Furnace Productivity Research Articles

Investigation of Formation and Shedding Behavior of Slag Crust in a Large Blast Furnace with Copper Stave: Flow Properties and Crystallization Characteristics

The damage of the copper stave will affect the sustainable production of the blast furnace and is not conducive to improving the economic efficiency of the blast furnace. The formation of a stable slag crust is crucial for the longevity of the copper stave. In this study, the flow properties and crystallization characteristics of the slag crust in a blast furnace with the copper stave running for 10 years without damage in China were analyzed. The phase precipitation during the cooling process was calculated by FactSage software. The phase composition and micromorphology of the slag crust were studied in detail by XRD and SEM–EDS. The results show that the slag phase in the slag crust is a CaO-SiO2-Al2O3-MgO-FeO slag system with high alumina content (33.62 ~ 35.72%) and low magnesium oxide content (2.68 ~ 3.84%). The melting characteristic temperature of the slag crust in the belly and the bosh is between 1127–1303 °C and 1287–1500 °C, respectively, and the characteristic temperature of the cold side of the slag crust is higher than that of the hot side, which was mainly resulted from the tendency of gehlenite and magnesia-aluminum spinel in the slag phase to precipitate during the cooling process. With the increase of the basicity of the slag phase, the precipitation temperature and amount of gehlenite increase, resulting in the characteristic temperature of the slag crust in the bosh significantly higher than that in the belly. The increase of FeO content reduces the initial precipitation temperature of crystals, and the increase of cooling strength is beneficial to the slagging on the copper stave, which provides a theoretical basis for the stable operation of the slag crust on copper stave blast furnace.

Can methane pyrolysis based hydrogen production lead to the decarbonisation of iron and steel industry?

Decarbonisation of the iron and steel industry would require the use of innovative low-carbon production technologies. Use of 100% hydrogen in a shaft furnace (SF) to reduce iron ore has the potential to reduce emissions from iron and steel production significantly. In this work, results from the techno-economic assessment of a H2-SF connected to an electric arc furnace(EAF) for steel production are presented under two scenarios. In the first scenario H2 is produced from molten metal methane pyrolysis in an electrically heated liquid metal bubble column reactor. Grid connected low-temperature alkaline electrolyser was considered for H2 production in the second scenario. In both cases, 59.25 kgH2 was required for the production of one ton of liquid steel (tls). The specific energy consumption (SEC) for the methane pyrolysis based system was found to be 5.16 MWh/tls. The system used 1.51 MWh/tls of electricity, and required 263 kg/tls of methane, corresponding to an energy consumption of 3.65 MWh/tls. The water electrolysis based system consumed 3.96 MWh/tls of electricity, at an electrolyser efficiency of 50 KWh/kgH2. Both systems have direct emissions of 129.4 kgCO2/tls. The indirect emissions are dependent on the source of natural gas, pellet making process and the grid-emission factor. Indirect emissions for the electrolysis based system could be negligible, if the electricity is generated from renewable energy sources. The levellized cost of production(LCOP) was found to be $631, and $669 respectively at a discount rate of 8%, for a plant-life of 20 years. The LCOP of a natural gas reforming based direct reduction steelmaking plant of operating under similar conditions was found to be $414. Uncertainty analysis was conducted for the NPV and IRR values.

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

Summary Given increased urgency to transition the global economy to net-zero CO2 emission, governments and industry have increased focus on decarbonizing hard-to-abate sectors, including steel making, which contributes roughly 6% of global CO2 emission and 8% of energy-related emission (including power consumption emission). This paper reviews current global iron and steel production and assesses available decarbonization technologies, including hydrogen injection, solid biomass substitution, zero-C electricity substitution, carbon capture and storage (CCS) retrofit, and combinations of these decarbonization approaches. Blast furnace-basic oxygen furnace (BF-BOF) dominates production (71%) and is particularly stubborn to any decarbonization technology. Direct reduced iron to electric arc furnace (DRI-EAF) production is 5% and growing, it appears to have better decarbonization potential to move toward net-zero. Secondary steel production using mainly steel scrap in electric arc furnace (EAF-scrap) is 24% of global production and has both the lowest energy consumption and is technically simplest to decarbonize through electrification but is limited in market share to recycled steel capacity. Of the options assessed, blue hydrogen, carbon neutral biomass, and CCS appear to have the lowest cost and highest technical maturity. However, no single approach today can deliver deep decarbonization to the iron and steel industry and all approaches lead to substantial production cost increase. No uniform ideal solution exists, and different geographies, infrastructure, and economies will determine the local optimum solution with viability and cost. Policy measures will be required to provide financial incentives for decarbonization and to avoid unwelcome outcomes such as emissions leakage or job loss.

