Potential of Applying Artificial Intelligence to Hot Metal Logistics Management

The steel industry,known for its complexity and the need to reduce CO_(2)emissions,is adopting advanced digitalization tools to move towards a more sustainable,integrated,and agile operating model.Digital twins with artificial intelligence-based optimization and scheduling models can improve decision-making in logistics,refractory maintenance,and energy efficiency.By incorporating advanced AI algorithms into this decision support system,the hot metal route scenarios can be evaluated,resulting in minimized hot metal temperature losses and increased scrap utilization.This paper integrated digital twins with reinforcement learning algorithms to investigate the logistics of torpedoes and hot metal ladles.It considered important input parameters such as the ladles and torpedoes'thermal state and location,refractory thickness,hot metal volume and temperature,and crane availability.By incorporating advanced AI algorithms into this decision support system,energy-efficient scenarios can be evaluated,increasing scrap utilization and resulting in a possible reduction of 15°C in hot metal temperature losses.

Intelligent optimization method for the dynamic scheduling of hot metal ladles of one-ladle technology on ironmaking and steelmaking interface in steel plants

The one-ladle technology requires an efficient ironmaking and steelmaking interface. The scheduling of the hot metal ladle in the steel plant determines the overall operational efficiency of the interface. Considering the strong uncertainties of real-world production environments, this work studies the dynamic scheduling problem of hot metal ladles and develops a data-driven three-layer approach to solve this problem. A dynamic scheduling optimization model of the hot metal ladle operation with a minimum average turnover time as the optimization objective is also constructed. Furthermore, the intelligent perception of industrial scenes and autonomous identification of disturbances, adaptive configuration of dynamic scheduling strategies, and real-time adjustment of schedules can be realized. The upper layer generates a demand-oriented prescheduling scheme for hot metal ladles. The middle layer adaptively adjusts this scheme to obtain an executable schedule according to the actual supply–demand relationship. In the lower layer, three types of dynamic scheduling strategies are designed according to the characteristics of the dynamic disturbance in the model:real-time flexible fine-tuning, local machine adjustment, and global rescheduling. Case test using 24 h production data on a certain day during the system operation of a steel plant shows that the method and system can effectively reduce the fluctuation and operation time of the hot metal ladle and improve the stability of the ironmaking and steelmaking interface production rhythm. The data-driven dynamic scheduling strategy is feasible and effective, and the proposed method can improve the operation efficiency of hot metal ladles.

Chaotic Identification and Prediction of Silicon Content in Hot Metal

The time series data of silicon content in hot metal were identified to have the chaotic feature because of the positive maximum Lyapunov exponent, and then the time scales to predict future were estimated. Finally a chaotic local-region model was constructed to predict silicon content in hot metal with good performance due to high hitting rate.

Fuzzy Prediction of Silicon Content for BF Hot Metal

Some key operation variables influencing hot metal silicon content were selected, and time lag of each of them was obtained. A standardized fuzzy system model was developed to approach the random nonlinear dynamic system of the change of silicon content, forecast the change of silicon content and calculate silicon content. The prediction of hot metal silicon content is very successful with the data collected online from BF No. 1 at Laiwu Iron and Steel Group Co.

High Efficient Technology of Steelmaking With Low Silicon Hot Metal on Large Converter

To resolve the difficulty in slag formation during steelmaking with low silicon hot metal and to increase productivity, a new 5-hole lance was developed by increasing oxygen flow from 50 000 m^3/h to 60 000 m^3/h. Synthetic slag was added to adjust the slag composition. The problems such as difficulty in dephosphorization and slag adhesion to oxygen lance and hood were settled. Steel production and metal yield were increased and the nozzle life was prolonged through these techniques.

Vacuum Treatment for Simultaneous Desulphurization and Dephosphorization of Hot Metal and Molten Steel

The vacuum treatment for simultaneous desulphurization and dephosphorization of hot metal and molten steel with pre-melted CaO-based slag was carried out.For pre-treatment of hot metal,both desulphurization and dephosphorization are improved with the increase of CaO in slag,but deteriorated with the increase of CaF2 in slag.The average desulphurization and dephosphorization rate is 68.83 % and 78.46 %,respectively.For molten steel,the substitution of BaO for CaO in slag has minor effect on simultaneous desulphurization and dephosphorization.The desulphurization and dephosphorization rate is higher than 90% and 50% respectively with the lowest final sulfur and phosphorus mass percent being 0.001 2% and 0.010%,respectively.The overall effect of simultaneous desulphurization and dephosphorization of molten steel is better than that of hot metal.

