Energy Consumption Of Furnace Research Articles

Assessing the Sustainability Impact of Improving Secondary Steel Production: Lessons Learned from an Italian Plant

Abstract This work presents a sustainability assessment approach to evaluate technological innovations in secondary steel production making use of Electric Arc Furnace (EAF) technology. The assessment covers the environmental, social, and economic dimensions of sustainability by combining different tools (Life Cycle Assessment and Analytic Hierarchy Process), and also provides an integrated assessment of the overall sustainability. The approach, which can also be used to support decision-making, has been applied to a real case study of a steel plant located in Northern Italy. In the case study, environmental sustainability is positively impacted mainly by increased metal yield and reduced furnace energy consumption. The greatest social sustainability benefits are mainly related to improved ergonomic and safety conditions for workers (reduced demand for physical effort, manual handling and repetitiveness, and lower risk of accidents), as a consequence of the introduction of Industry 4.0 technologies. Regarding economic sustainability, a positive impact related to reduced cycle time, increased metal yield and quality yield, reduced maintenance and quality control costs was observed. The integrated assessment of the overall sustainability has proven to be a viable approach to manage trade-offs between the different dimensions of sustainability.

The effect of different carbon reductants on the production of ferrosilicon 75% on an industrial scale in an electric arc furnace

Ferrosilicon production is based on the carbothermal reduction of silica and iron oxide in submerged electric arc furnaces. The reducing process of iron oxide and silicon oxide is carried out by the carbon contained in carbon materials such as coal, charcoal, semi-coke, and all types of coke. Based on its inherent and functional characteristics, the kind of carbon material can be effective in the ferrosilicon production process and furnace energy consumption. Therefore, in this work, which was performed by Iran Ferrosilice company, in a long period of 5 years, the effects of seven combinations of different carbon materials on the electrical and metallurgical performance of the process were investigated. The results showed that the minimum value of energy coefficient per ton (8.46 MWh/ton) was obtained using combination 5 (consisting of 55% coal, 30% semi-coke, 5% charcoal, and wood chips). The use of wood chips reduced the energy consumption by 3.03 MWh/ton. The composition consisting of 50% coal, 35% semi-coke, 15% charcoal, and wood chips had the highest Si% of 73.64% and the lowest Al% of 1.54%. Finally, by evaluating all the results, especially the reduction of energy consumption and recovery of Si, compound 5 was introduced as the optimal compound in the ferrosilicon production process.

Causes of the appearance of current waves in high voltage electric arc furnaces, and methods of their reduction

This article presents a method of generation and reduction of current waves in high-voltage electric arc furnaces in industrial and mining enterprises, in contrast to existing methods. The developed method is currently relevant for the solution of problems related to the generation of current waves during the operation of high-voltage electrics are furnaces with a power of 3 MWt used in the melting and pouring of metals of different densities at the Navoi mechanical engineering plant. The main goal of implementing the developed method is to reduce the electric energy consumption of high-voltage electrics arc furnaces and to increase the efficiency of electric energy consumption of the furnace.

Sustainable Scheduling of the Production in the Aluminum Furnace Hot Rolling Section with Uncertain Demand

In order to reduce the energy consumption of furnaces and save costs in the product delivery time, the focus of this paper is to discuss the uncertainty of demand in the rolling horizon and to globally optimize the sustainability of the production in the aluminum furnace hot rolling section in environmental and economic dimensions. First, the triples α/β/γ are used to describe the production scheduling in the aluminum furnace hot rolling section as the scheduling of flexible flow shop, satisfied to constraints of demand uncertainty, operation logic, operation time, capacity and demand, objectives of minimizing the residence time of the ingot in the furnace and minimizing the makespan. Second, on the basis of describing the uncertainty of demand in rolling horizon with the scenario tree, a multi-objective mixed integer linear programming (MILP) optimization model for sustainable production in the aluminum furnace hot rolling section is formulated. Finally, an aluminum alloy manufacturer is taken as an example to illustrate the proposed model. The computational results show that when the objective weight combination takes the value of α=0.7, β=0.3, the sustainability indicators of the environmental and economic dimensions can be optimized to the maximum extent possible at the same time. Increasingly, managerial suggestions associated with the trade-off between environmental and economic dimensions are presented. Scheduling in the rolling horizon can optimize the production process of the aluminum furnace hot rolling section globally, indicating that it is more conducive to the sustainable development of the environment and economic dimensions than scheduling in a single decision time period.

