Intelligent steel factory based on AI technology and construction method thereof

Abstract

The invention belongs to the technical field of intelligent factories, and particularly relates to an AI technology-based intelligent steel factory and a construction method thereof. The construction method comprises the steps that industrial robots are arranged in a raw material area, an area before iron making, a steelmaking area, a steel rolling area, a finishing operation area and an inspection and test area of a steel factory; performing unified standardization and quantification on related factors compiled by the production plan to form a factor library and a material type library; setting an optimization control system of various specific business targets; constructing an intelligent database of the steel factory, namely summarizing data information in the whole range of the steel factory into the intelligent database of the steel factory; establishing a production operation management and control platform based on an AI technology, and performing data extraction, cleaning and classified storage on the intelligent database of the steel factory; and intelligent personnel and material scheduling is carried out according to the production operation management and control platform. Through the application of the AI algorithm and in combination with the process standard, the plan yield and the plan making efficiency are improved, the application of the control model is optimized, and the quality consistency management and control is promoted.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart factories, and specifically relates to an AI-based smart steel factory and a construction method thereof. Background Art

[0002] The steel industry is leveraging technologies like the Industrial Internet and AI to improve production efficiency and green practices, meeting market demand for high-quality, customized steel. However, this initiative faces multiple challenges: The difficulty integrating legacy equipment with new technologies leads to data silos; complex processes and high-temperature environments hinder intelligent application; high transformation costs and long payback periods burden businesses; and there is a shortage of interdisciplinary talent with both process and digital skills. Deep integration of AI technology with the steel industry is urgently needed to overcome these bottlenecks.

[0003] The steel industry has long processes, multiple links, long cycles, and complex techniques. There are many problems in smart operation management and control and intelligent manufacturing, and there is great potential for growth. However, existing smart factories have the following shortcomings:

[0004] 1. Difficulty in multi-process collaboration: The process is long and multi-step (raw materials → ironmaking → steelmaking → rolling → deep processing). Each process is highly independent and data silos are common, making it difficult to achieve dynamic optimization and real-time collaboration across the entire process.

[0005] 2. Complex quality control: Steel performance is significantly affected by process parameters (temperature, pressure, composition, etc.), requiring cross-process data traceability. Traditional manual sampling is inefficient and difficult to cover the entire process.

[0006] 3. Insufficient data integration and standardization: Equipment heterogeneity is high (old blast furnaces coexist with new sensors), data protocols are not unified, and real-time data collection and analysis capabilities are weak;

[0007] 4. Difficulty in implementing model applications: Due to the complexity of process mechanisms, AI models (such as predictive maintenance and intelligent scheduling) need to be deeply integrated with industry experience, but there is a lack of cross-disciplinary and multidisciplinary talent.

[0008] 5. Low level of equipment intelligence: Traditional equipment accounts for a high proportion, sensor coverage is insufficient, and key process parameters rely on manual experience, making precise control difficult to achieve. Summary of the Invention

[0009] The purpose of the present invention is to overcome the defects of the existing technology that multiple processes are difficult to coordinate and rely on manual parameter experience, and to provide an AI-based steel smart factory with multi-field collaboration based on materials as the main line and integration of various levels, as well as its construction method.

[0010] The technical solution adopted by the present invention to solve its technical problem is:

[0011] First aspect, a construction method for an intelligent steel plant based on AI technology, including the following:

[0012] Set industrial robots in the raw material area, front-of-iron area, steelmaking area, rolling area, finishing operation, and inspection and testing area of the steel plant;

[0013] Unify and standardize and quantify the relevant factors for production plan compilation to form a factor library and a material type library;

[0014] Set optimization control systems for multiple specific business objectives;

[0015] Construct an intelligent database for the steel plant, that is, summarize the data information within the entire scope of the steel plant into an intelligent database for the steel plant;

[0016] Establish a production operation and management and control platform based on AI technology, and perform data extraction, cleaning, and classified storage on the intelligent database of the steel plant;

[0017] Perform intelligent scheduling of personnel and materials according to the production operation and management and control platform.

[0018] Specifically, the unifying, standardizing, and quantifying the relevant factors for production plan compilation includes:

[0019] Obtain the relevant factors for production plan compilation, and the relevant factors include order delivery date requirements, steelmaking production requirements, steel grades, and steel dimensions;

[0020] Set the unified format for the relevant factors according to the type;

[0021] Use a combination algorithm to combine and quantify the relevant factors in the unified format, and save them to the factor library and the material type library.

[0022] Specifically, the optimization control model includes at least one of an LF alloy feeding intelligent optimization system, a slab quality optimization control system, a heating furnace temperature optimization control system, and a rolling process simulation and auxiliary optimization system.