Kinetic Factors for Intensive Reaction of Magnesium-Based Spheroidiser in Hot Metal

The spheroidiser is a necessary additive to manufacture ductile iron.Sometimes with the same hot metal,spheroidisers and treated technology,reactions differ greatly from each other.The reaction may be quite normal in one case,but very intensive for another one.The effects of kinetic factors such as size,surface area and morphology o f spheroidiser on the reaction of spheoidization are studied.

Investigation on Steelmaking with Hot Metal Containing Low Silicon Content in Large Converter

There are some problems in steelmaking with hot metal containing low silicon content such as difficulty in slag formation, less slag for dephosphorization and slag adhesion on oxygen lance and hood. To overcome these problems, experiments wcrc conducted and some improvements were obtained, such as adding appropriate flux, increasing the lance position slightly during steelmaking and using effective multi-outlet nozzle. Moreover, to keep normal heating rate, the ore and scrap charge should be reduced due to less chemical heat input in steelmaking.

Prospect of Refractory for Hot Metal Pretreatment

The paper describes the recent developing situation and the latest research achievements of refractory for hot metal pretreatment. The relationship among desiliconization, dephosphorization and desulphurization techniques and the main corrosion reactions by various treating agents is analyzed. Some improving measures for several problems in practice are put forward while we anticipate the future developing direction of refractory for hot metal pretreatment.

Eco-Friendly Smokeless Al_2O_3-SiC-C Brick for Hot Metal Ladle

Hot metal transfer ladles were historically lined with high alumina refractories because of compatibility of high alumina refractories with the highly acidic slag, which is transferred .from the iron making plant along with hot metal. With the introduction of higher capacity ladles, technological advancement in the process and increased productivity, calls for a higher campaign life of hot metal ladles, which could not be performed by ordinary high alumina refractories. Resin bonded Al2O3- SiC-C （hereinafter ASC ） bricks gradually developed which at present taking place replacing the conventional refractories. Considerable work has been carried out in developing the ASC refractory to reach the present state. However, for higher capacity ladles still there is a lot of scope for improvement. The present paper deals with the newly developed ASC bricks, which was used in 165 ton capacity hot metal ladles in one European plant and has given a substantial increase in performance. But, the customer was not fuUy satisfied since the brick was reported to produce smokes during preheating of the ladle. In the subsequent supply the smoke generation problem was taken care by adjusting the binders and additives and eco-friendly bricks were re-engineered and supplied to the same plant, which also performed splendidly and created all time record in their plant history.

Technical and economic analysis of Ni-containing hot metal production with laterite in blast furnaces

In recent years, many Ni-containing materials manufactured from laterite have played a significant role in supporting the rapid development of the stainless steel industry in China. Currently ,pyrometallurgy is the main process for laterite smelting, where blast furnaces are employed to make Ni-containing hot metal. With the aim of giving some references for making good use of laterite, technical and economic analysis was conducted in this paper, based on the discussion of the key technologies of Ni-containing hot metal production with laterite （50.4% Fe） in blast furnaces.

Al_2O_3-SiC-C Bricks for Hot Metal Pretreatment

1 Scope This standard specifies the classification, shape and dimensions, technical requirements, test methods, quality appraisal procedures, packing, marking, transportation, storage, and quality certificate of Al2O3- SiC - C bricks for hot metal pretreatment.

Al_2O_3-SiC-C Bricks for Hot Metal Pretreatment

1 Scope This standard specifies the classification, techni- cal requirements, test methods, inspection rules, packing, marking, transportation, storage and quality certificate of Al2O3- SiC - C bricks for hot metal pretreatment.