Optimization of Tempering Process Parameters of AISI 3140 Low Alloy Steel to Conserve Furnace Energy using Tukey’s Honestly Significant Difference Test

Quenching and Tempering of AISI 3140 alloy steel is a necessary heat treatment process to attain desired hardness and toughness. However the tempering process consumes remarkable amount of energy in furnace. One of the usual tempering processes of AISI 3140 steel is performed by heating it to a temperature of 425°C in crucible furnace and holding at that same temperature for 2 hours. Furnace energy consumption may be reduced by increasing tempering temperature to 540°C and holding for a relatively lesser duration. Therefore, 20 specimens of AISI 3140 steel are oil quenched. Few specimens are tempered at lower temperature of 425°C for 2 hours. Remaining specimens are tempered in 4 batches at higher temperature of 540°C for various holding time of 50 minutes, 40 minutes, 30 minutes and 20 minutes respectively. The heat treated specimens are subjected to Izod’s Impact test and Rockwell Hardness test. Test results are statistically analyzed using Tukey’s Honestly Significant Difference Test and it is found that impact toughness and hardness attained by tempering at 425°C for 2 hours is significantly equal to that attained at 540°C for 30 minutes. It is observed that the furnace energy consumed is decreased significantly by increasing furnace temperature and reducing holding time during tempering process while other process parameters are kept identical. Thus energy and time are conserved without compromising the vital mechanical properties by optimizing tempering process parameters.

Brief Discussion on Energy Saving of Building Sanitary Ceramic Kiln

Since the 11th five-year plan, “energy conservation, consumption reduction and green upgrading” has gradually become the theme of China’s industrial ecological civilization construction. “High energy consumption, high emission, high pollution” building sanitary ceramics industry as a typical traditional industry, has been regarded as the key object of energy conservation and consumption reduction. Among them, furnace energy consumption accounts for more than 60% of ceramic production, so “furnace energy saving” is regarded as the “top priority” of energy saving. Furnace energy saving is a system of energy saving. Therefore, the factor of energy saved has included that construction materials, furnace structure, combustion technology, waste heat utilization, air surplus coefficient and automatic control. Based on the above influencing factors, this paper carries out research on furnace energy conservation, providing technical guidance for enterprises to save energy and reduce consumption, and helping the industry to transform and upgrade.

Energy consumption modelling using deep learning embedded semi-supervised learning

Reduction of energy consumption in the steel industry is a global issue where government is actively taking measures to pursue. A steel plant can manage its energy better if the consumption can be modelled and predicted. The existing methods used for energy consumption modelling rely on the quantity of labelled data. However, if the labelled energy consumption data is deficient, its underlying process of modelling and prediction tends to be difficult. The purpose of this study is to establish an energy value prediction model through a big data-driven approach. Owing to the fact that labelled energy data is often limited and expensive to obtain, while unlabelled data is abundant in the real-world industry, a semi-supervised learning approach, i.e., deep learning embedded semi-supervised learning (DLeSSL), is proposed to tackle the issue. Based on DLeSSL, unlabelled data can be labelled and compensated using a semi-supervised learning approach that has a deep learning technique embedded so to expand the labelled data set. An experimental study using a large amount of furnace energy consumption data shows the merits of the proposed approach. Results derived using the proposed method reveal that deep learning (DLeSSL based) outperforms the deep learning (supervised) and deep learning (label propagation based) when the labelled data is limited. In addition, the effect on performance due to the size of labelled data and unlabelled data is also reported.