Prediction of coke CSR using time series model in Coke Plant

Coke is raw material for blast furnace for production of hot metal. Good quality raw material produces low cost hot metal and one of the important quality parameter for blast furnace is Coke Strength after Reaction (CSR), as it refers to coke “hot” strength, generally a quality reference in a simulated reaction condition in an industrial blast furnace. In this research, the effects of coal properties and process parameters on the Coke CSR were studied by Time Series forecasting and artificial neural network models. In this method, historical data of last 3 years was used to estimate the CSR value. In this investigation, thirty-four input parameters such as moisture, volatile matter, ash, fluidity, battery temperature etc. were used. An Unobserved Component Model of Time Series was found to be optimum with nine parameters of coal properties and other process parameters with maximum accuracy of 76%, on the validation dataset respectively. The operating range of coal properties and controllable process parameters is derived from model developed to operate for consistent Coke CSR of 65.5% and above. The potential saving from this modelling initiative is INR 120 Million/USD 1.75 Million.

Energy intensification of steam methane reformer furnace in ammonia production by application of digital twin concept

ABSTRACT The Digital Twin concept undoubtedly emerges in different industries as a must-have option for improving energy efficiency, increase maintenance reliability, prevent environmental pollution, and mitigating safety issues. However, there is still no suitable solution specifically developed for continuous monitoring and optimisation of the complex process units such as steam methane reforming (SMR) furnace used in ammonia production. The current work addresses this problem with the main goal to save energy and reduce carbon footprint. The paper investigates the application of the Digital Twin concept in combination with already proven methods for the identification and optimisation of energy-saving opportunities and reduction of CO2 emissions. The results are total energy saving between 3 and 4% with CO2 reduction of approximately 0.890 tons/h.

Development of Dedusting Technology in the Silicon Production

The aim of this paper was to identify processes forming the largest amounts of dust and to develop and test additional methods for suppressing dust emissions into the air of the working area for the main occupations, primarily at the stage of loading ore raw materials into the ore-smelting furnace for the silicon production. Using the method for determining the specific surface area of fine materials - the Brunauer-Emmett-Teller (BET) method - it was shown that gas cleaning dust of the silicon production has a developed surface and high wetting ability, which makes it possible to recommend dust suppression methods using irrigation systems. In assessing occupational risks, it has been found that the level of risk is high, working conditions are hazardous and it is necessary to take measures to reduce the dust content in the workplace through the introduction of effective dust suppression systems.

Laboratory Assessment of Dense Graded Asphalt Concrete Incorporating Coal Furnace Ash in South of Vietnam

Currently, application of industrial waste or by-product in road construction industrials is a major interest by researchers, government officers and engineers. Coal ashes by-product from industrial parks negatively impact environment, costly in treatment, and require large ground for disposing areas. Therefore, this paper proposes on using the coal ash from furnace products of an industrial park in South of Vietnam to be incorporated into dense graded asphalt concrete using Nominal Maximum Aggregate Size 12.5mm. Laboratory performance tests including Marshall stability, indirect tensile strength, Cantabro loss, and dynamic fatigue test were conducted. The effects of coal ash contents in replacement of fine aggregate which is passing 4.75mm sieve from asphalt mixture into laboratory performance of mixture is also discussed in detail.

Analysis of the influence of coke quality on the production of pig iron in the conditions of JSC “Ural Steel”

The purpose of the study was to conformity of the quality of coke used in the blast-furnace shop of JSC “Ural Steel” meets the requirements recommended in the scientific literature, and to study its impact on the consumption of coke and the production of pig iron at the enterprise. For the study, the blast furnace № 1 with a useful volume of 1007 m3 and the blast furnace No. 4 with a useful volume of 2002 m3 were selected. The results of the analysis of data on the quality of coke over a three-year period: ash content, volatile matter and sulphur in the coke, the moisture content in the coke, the coke uniformity coefficient, indicators of the cold strength of coke (M25 and M10), indicators of coke hot strength (CSR) and reactivity of coke after high-temperature interaction with CO2 (CRI). Studies have revealed significant instability of the moisture content in the coke, which affects the change in its consumption, and heterogeneity of the granulometric composition of the coke, increasing the stability and uniformity of which would favorably affect the indicators of the blast furnace process. It was found that the values of the indicators of M10 coke attrition, hot strength of coke (CSR) and reactivity of coke (CRI) do not meet the recommendations of domestic and foreign scientists. Measures are proposed to improve the quality of coke, the implementation of which will increase the productivity of blast furnaces and reduce the consumption of coke per ton of pig iron.

