps of the method described in any one of claims 1 to 5.

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