Multi-objective Optimization of Aluminum Anode Baking Process Employing a Response Surface Methodology

In the aluminum anode baking furnace, the operational parameters have a significant influence on the furnace performance and the resulting anode quality. For this furnace, an important parameter is the fire-cycle, which determines the production rate of the baking kiln and the anodes quality. Shorter fire-cycle results in a higher furnace production rate and a higher fuel consumption (same anode temperature should be obtained in a shorter time). For a particular fire-cycle, flue-gas soaking temperature and soaking time are the other two key parameters that affect anode temperature distribution and furnace energy consumption. Limited studies in the literature focused on employing the traditional one-factor-a-time (OFAT) method to investigate the effect of these factors. Based on a simplified multi-physics model, a high-fidelity computational tool named ABKA (anode baking kiln analysis) software is developed to investigate the effects of these key operational parameters on the anode baking furnace heating performance. ABKA is employed to conduct a three-factors, two-level full factorial design, with a center point, to investigate the effects of varying fire-cycle, soaking temperature, and soaking time on furnace production rate, fuel consumption, and anode maximum, minimum and average temperature. The advantage of the present approach compared to the traditional one-factor-a-time (OFAT) method is that it can provide adequate information on interactions of different input variables, to effectively estimate the significance level of each factor, and to identify clear optimal settings of the three variables. Using ANOVA (analysis of variance), the effect and significance level of each factor and their interactions are effectively estimated. It is observed that soaking temperature has the highest impact on the final anode temperature distribution. Considering the furnace fuel consumption as a response, it is perceived that soaking time and soaking temperature jointly are as significant. Finally, employing RSM (response surface methodology), conducting multi-objective optimization, the optimal settings of the soaking time and soaking temperature for different production rates (fire-cycle values) are also estimated.

On Development of Module for Neural Tuner to Adjust D-part of PID-controller Online

Nowadays nonlinear industrial plants are controlled by linear P, PI and PID-controllers with constant parameters. This results in both transients quality and energy efficiency decrease. An adaptive neural tuner to adjust P and PI controllers parameters has been proposed to solve these problems and tested both for heating furnaces and DC drives. But it is not able to adjust a D-part of the controller, which is widely used for the heating furnaces. So the aim of this research is to extend the functionality of the tuner with a new software module to adjust KD parameter online. In order to achieve this, a new structure of the neural network for the tuner is chosen, its rule base is enhanced with the developed rules for KD, and the sustainability criterion for the system with the tuner and the PID-controller is developed. The new version of the tuner is applied to control a heating furnace to keep the required transients quality under the condition of the furnace parameters non-stationarity. Comparing to the PID-controller, it allows to reduce transients time averagely by 11.6% and the furnace energy consumption by 8.4%.

Investigating the flue-wall deformation effects on performance characteristics of an open-top aluminum anode baking furnace

The carbon anode baking is typically the bottleneck in the production of anodes for the aluminum industry. The challenge is to produce high quality baked anodes while keeping the energy consumption, environmental emissions, and cost to a minimum. Anode baking homogeneity is an important consideration in the design and operation of the anode baking furnaces. The flue-walls, into which the firing takes place, are the heart of the furnace. The flue-walls must be well designed and well maintained in order to be able to regulate them properly. However, during the service life of a baking furnace, flue-walls deform which affect the baking uniformity and consequently result in over-consumption energy and reduction in carbon anode quality. Studying the effects of flue-wall deformation by plant tests is highly challenging and expensive. Hence, this study aims at investigating this phenomenon by developing a three-dimensional (3D) model which includes many physical phenomena and parameters that play vital roles in the baking process. It was observed that indeed the flue-wall deflection has a significant impact on heat transfer characteristics of the anode baking process and furnace energy consumption. In specific, the flue-wall deformation results in an increase in temperature gradients within the anode pack such that the differences between anode pack minimum, average and maximum temperatures lead to overbaking or underbaking of anodes. In fact, this non-uniform baking gives rise to the evolution of non-homogeneous carbon anodes material properties, which is the main reason for excess energy consumption and various instabilities in the aluminum reduction cell. The insights obtained in the present study can be employed in modifying the furnace geometrical and operational parameters with the deformed flue-walls.