Carbon reduction potential and costs through circular bioeconomy in the Brazilian steel industry

Although steel recycling is a credited circular economy strategy, domestic scrap stock may be a limitation to curb steelmaking carbon emissions. In Brazil, charcoal production can be a complementary climate change mitigation alternative to recycling. This study has assessed CO2 abatement potentials and costs in a low-carbon (LC) scenario for the Brazilian steel industry based on two circular bioeconomy-based options. For this purpose, Brazilian steel production was forecasted up to 2050 through an econometric model. The technical amount of scrap and the economic feasibility of charcoal have been estimated to determine the penetration of LC strategies. In addition, an uncertainty analysis was conducted using the Monte Carlo method. For the median value in the simulation, we found that crude steel production will emit 64 MtCO2 in 2050. A recycling share of 36% of the total steel production could reduce these emissions by 20%, and 86% of the remaining blast furnace production could be based on charcoal, improving the total abatement by 65%. The weighted average cost of the LC scenario is -$1/tCO2 for the median value in the simulation, but positive values have been found in 45% of the simulations. Charcoal presents higher abatement costs but less uncertainty than recycling. Such strategies can significantly reduce Brazilian steelmaking emissions, postponing other emerging or more expensive alternatives. Nevertheless, economic policies are needed due to additional costs of charcoal, in conjunction with law enforcement to ensure sustainable charcoal production, and regulations are needed to improve logistics and scrap market disparities.

Complex for the production of compressed carbon dioxide based on an industrial furnace for food production

Today, the problem of the use of energy is the most common. In order to increase energy efficiency could be used at food enterprises. A new scheme of combined main production and auxiliary production has been developed. In particular, on the basis of industrial furnaces for the production of compressed carbon dioxide. In this system, the coolant is supplied from an industrial furnace. In addition, it is shown that the coolant may be a rotary kiln or an industrial steam generator. The developed scheme is universal and can be used at the enterprise for various purposes.

Analyzing the Formation of Gaseous Emissions during Aluminum Melting Process with Utilization of Oxygen-Enhanced Combustion

Oxygen-enhanced combustion (OEC) is a useful method for improving the efficiency of thermal plants and for decreasing greenhouse gas (GHG) emissions. Basic and modified burner designs utilizing OEC in the aluminum melting process in a rotary tilting furnace were studied. A combined approach comprising experimental measurement and simulation modeling was adopted aimed at assessing GHG emissions production. Reduction of up to 60% fuel consumption of the total natural gas used in the laboratory-scale furnace was achieved. The optimal oxygen concentration in the oxidizer regarding the amount of total GHG emissions produced per charge expressed as CO2 equivalent was 35% vol. Its further increase led only to marginal fuel savings, while the nitrogen oxide emissions increased rapidly. Using the modified burner along with OEC led to around 10% lower CO2 emissions and around 15% lower total GHG emissions, compared to using a standard air/fuel burner. CFD simulations revealed the reasons for these observations: improved mixing patterns and more uniform temperature field. Modified burner application, moreover, enables furnace productivity to be increased by shortening the charge melting time by up to 16%. The presented findings demonstrate the feasibility of the proposed burner modification and highlight its better energy and environmental performance indicators, while indicating the optimal oxygen enrichment level in terms of GHG emissions for the OEC technology applied to aluminum melting.

Design of controlled temperature test in biochar production furnace automation

This study aims to test the temperature sensor that will be used in the biochar production furnace. Temperature testing is carried out to determine the ability of the sensor to respond to temperature changes that will be applied to the furnace. The sensors used in this system are the K-type thermocouple and the MAX6675 module. Testing is done by forming a control system. The system will be installed in the furnace by providing heating with fire in the furnace. The result of the maximum temperature was 574.25 °C at 575 seconds of heating for 1110 seconds. The test of corelation between the sensor output voltage to temperature when the temperature is raised from the beginning to the maximum, the sensor sensitivity is obtained at 5.1762 mV / °C and the slope of the graph is close to 1. Testing the relationship of the sensor output voltage to temperature when the temperature is lowered from the maximum point, the sensor sensitivity is obtained at 4.878 mV / °C and an offset voltage of 25 mV. The voltage-to-time correlation of the two tests is close to the value of 1, which means that the sensor linearity is very good so that it can be used as a temperature measurement tool.