A Straightforward Mathematical Model of Hot Metal Desulphurization

A straightforward kinetic model for the hot metal desulphurization process is presented. The model contains some of the most important parameters and variables that govern the process. The inputs, outputs and parameters of a desulphurization program employed at industry are discussed. The model is able to cope with different injection policies of desulphurizers such as mono- injection, co-injection or multi-injection. When compared to the rotary impeller method, results of this model shows that the weight of lime consumed in the lance injection method is lesser than that consumed in the rotary impeller method for the same conditions of the hot metal charge.

Research on Wheel Rail Wear for a 140 t Open Type Hot Metal Car

To maintain the safety of an open-type hot-metal car and to reduce wheel-rail wear during transportation, simulation models of the main components of such car were built using Pro/E software and then tested. In particular, the Pro/E models were imported into ADAMS/Rail for assembly and then used to construct a complete hot-metal car dynamic model. Locomotive wheel-rail attack angle, wheel-rail lateral force, and wear index were used as evaluation parameters during the simulation to analyze the effects of bogie parameter, rail parameter, and speed of the hot-metal car on wheel-rail wear. An improvement scheme for reducing wheel-rail wear was proposed based on the result of the dynamic simulation, wherein wheel-rail wear and curving performance were analyzed and compared. The simulation provided an important reference for evaluating and improving the dynamic performance of the hot-metal car. The applied effect showed that the improvement scheme is effective.

Modeling and Simulation of Hot Metal Desulfurization by Powder Injection

The desulfurization of hot metal by the mono-injection of lime powder and the co-injection of lime, calcium carbide and magnesium powders is mathematically modeled. The mono-injection model is derived from the continuity equation and is validated using experimental results and data previously reported in the literature. The co-injection model and the rate constant of the injected mixture are determined from the molar fractions and rate constants of the individual powders. The effect of the lime content of the mixture on the desulfurization dynamics is studied and discussed.

Hot metal quality monitoring system based on big data and machine learning

The system of hot metal quality monitoring was established based on big data and machine learning using the real-time production data of a steel enterprise in China.A working method that combines big data technology with process theory was proposed for the characteristics of blast furnace production data.After the data have been comprehensively processed,the independent variables that affect the target parameters are selected by using the method of multivariate feature selection.The use of this method not only ensures the interpretability of the input variables,but also improves the accuracy of the machine learning process and is more easily accepted by enterprises.For timely guidance on production,specific evaluation rules are established for the key quality that affects the quality of hot metal on the basis of completed predictions work and uses computer technology to build a quality monitoring system for hot metal.The online results show that the hot metal quality monitoring system established by relying on big data and machine learning operates stably on site,and has good guiding significance for production.

Model of Hot Metal Silicon Content in Blast Furnace Based on Principal Component Analysis Application and Partial Least Square

In blast furnace （BF） iron-making process, the hot metal silicon content was usually used to measure the quality of hot metal and to reflect the thermal state of BF. Principal component analysis （PCA） and partial least- square （PLS） regression methods were used to predict the hot metal silicon content. Under the conditions of BF rela- tively stable situation, PCA and PLS regression models of hot metal silicon content utilizing data from Baotou Steel No. 6 BF were established, which provided the accuracy of 88.4% and 89.2%. PLS model used less variables and time than principal component analysis model, and it was simple to calculate. It is shown that the model gives good results and is helpful for practical production.

Cold Model Study on Mg Desulfurization of Hot Metal Under Mechanical Stirring

The new method of in-situ desulfurization with mechanical stirring of new type impellers was introduced, in which the bubble＇s dispersion and disintegration of magnesium vapor were the key to boosting the desulfurization efficiency and increasing the utilization rate of magnesium. Effects of different new type of impellers on bubble dis persion and disintegration were studied through bubble image analysis, gas-liquid mass transfer, and power con- sumption levels of different impeller structures. The results showed that the sloped swept-back blade impeller-2 pro- duces optimal bubble＇s dispersion and disintegration, as well as higher volumetric mass transfer coefficient and CO2 gas utilization while consuming the least power. Numerical simulation result with Fluent software also showed that the sloped swept-back blade impeller-2 has higher turbulent kinetic energy and better velocity distribution than the other two impellers.