automation in steel industry
We provide a one-stop intelligent solutions for steelmaking/continuous casting / steel rolling
- Industry robot
- Visual Inspection System
- online measurement system
- Unmanned Crane System
We provide a one-stop intelligent solutions for steelmaking/continuous casting / steel rolling
Automaticly counting and separating for steel bars
Add mold powder evenly
Square Billet, Round Billet, Slab And Coil
For slitting and rolling production lines
With machine vision as the core, DBM can provide intelligent equipment R&D, manufacturing and transformation services such as unmanned factories in the metallurgical industry and other industries, machine vision, and robot application design.
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Widely used in rolling steel, cast pipe, cable, glass pipe, plastic pipe, rubber roller, machining, chemical industry, food and many other fields, and has been well received by users.
Compared with traditional metallurgical technology, the development advantages of iron and steel intelligent metallurgy technology have the following development advantages:
Intelligent iron and steel metallurgy technology can effectively reduce production costs and improve production efficiency through digital, intelligent and automated production methods.
The digital and intelligent production method can monitor and analyze the production process in real-time, so as to improve the stability and reliability of production quality.
Intelligent technology can accurately control key parameters such as temperature, pressure, and oxygen content in the production process, thereby reducing energy waste and emissions of waste gas, wastewater and other pollutants.
Intelligent technology can realize real-time monitoring and control of the production process and can detect equipment failures or abnormal conditions in time, thereby enhancing product safety.
The application of steel-intelligent metallurgical technology can promote the transformation of the traditional steel industry to digital, intelligent and green, and enhance the competitiveness and sustainability of the industry.
Intelligent technology can realize real-time monitoring and intelligent maintenance of steel equipment through sensors and data acquisition technology, reduce equipment failure, and improve production efficiency and equipment reliability.
In short, intelligent steel metallurgical technology can bring more efficient, more environmentally friendly, safer, and more reliable production methods, providing a broad space and opportunity for the sustainable development of iron and steel enterprises.
Eight AI application scenarios commonly used in the steel industry
Aiming at many difficulties and pain points in iron and steel metallurgical production, the artificial intelligence image recognition technology is closely combined with knowledge in the iron and steel field, and professional industrial cameras and visual intelligence algorithms are used to replace “human eyes” and “human brains”. Free skilled workers from those “3D” jobs (dirty, tiring, dangerous, dangerous, poor working environment, simple repetitive jobs) and boring “staring at the screen” work, Change the way of working, improve work efficiency, and further promote the reduction of staff and efficiency of iron and steel enterprises.
For example, the conventional counting system in the bar production line generally has problems such as weak anti-interference ability, inaccurate counting results, high failure rate, and difficulty in manual review after the steel is divided into bundles. These problems largely limit the entire steel rolling production line. The intelligence level and quality control level of the line.
The intelligent bar counting system adopts intelligent stereo vision technology, which overcomes the pain points of the industry, and can meet the application requirements of counting and volume measurement of various wire rods and pipes.
The original manual counting machine is cumbersome, but the visual AI perception can “one-click counting”, and the visual analysis is triggered in linkage, and the analysis results are verified with the weighing count and the quantity of the manifest.
If there is a discrepancy between the number of counts and the weight information, go offline to the waiting area.
The main implementation methods of artificial intelligence in equipment failure prediction and health management are as follows:
(1) Effective combination of AI technology and machine vision;
(2) Obtain a cost-effective forecasting scheme;
(3) Abundant fault data and labels.
On the one hand, equipment operation and maintenance based on artificial intelligence technology can predict equipment failures before accidents and reduce unplanned downtime.
On the other hand, in the face of sudden equipment failures, it can quickly diagnose the failure, locate the cause of the failure and provide corresponding solutions.
The application of surface defect detection based on machine vision has become more common in the manufacturing industry.
The combination of machine vision and 3D camera is applied to the steel industry.
It can not only detect product surface quality defects but also the depth information of defects.
For example, there are many types of defects such as surface scratches, cracks, pits, and foreign matter intrusion in the production process of continuous casting slabs in steelmaking plants.
After adopting the visual automatic detection of surface defects, through setting the minimum value and maximum value of the area and size, the detection of pits on the surface of the slab and the detection of longitudinal cracks on the surface of the slab are carried out automatically.
By introducing 3D camera technology, longitudinal fissure depth information can be detected automatically.