The design of furnace for biochar production by using vacuum pump and temperature manual control

Temperature control is very prominent to be done in producing biochar, because the quality of biochar depends on combustion temperature and the amount of oxygen existing when the combustion process is happening. In this research, the designing of furnace for biochar production by using vacuum pump and temperature manual control had been done. The fuel used was LPG gas. The furnace was designed by having two parts which are cylinder tube for biochar production and tube feet as the holder of the kiln. The calibration of the furnace for biochar production was done to find out the temperature and the pressure that can be generated and its effect toward produced biochar. The calibration was done by using vacuum pump to vacuum the combustion chamber and temperature manual control as temperature indicator. There were two steps for this furnace calibration, first, the leakage test and second, combustion test of biochar production. The leakage test was done by using bubble test method. The result showed that there were still some leakages happened, but they were fixed with glue on the leak parts. As the final result of the leakage calibration, the vacuum condition obtained was -25 cmHg. And as the result of biochar combustion as long as one and two hour, the temperature reached 2800C and 2500C.

ПРЯМОУГОЛЬНЫЕ ЖЕЛЕЗОПЛАВИЛЬНЫЕ ПЕЧИ ГОРНОГО АЛТАЯ: ПРОБЛЕМА ГЕНЕЗИСА И ХРОНОЛОГИИ

The article raises the questions related to the appearance of unique rectangular box-shape furnaces in the Altai mountains. These furnaces were the largest iron-smelting construction in Siberia and Central Asia. Archaeological field work carried out in 2018-2020 coupled with the series of radiocarbon dates made it possible to establish that furnaces of this type appeared in the Southeastern Altai not in the era of the Turkic Khaganates, as it was previously thought, but in a previous time within the 3rd-5th centuries AD. The article discusses the design and productivity of the box-shape furnaces. It is hypothesized that the similar in shape Xiongnu pottery kilns type could have been a prototype of large rectangular structures of the box-shape linear furnaces. Radiocarbon analyzes have proven the synchronicity of the Xiongnu pottery kilns and the rectangular furnaces. The sudden disappearance of the box-shape furnaces in the Altai Mountains in the 7th-8th centuries AD and the same sudden appearance of the similar furnaces in Japan in the same period is explained by the possible migration of smelters in the era of the Second East Turkic Khaganate. Keywords: archaeometallurgy, iron-smelting furnaces, Gorny Altai, Xiongnu-Xianbei time

Development of the method of visualization for production facilities with application of augmented reality technologies

This article reviews the experience of application of VR-AR technologies (virtual and augmented reality technologies) for visual demonstration of production facilities in the process of engineering and operation. The three-dimensional modeling in CAD systems is commonly used as a means for development of construction documentation, visualization of work at different stages of engineering, and preparation of objects for engineering analysis. The authors believe that the use of AR-solutions not in parallel, but along with modern CAD systems for solution of engineering and design problems would allow avoiding design flaws and simplify the process of demonstration of projects. Based on the blueprints and three-dimensional models of the parts and assembly of two-stage reduction gear used  for lifting a thermal furnace in metallurgical production, within the framework of development of the Unity multimedia application is developed the AR application for visual demonstration of the device. As the guide mark for visualization is selected the assembly drawing of the reduction gear in digital graphical format edited in the Vuforia portal. The guide mark database is imported into the Unity environment, the logic of implementation of the technique for demonstrating the assembly of the device and separate parts is written in script program. The application is installed on a smartphone and tested; pointing the camera at the printed assembly drawing allows seeing the 3D model of the reduction gear from different angles, hide any details and scrutinize the device. The AR-applications developed according to the proposed method can be used in the process of training operational personnel, which would improve the performance and quality of work during installation and maintenance of industrial facilities, as well as for displaying the projects during exhibitions and presentations of new products.