[0023] Specifically, the classification of data stored in the production operation and management and control platform includes one or more of a quality management module, a data security and compliance module, a data standard and classification module, a data life cycle management module, and a metadata management module.

[0024] Specifically, the intelligent scheduling of personnel and materials according to the production operation and management and control platform includes the following:

[0025] Manually search for real-time information of personnel and materials through the production operation and management and control platform;

[0026] Through the feedback information of the production operation and management and control platform, perform the transfer of personnel and / or materials.

[0027] The second aspect is a smart steel factory based on AI technology, which is constructed using any of the construction methods described above.

[0028] Specifically, an AI-based smart steel factory includes:

[0029] At least one steel production workshop for the production of steel products;

[0030] Production monitoring platform, used to monitor production data, material data, personnel data, and equipment operation data in steel production workshops;

[0031] Storage silos, used to store steel raw materials and produced steel products;

[0032] Warehouse management platform, used to monitor and update the data information in the storage warehouse in real time;

[0033] Logistics module, which includes logistics equipment, logistics identification unit, logistics scheduling unit and logistics management platform;

[0034] The AI production operation management and control platform collects data information from the production monitoring platform, warehouse management platform, and logistics management platform, and serves as a search portal for managers.

[0035] Specifically, it also includes an energy operation management platform for real-time monitoring of energy information of multiple steel production workshops.

[0036] Specifically, it also includes a business analysis module for performing real-time data analysis on the steel production workshop and monitoring the business performance of any steel workshop in real time.

[0037] Specifically, the AI production operation management and control platform includes a production and manufacturing management module, a warehousing and logistics management module, a quality control management module, an equipment operation management module, and an energy operation management module.

[0038] The beneficial effects of the AI-based steel smart factory and its construction method of the present invention are:

[0039] This invention takes business performance as the main line, focusing on production planning, manufacturing process control, quality control, energy scheduling, and data governance. The distributed application of industrial robots on the production line works in collaboration with the main equipment to reduce manual operations and reduce fluctuations. At the same time, a production planning factor library and a material type library are established. Through the application of AI algorithms and combined with process standards, intelligent production scheduling of production plans is realized, the planned yield rate is improved, and the efficiency of plan preparation is improved. The application of optimized control models is improved to improve the level of intelligent optimization control of special operation scenarios, improve operation efficiency, and promote consistent quality control.

[0040] Moreover, the intelligent steel factory of the present invention realizes efficient data management through a production operation control platform based on AI technology, laying a data foundation for business performance management and data-driven business improvement. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0042] Figure 1 It is a flowchart of a method for constructing an intelligent factory according to an embodiment of the present invention.

[0043] Figure 2 It is a distribution map of robots according to an embodiment of the present invention.

[0044] Figure 3 It is a framework diagram of an intelligent factory according to an embodiment of the present invention.

[0045] Figure 4 It is a framework diagram of an AI production operation control platform according to an embodiment of the present invention.

[0046] Figure 5 It is a screenshot of the software interface of an AI production operation control platform according to an embodiment of the present invention.

[0047] In the figure: 1, steel production workshop; 2, production monitoring platform; 3, storage bin; 4, warehousing management platform; 5, logistics module; 6, AI production operation control platform. SPECIFIC EMBODIMENTS

[0048] The present invention will now be further described in detail with reference to the drawings. These drawings are all simplified schematic diagrams, only illustrating the basic structure of the present invention in a schematic manner, and therefore only showing the components related to the present invention.

[0049] As Figures 1 - 5 shown in a specific embodiment of a method for constructing an intelligent steel factory based on AI technology of the present invention, specifically refer to Figure 1 , and includes the following steps:

[0050] S10: Set industrial robots in the raw material area, front of iron area, steelmaking area, rolling area, finishing operation area, and inspection and testing area of the steel factory;

[0051] S20: Standardize and quantify the relevant factors for production plan preparation to form a factor library and a material type library;

[0052] S30: Set optimization control systems for multiple specific business objectives;

[0053] S40: Construct an intelligent database for the steel factory, that is, summarize the data information within the entire scope of the steel factory into an intelligent database for the steel factory;

[0054] S50: Establishing a production operation management and control platform based on AI technology to extract, clean, and classify and store data in the steel plant intelligent database;

[0055] S60: Intelligent scheduling of personnel and materials based on the production operation control platform.

[0056] This invention takes business performance as the main line, focusing on production planning, manufacturing process control, quality control, energy scheduling, and data governance. The distributed application of industrial robots on the production line works in collaboration with the main equipment to reduce manual operations and reduce fluctuations. At the same time, a production planning factor library and a material type library are established. Through the application of AI algorithms and combined with process standards, intelligent production scheduling of production plans is realized, the planned yield rate is improved, and the efficiency of plan preparation is improved. The application of optimized control models is improved to improve the level of intelligent optimization control of special operation scenarios, improve operation efficiency, and promote consistent quality control.