Intelligent logistics in the iron and steel industry realize the rational allocation of logistics and transportation resources and the coordination of transportation instructions through the establishment of an integrated and collaborative logistics dispatching model through technical measures such as the integration of logistics information, automation of the parking area, vehicle tracking, and mobile applications, and the optimization of supporting management processes. Intelligent generation improves the efficiency of logistics and transportation.
Specifically, it includes billet automatic number spraying and furnace billet number automatic identification technology, conveying automation technology, packaging automation technology, automated warehouse (wireless positioning), intelligent delivery, etc. Goal: To achieve accurate measurement, weighing, positioning and tracking, automatic transportation of production materials, transportation tools, intermediate products and final products, accurate scheduling of materials, and consistency with financial settlement.
In terms of product quality, operation management, energy consumption management, and production planning management, iron and steel enterprises can apply artificial intelligence technologies such as machine learning, combined with big data analysis, optimize scheduling methods, and improve corporate decision-making capabilities.
The steelmaking intelligent management and control platform is a system platform for centralized management and control of production factors such as production planning, furnace machine matching, furnace machine production rhythm, production condition adjustment, process flow requirements, and abnormal state control. The system only needs one operation interface and one set of models, a command centre, and a production driving point, the whole process can be realized on time.
And it can build a just-in-time production model with automatic matching of multiple furnaces and multiple machines, automatic error correction, and efficiency priority to achieve scientific, efficient, accurate, and balanced production goals.
Digital twins are mirror images of objective things in the virtual world.
The process of creating a digital twin integrates artificial intelligence, machine learning, and sensor data to build a “real” model that can be updated in real-time and has a strong sense of presence to support decision-making in various activities in the physical product life cycle.
By making full use of the automatic control mechanism model, machine learning model and process simulation model, the digital twin system adopts various sensing technologies of sound, light, electricity, magnetism and heat, and is based on the industrial Internet platform and big data. Based on the theory of physical quantity, multi-scale, and multi-probability, create a parallel continuous casting production site with a one-to-one mapping between virtual and reality, and realize virtual evaluation of continuous casting production, digital process simulation, and three-dimensional immersive operation guidance, etc.
Employees can easily understand the dispatching situation of the continuous casting regional logistics through the overall interface, and dispatch and command the on-site equipment in a timely manner according to the actual production situation.
Using technologies such as cloud computing, big data, Internet of Things, machine vision, intelligent algorithms, 5G, BIM, etc., through the management of safety regulations in all aspects of the enterprise, production and operation monitoring and early warning, resource management and accident investigation, special equipment monitoring and other systems, it can Realize comprehensive monitoring of the site, provide guarantee for all-around production safety management, and feedback the collected information to the platform for multi-dimensional statistical analysis to form timely, effective, accurate and complete engineering big data, real-time, Comprehensively and accurately grasp the situation of the production site, and realize green, digital, refined and intelligent safety management.
Through the analysis of external data, an accurate demand forecasting model is established, and based on demand forecasting, inventory replenishment strategies are formulated, as well as supplier evaluation and procurement strategy optimization.
Purchasing department should carry out personalized procurement according to the customer’s demand for steel, formulate a corresponding raw material procurement plan, choose suppliers reasonably, ensure the required materials, and supply them in time.
Iron and steel raw material suppliers often have to go through long-distance transportation to iron and steel enterprises, especially raw materials such as imported iron ore and scrap steel, and take precautions against various risks.
Under the premise of ensuring the continuous production of steel, artificial intelligence data analysis can provide data for the procurement department, optimize procurement strategies, and directly or indirectly reduce procurement costs.
(1) Rod and wire branch factory, hot rolling, and plate online quality monitoring system, etc.
It has realized product quality tracking and control; scrap steel identification projects, surface quality inspection projects, etc., and has broken through the performance prediction of steel products in a single process section and the structure and performance prediction of steel plates based on big data.
(2) Patrol robots, robots for automatic clay change, tuyere inspection robots, number spraying robots, slag adding robots, welding mark robots, etc. realize the detection of dangerous areas and personnel dangerous behaviors through environmental perception, personnel behavior recognition, and personnel location tracking. control, replacing a series of manual operations.
(3) Smart coking, smart blast furnace, smart two-cutting, etc. use technologies such as online detection, smart diagnosis, and smart image recognition to realize predictive maintenance and full life cycle management of equipment.
(4) The unmanned overhead crane in the hot-rolled finished product warehouse and the unmanned overhead crane in the dry coal shed use mobile communication technology and positioning application technology to realize the mobile scheduling and intelligent scheduling of storage materials; use the Internet of Things sensing technology to realize the fixed positioning of storage materials, Speed up material turnover.