Prediction and Optimization of Internal Return Fines Generation in Iron Ore Sintering Using Machine Learning

Prior to dispatch of sinter to the blast furnace for hot metal production, the sinter product from the sinter cooler is screened to remove smaller/finer particles. The undersize so generated is called internal return fines, which are generally recirculated into the sintering machine. A very high level of internal return fines generation limits the use of virgin ore for sintering which may hamper sinter productivity. Recently, the sinter plant at Tata Steel’s Kalinganagar works has faced issues of high internal return fines generation. As the sinter plant begins to increase its productivity levels, it becomes critical to control the generation of internal return fines to allow fresh material consumption. Limited literature is available on factors affecting the internal return fines generation in sinter plant. Given the current computational capabilities, a machine learning model was developed to ascertain the factors affecting the internal return fines generation. The development of the machine learning model and the optimization carried out based on model output is described in this work. The key parameters affecting the internal return fines generation were the sintering rate, sinter basicity, charge density and temperature in the ignition hood. In Kalinganagar, the increase in ignition hood temperature was limited by the furnace refractory condition. Further, the sinter basicity is determined by the percentage of sinter in blast furnace burden. Incorporating these constraints, the model was used to optimize the process parameters to generate the lowest possible return fines. The understanding generated from this machine learning framework has resulted in a reduction of 2-3% in internal return fines generation, which implied higher net sinter production.

Performance analysis of hot metal temperature prediction in a blast furnace and expert suggestion system proposal using neural, statistical and fuzzy models

Blast Furnace (BF) production methodology is one of the most complex process of iron & steel plants as it is dependent on multi-variable process inputs and disturbances to be modelled properly. Due to expensive investment costs, it is critical to operate a BF by reducing operational expenses, increasing the performance of raw material and fuel consumptions to optimize overall furnace efficiency and stability, also to maximize the lifetime. The chemical compositions and temperature of hot metal are important indicators while evaluating the operation, therefore, if the future values of hot metal temperature can be predicted in advance instead of subsequent measuring, then the BF staff can take earlier counteractions on several operational parameters such as coke to ore ratio, distribution matrix, oxygen enrichment rate, blast moisture rate, permeability, flame temperature, cold blast temperature, cold blast flow and pulverized coal injection rate, etc. to control the furnace optimally. In this study, Artificial Neural Networks (ANN) model is proposed combined with NARX (Nonlinear autoregressive exogenous model) time series approach to track and predict furnace hot metal temperature by selecting the most suitable process inputs and past values of hot metal temperatures using the real data which is collected from the BF operated in Turkey during 2 months of operation. Various data mining techniques are applied due to requirements of charge cycling and operating speed of the furnace which secures novelty and effectiveness of this study comparing previous articles. Furthermore, a statistical tool, Autoregressive Integrated Moving Average (ARIMA) model, is also executed for comparison. ANN prediction results of 0.92, 8.59 and 0.41 are found very satisfactory comparing ARIMA (1,1,1) model outputs of 0.73, 97.4 and 9.32 for R2 (Coefficient of determination), RMSE (Root mean squared error) and MAPE (Mean absolute percentage error) respectively. Consequently, an expert suggestion system is proposed using fuzzy if-then rules with 5 × 5 probability matrix design using the last predicted HMT value and the average of the last 5 HMT values to decide furnace’s warming or cooling movements state in mid-term and maintain the operational actions interactively in advance.

ПРИНЦИПОВА СХЕМА МОДЕЛІ НАСКРШЗНОЇ ТЕХНОЛОГІЇ ВИРОБНИЦТВА КОНКУРЕНТОЗДАТНОЇ МЕТАЛОПРОДУКЦІЇ ПІДПРИЄМСТВАМИ УКРАЇНИ, ЩО ПРАЦЮЮТЬ В НЕСТАБІЛЬНИХ СИРОВИННИХ ТА ЕНЕРГЕТИЧНИХ УМОВАХ

Detailed calculation-analytical, laboratory and industrial researches of influence of sinter composition on features of technology of production of an agglomerate, and also use of such agglomerate in a complex with application of pulverized coal on results of technology and parameters of the made pig-iron are executed. The influence of the introduction of secondary materials into the sintering charge on the indicators of experimental sintering of the sinter on the example of the introduction of the use of sludge and fine dust was studied. It is established that the use of sludge blast furnace production has a greater impact on the productivity of sintering machines, to a lesser extent on the yield and cold strength. The use in the charge of fine dust electrostatic precipitators in the amount of ~ 20.5 kg/t leads to a significant reduction in productivity and strength characteristics of the sinter. Based on the results of experimental studies, the influence of the introduction of different amounts of secondary resources into the sinter charge on some characteristics of the sinter some indicators of the blast furnace operation. The balance calculations showed that with the partial replacement of pulverized coal with natural gas in the amount of 35 m3/t of cast iron, coke consumption decreased by 35 kg/t of cast iron, which led to a decrease in the cost of cast iron by 2.1%. Mathematical models created using the results of experimental data, as well as graphical dependences of reagent consumption (Mg and Mg + CaO mixture) allowed to determine the required values of specific mass consumption of reagents and on this basis to determine the cost of production of low-sulfur iron. Mathematical modeling of oxygen-converter smelting on the basis of calculation of material and heat balances and taking into account thermodynamic and physicochemical features of chemical transformations is performed. Using mathematical modeling, a comprehensive comparative analysis of the impact of the design of blast devices and the type of liquid cast iron on the technical and economic performance of steel production OS in the oxygen-converter shop of PJSC "DMK".