[0057] like Figure 2 As shown, scenario-based industrial robot applications primarily assist human intervention in the production process, improving the accuracy and stability of process control and freeing humans from arduous or unsafe working environments. From the perspective of material flow and process quality control throughout the steel industry, industrial robots are primarily used in the following areas: 1) Raw material area: sampling raw materials and measuring stockpiles; 2) Ironmaking area: automated taphole filling at the furnace, automated oiling of sintering trolleys, inspections, and unmanned overhead cranes; 3) Steelmaking area: temperature measurement and sampling, addition of covering agents, addition of mold slag for continuous casting, low-magnification inspection, and billet identification; 4) Rolling area: billet identification, automated sampling, and material identification; 5) Finishing: automated unbundling, loading, chamfering, spot grinding, and painting; 6) Inspection and testing area: sample preparation and processing, as well as impact, tensile, hardness, and bending tests. The application process of industrial robots needs to be deeply integrated with the scene. First, appropriate design should be made based on the production rhythm. Secondly, necessary protective measures should be taken in terms of stability and safety, such as anti-shake and anti-collision, obstacle avoidance, temperature control, etc.

[0058] Specifically, the unified standardization and quantification of the relevant factors of production planning include:

[0059] S201: Obtain relevant factors for production planning, wherein the relevant factors include order delivery requirements, steelmaking production requirements, steel type, and steel size;

[0060] S202: Setting the relevant factors in a unified format according to their types;

[0061] S203: Utilize a combination algorithm to combine and quantify the relevant factors in a unified format, and save them in a factor library and a material type library.

[0062] Based on order-based production, we standardize and quantify the factors influencing production planning, creating a production planning factor library and a material profile library. Based on factors such as order delivery dates and steelmaking production requirements, we apply intelligent algorithms to assist in production planning, improve planning efficiency and intelligence, reduce excess billets and materials, and increase yield rates. This factor library includes, but is not limited to, the number of continuous casting furnaces, molten steel yield, continuous casting steel grade groups, yield rate, head and tail trimming, and edge trimming.

[0063] The optimization control model in this embodiment includes at least one of the LF alloy feeding intelligent optimization system, the slab quality optimization control system, the heating furnace temperature optimization control system, and the rolling process simulation assisted optimization system. In a specific scenario, an optimization control model is implemented to achieve a specific business goal. Through a series of AI technologies such as algorithms and models, massive historical sample data are analyzed and modeled, and through simulation verification, a dedicated optimization control model is formed to guide the production process control to be more optimized and intelligent. Dedicated optimization control models include but are not limited to: 1) LF alloy feeding intelligent optimization system; 2) slab quality optimization control system; 3) heating furnace temperature optimization control system; 4) rolling process simulation assisted optimization.

[0064] Among them, the classification of data stored in the production operation control platform in this embodiment includes one or more of a quality management module, a data security and compliance module, a data standard and classification module, a data lifecycle management module, and a metadata management module.

[0065] Establish a unified data center platform to extract data from various business systems, cleanse, classify, and store it, providing high-quality business data support for data analysis and application. A production and operations management platform generally includes data quality management, data security and compliance, data standards and classification, data lifecycle management, and metadata management.

[0066] like Figure 3 As shown, the steel smart factory constructed using the above construction method includes:

[0067] At least one steel production workshop 1, used for producing steel products;

[0068] Production monitoring platform 2, used to monitor the production data, material data, personnel data and equipment operation data of the steel production workshop;

[0069] Storage silo 3, used to store steel raw materials and produced steel products;

[0070] Warehouse management platform 4, used for real-time monitoring and updating of data information in the storage warehouse;

[0071] Logistics module 5, the logistics module includes logistics equipment, a logistics identification unit, a logistics scheduling unit, and a logistics management platform 51;

[0072] AI production operation control platform 6, the AI production operation control platform 6 collects the data information of the production monitoring platform 2, the warehouse management platform 4, and the logistics management platform 51, and serves as the search entry for the manager.

[0073] As Figure 3 and Figure 4 shown, it should be further noted that this intelligent factory also includes an energy operation management platform for real-time monitoring of the energy information of multiple steel production workshops. Conduct an overall systematic assessment and diagnosis in the energy field, and based on the main energy flow context of intake - production - consumption, provide appropriate energy supply for relevant fields such as production, maximize energy waste reduction, and improve the comprehensive energy utilization rate. Apply AI algorithms, analyze using the accumulated energy consumption data, decompose and deeply analyze the corresponding indicators, and provide a starting point and quantitative data support for energy conservation and consumption reduction work.