The effects of flue-wall design modifications on combustion and flow characteristics of an aluminum anode baking furnace-CFD modeling

A modern aluminum smelter has a capacity of 1–2 million tons of aluminum per annum which requires more than 0.5–1.0 million tons of heat treated (baked) carbon anodes per year. The anode baking process is very energy intensive, approximately requires 2 GJ of energy per ton of carbon anodes which will be approximately 1–2 million GJ of energy per year. Since the plant testing is very expensive, anode baking furnace modeling is imperative to investigate the effects of different operational and geometrical parameters on the furnace energy consumption.In the numerical modeling of turbulent reactive flows, the accuracy of the model highly depends on the description of turbulence-chemistry interaction, and the robustness of the radiative transfer equation solver. Hence, the present study tested different turbulence-chemistry interaction frameworks and radiative transfer equation solvers for confined turbulent diffusion flames and results are compared with the experimental data. It was observed that the k-ε realizable turbulence model combined with the presumed probability density function method as turbulence-chemistry interaction, and discrete ordinates method as radiative transfer equation solver illustrate excellent agreement with the experimental data.Anode baking homogeneity is an important consideration in the design of the anode baking furnace, which requires appropriate flow distribution in the flue-wall cavity. Hence, the developed numerical framework was employed to investigate the effects of flue-wall design modifications on combustion and heat transfer characteristics of anode baking furnace energy consumption. It was observed that the modified design results in a higher thermal efficiency (lower energy consumption), and more homogenous temperature and flow fields which result in the baking of anodes more uniformly which consequently result in the evolution of more homogenous material properties. Consequently, the energy consumption in the aluminum reduction cell will also be significantly reduced. The present study also investigated the effect of flue-wall flow blockage due to packing coke infiltration on baking energy consumption for the aged anode baking furnaces and introduced three modified flue-wall designs.

Energy Savings Through Thermally Efficient Crucible Technology: Fundamentals, Process Modeling, and Applications

Melting and holding molten metals within crucibles accounts for a large portion of total energy demand in the resource-intensive nonferrous foundry industry. Multivariate mathematical modeling aided by detailed material characterization and advancements in crucible technologies can make a significant impact in the areas of cost-efficiency and carbon footprint reduction. Key thermal properties such as conductivity and specific heat capacity were studied to understand their influence on crucible furnace energy consumption during melting and holding processes. The effects of conductivity on thermal stresses and longevity of crucibles were also evaluated. With this information, accurate theoretical models using finite element analysis were developed to study total energy consumption and melting time. By applying these findings to recent crucible developments, considerable improvements in field performance were reported and documented as case studies in applications such as aluminum melting and holding.

Modeling, optimization and control of an austenitization furnace for achieving target product toughness and minimizing energy use

Quench hardening is the process of heating finished or pre-finished steel parts to a specific temperature in order to reach a phase transformation of steel to austenite (austenitization) followed by quenching in oil, water or brine to induce desired metallurgical properties. During this process, both macroscopic quantities such as temperature and heat duty and microscopic variables, such as austenite grain size, determine the quality of the quenched product. In this paper, we propose a novel model-based approach for optimizing the energy input to an austenitization furnace system by capturing the essential physics at both the aforementioned length scales. The model predicts the energy consumption of the system, the part temperature distribution and the austenite grain size distribution as a function of the processing time and processing conditions. An optimization scheme is proposed to minimize the furnace energy consumption without compromising the part heating requirements and product quality.

Conservação de energia em fornos de cozimento de anodo

A tendência por unidades de produção mais sustentáveis vem obrigando a indústria de alumínio a adotar estratégias para reduzir o consumo de energia e minimizar a geração de resíduos. Procedimentos nesta direção têm sido implementados em fornos de cozimento de anodo, onde alguns aprimoramentos têm permitido a redução no consumo de energia. Entretanto, sabe-se que durante a etapa de queima do anodo, elevada quantidade de calor é ainda dissipada para o ambiente, aumentando os custos com energia. Desta forma, o presente trabalho tem por objetivo apresentar alternativas de redução do consumo de combustível do forno de cozimento de anodo considerando, para isto, o transporte de calor das câmaras de combustão desde as paredes refratárias até o bloco de carbono, passando pelo coque fluido. Os resultados aqui obtidos indicam que uma possível mudança da distribuição do tamanho de partículas do coque, bem como, a adição de uma manta isolante no topo do forno pode aperfeiçoar o desempenho do sistema quando o foco é sustentabilidade e otimização do processo.