ВПРОВАДЖЕННЯ СИСТЕМ ПІДТРИМКИ ПРИЙНЯТТЯ РІШЕНЬ ЩОДО УПРАВЛІННЯ ДОМЕННОЮ ПЛАВКОЮ В УМОВАХ МЕТАЛУРГІЙНОГО ВИРОБНИЦТВА ПрАТ “ДКХЗ“

The aim of the work is to increase the level of automation of blast furnace production through the development and implementation of new systems to support decision-making on the management of blast furnace smelting in changing technological and fuel conditions. The article presents a description of three decision support systems (DSS) in the mode of an adviser to the technological personnel of blast furnaces, which were implemented by the Iron and Steel Institute or underwent pilot testing as part of the automated control system of the blast furnace shop of the metallurgical production of PrJSC "Dniprovskyi Coke Plant" (Kamianske). The first DSS for managing the thermal state was implemented in 2021, it includes the entire list of information necessary for personnel in a convenient and compact form, generates recommendations in case of technology deviations and, in case of incorrect actions of the personnel, signals the need for correct actions. The main recommendations of the system are to correct the raceway adiabatic flame temperature, coke consumption when its characteristics and ore load change. Using the system allows both reducing the specific coke consumption and preventing unplanned downtime. The second DSS for controlling the distribution of fuel additives over air tuyeres is based on information on thermal loads determined on water-cooled elements of tuyere tools. The main recommendations of the system are to adjust the amount of injected pulverized coal fuel on individual tuyeres in order to ensure a uniform distribution of the raceway adiabatic flame temperature around the circumference of the blast furnace and, as a result, the energy efficiency of blast furnace smelting. The third DSS for adjusting the parameters of the charging mode is based on information from the means of controlling the temperatures of the gas flow above the surface of the charge in the blast furnace. The functioning of this system is based on determining the reference curves for the distribution of the gas flow along the furnace radii, corresponding to the minimum consumption of coke and maximum productivity, and on the search for solutions by direct and iterative optimization methods, which allow, by adjusting the loading parameters, to ensure a rational distribution of charge materials and gas flow in the furnace.

РОЗРОБКА ТЕХНОЛОГІЇ ВИРОБНИЦТВА ЗАЛІЗУРОВОГО МОНОСИРОВИНИ ДЛЯ ДОМЕННОЇ ПЛАВКИ

The aim of the work is to develop and test technological regimes for obtaining new types of shelled iron ore materials and mono-raw materials for blast furnace smelting. It is shown that the traditional ways to improve the technology of blast furnace smelting to increase the productivity of the furnace and reduce the specific consumption of coke have largely exhausted their potential. At the same time, the creation of pelleted iron ore mono-raw material with the necessary indicators of the complex of metallurgical characteristics provides additional opportunities to reduce energy costs during blast furnace smelting. The article presents the results of the developed technology for the production of pelleted iron ore monoprocess for blast furnace smelting, which has at the same time a high content of iron and residual carbon. The authors developed new types of iron ore raw materials - fluxed local spikes from iron ore concentrates of different degrees of enrichment, local spikes with increased compared to agglomerate and pellets, iron content and local spikes with high residual carbon content. To obtain local heat, as a high-temperature part of the charge, metallized rolls, metallized ores or mixtures thereof were used. It is shown that the proposed mono-raw material can be produced in existing shops for the production of fired rolls, and can significantly improve the technical and economic performance of pig iron smelting. The components of the charge were mixed, after which the mixture was subjected to heat treatment with a gaseous coolant with oxidizing or weakly oxidizing potential. The specific productivity of the combustion unit and the specific costs of energy resources (heat and electricity) in the production of scuffed mono-raw materials remained almost identical for the production of other local heat. The results of the calculation of blast furnace smelting indices when using in its charge flaked fluxed mono-raw material with high iron and carbon content are presented. Calculations show that the use of this material in blast furnace production will significantly improve the technical and economic performance of pig iron smelting.