[0074] As Figure 5 shown, this intelligent factory also includes a business analysis module for real-time parsing and analysis of the data of the steel production workshop, and real-time monitoring of the business performance of any steel workshop. The AI production operation control platform includes a production manufacturing management module, a warehousing and logistics management module, a quality control management module, an equipment operation management module, and an energy operation management module.

[0075] Based on the scenario-based industrial robot application planning and design for the efficient operation of the entire production line, reduce human intervention, reduce fluctuations, and make the process control more precise and intelligent. Apply AI algorithms, compile a comprehensive production plan based on the factor library and material type library, which is more efficient and intelligent. Based on the optimization control model of AI technology, integrate more production elements, train an optimization control model that fits the actual situation through historical data, promote the optimization of the special process control, and the quality consistency control. The application of the production operation control platform promotes the improvement of data quality. Apply AI technology to standardize and normalize the data governance process, making the data governance process more efficient and intelligent. From the perspective of optimizing the operation of the energy flow, apply AI algorithms to decompose and deeply analyze the corresponding indicators, and provide a starting point and quantitative data support for energy conservation and consumption reduction work.

[0076] It should be understood that the specific embodiments described above are only used to explain the present invention and are not used to limit the present invention. Obvious changes or variations derived from the spirit of the present invention are still within the protection scope of the present invention.

Claims

1. A construction method for an intelligent steel plant based on AI technology, characterized in that, It includes the following: Industrial robots are set in the raw material area, pre - iron area, steelmaking area, rolling area, finishing operation area, inspection and testing area of the steel plant; The relevant factors for production plan preparation are unified, standardized and quantified to form a factor library and a material type library; Optimization control systems for multiple specific business objectives are set; An intelligent database for the steel plant is constructed, that is, the data information within the entire scope of the steel plant is summarized into the intelligent database of the steel plant; A production operation and management control platform based on AI technology is established, and data extraction, cleaning, classification and storage are performed on the intelligent database of the steel plant; Intelligent scheduling of personnel and materials is carried out according to the production operation and management control platform.

2. The construction method of an intelligent steel plant based on AI technology according to claim 1, characterized in that: The unifying, standardizing and quantifying the relevant factors for production plan preparation includes: Obtaining the relevant factors for production plan preparation, and the relevant factors include order delivery date requirements, steelmaking production requirements, steel grades, and steel dimensions; Setting the relevant factors in a unified format according to the type; Using a combination algorithm to combine and quantify the relevant factors in the unified format, and saving them to the factor library and the material type library.

3. The construction method of an intelligent steel plant based on AI technology according to claim 1, characterized in that: The optimization control model includes at least one of the LF alloy feeding intelligent optimization system, slab quality optimization control system, heating furnace temperature optimization control system, and rolling process simulation auxiliary optimization system.

4. A construction method of an intelligent steel plant based on AI technology according to claim 1, characterized in that: The classification of data stored in the production operation and management control platform includes one or more of the quality management module, data security and compliance module, data standard and classification module, data life cycle management module, and metadata management module.

5. The construction method of an intelligent steel plant based on AI technology according to claim 1, characterized in that: The intelligent scheduling of personnel and materials according to the production operation and management control platform includes the following: Manually search for real - time information of personnel and materials through the production operation and management control platform; Feedback information through the production operation and management control platform to carry out the transfer of personnel and / or materials.

6. An intelligent steel factory based on AI technology, characterized in that: It is constructed by using the construction method described in any one of claims 1 - 5.

7. An intelligent steel plant based on AI technology according to claim 6, characterized in that, It includes: At least one steel production workshop for producing steel products; At least one production monitoring platform for monitoring the production data, material data, personnel data and equipment operation data of the steel production workshop; A storage warehouse for placing steel raw materials and produced steel products; A warehousing management platform for real - time monitoring and updating the data information in the storage warehouse; A logistics module, and the logistics module includes logistics equipment, logistics identification unit, logistics scheduling unit and logistics management platform; An AI production operation and management control platform, which collects the data information of the production monitoring platform, warehousing management platform and logistics management platform, and serves as the search entrance for the manager.

8. The intelligent steel plant based on AI technology according to claim 6, wherein: It also includes an energy operation management platform for real - time monitoring of the energy information of multiple steel production workshops.

9. The intelligent steel plant based on AI technology according to claim 6, characterized in that: It also includes a business analysis module for real - time analysis and parsing of the data of the steel production workshop, and real - time monitoring of the business performance of any steel workshop.

10. The intelligent steel plant based on AI technology according to claim 6 is characterized in that: The AI production operation and management control platform includes a production manufacturing management module, a warehousing and logistics management module, a quality control management module, an equipment operation management module and an energy operation management module.

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