New Control Structure for Feed-Effluent Heat Exchanger/Reactor Systems

Feed-effluent heat exchangers (FEHEs) are widely used in high-temperature exothermic adiabatic tubular reactor systems to conserve energy. The hot reactor effluent is recycled back to a feed preheater to provide all or a portion of the energy required to preheat the reactor feed to the optimum reactor inlet temperature. Several alternative flowsheets have been presented in the literature for this type of configuration. Some use bypassing of cold material around the FEHE, some use a furnace after the FEHE and before the reactor, and some use a cooler (steam generator) after the reactor. A number of control structures have been proposed to control the reactor inlet temperature, which is critical for the steady-state performance (achieving the desired conversion and staying below some maximum temperature). It is also critical for dynamic performance since these systems can be openloop unstable as a result of the positive feedback of energy from the reactor back to the preheat system. The control structure must prevent quenching to low temperatures (“blowout”) and temperature runaways (“blowup”). The most commonly suggested control structure recommends controlling the temperature of the mixed stream after the FEHE by manipulating the bypass flow and controlling the reactor inlet temperature by manipulating fuel to the furnace. This paper presents an alternative process and control configuration that reduces furnace energy consumption while maintaining good dynamic control in the face of very large disturbances.

E3 Analysis for Crude and Vacuum Distillation System

AbstractCrude oil blending is a very common practice in petroleum refineries, where the main focus is to minimize the total purchase cost of crude oils under specified blending oil properties. Crude oil blending actually has significant impacts on energy consumption from heating furnaces during crude oil processing. Conceivably, furnace energy consumption from burning fuels such as natural gas, fuel oil, or propane causes huge amounts of CO2 emissions. In this paper, a methodology framework for crude oil blending and processing with simultaneous consideration of energy, emission, and economic profit (E3) is developed. It includes four stages of work: steady‐state modeling, heating energy consumption calculation, emission model development, and economic evaluation. With Aspen HYSYS simulation, the developed methodology provides a quantitative support for refinery to identify an optimal E3 operating strategy. A case study is implemented to demonstrate the efficacy of this methodology.

Greenhouse Emissions in Primary Aluminium Smelter Cast Houses - A Life Cycle Analysis

The aluminium industry is reducing its carbon dioxide emissions and environmental footprint. In order to identify and prioritise areas in the cast house where greenhouse gas emissions can be reduced it is necessary to quantify CO2e (CO2 equivalent tonnes) emissions for the various cast house operations. In this study two typical cast house layouts are examined. In one case, 22kg 99.85% aluminium remelt ingots are produced using chain conveyor ingot casting machines. In the second case, wrought alloy extrusion and rolling slab direct chill cast products are made. Both plants are sized at 500ktpa. The various process inputs in terms of energy and materials were identified and typical usage rates assigned. The results show that general electricity consumption, dross generation and furnace energy consumption are the three biggest areas of CO2e and should be targeted for improvement. Magnesium consumption also has a large effect in the case of the

New heating schedule in hydrogen annealing furnace based on process simulation for less energy consumption

Cold rolled steel coils are annealed in batch furnaces to obtain desirable mechanical properties. Annealing operations involve heating and cooling cycles which take long due to high weight of the coils under annealing. To reduce annealing time, a simulation code was developed that is capable of evaluating more effective schedules for annealing coils during the heating process. This code is additionally capable of accurate determination of furnace turn-off time for different coil weights and charge dimensions. After studying many heating schedules and considering heat transfer mechanism in the annealing furnace, a new schedule with the most advantages was selected as the new operation conditions in the hydrogen annealing plant. The performance of all the furnaces were adjusted to the new heating schedule after experiments had been carried out to ensure the accuracy of the code and the fitness of the new operation condition. Comparison of similar yield of cold rolled coils over two months revealed that specific energy consumption of furnaces under the new heating schedule decreased by 11%, heating cycle time by 16%, and the hydrogen consumption by 14%.