60 results on '"Steel mill"'
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2. Screening South Yorkshire: The Gamekeeper and Looks and Smiles
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Forrest, David, Vice, Sue, and Mazierska, Ewa, editor
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- 2017
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3. Psychological Ownership
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Kemp, Simon and Kemp, Simon
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- 2016
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4. Marketing Inertia
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Sisodla, Rajendra S., Academy of Marketing Science, and Hawes, Jon M., editor
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- 2015
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5. Model and Improved Dynamic Programming Algorithm for Optimization of Unplanned Slab Allocation in the Steel Plant
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Yongzhou Wang, Zhong Zheng, Cheng Wang, and Gao Xiaoqiang
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Dynamic programming ,Mathematical optimization ,Knapsack problem ,business.industry ,Computer science ,Steel mill ,Slab ,Process (computing) ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Slab allocation ,Local search (optimization) ,Decomposition method (constraint satisfaction) ,business - Abstract
The unplanned slab is the open orders slab produced by the steelmaking-continuous casting process, which will increase the inventory cost of enterprises. The unplanned slab allocation problem is to reasonably assign the unplanned slabs to the hot rolling supplementary orders, steelmaking supplementary orders, or customer orders in a given period. It can be considered as an extension of the multiple knapsack problem. Therefore, a 0–1 integer programming model is established to minimize the cost of differences between unplanned slab and order specification. In this paper, a decomposition method of problem solving process, an adaptive measurement method of order priority in different scenarios, and an improved dynamic programming algorithm considering the local search strategy are proposed for the unplanned slab allocation. The testing cases with data from a steel plant show that the optimization algorithm for the unplanned slab allocation is superior to the manual one in terms of solution quality and calculation time.
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- 2021
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6. A Proposal to Redesign the Distribution Networks of Steel Manufacturing and Distribution Companies
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Yndira Guevara, Yereth Romero, Mario Chong, and Alexandra Ferrer
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Process (engineering) ,business.industry ,Computer science ,media_common.quotation_subject ,Distribution (economics) ,Manufacturing engineering ,Product (business) ,Work (electrical) ,Order (exchange) ,Service level ,Steel mill ,Quality (business) ,business ,media_common - Abstract
Steel product manufacturing and distribution companies use diverse optimization tools to improve its operations. This study seeks to compare the current model (AS-IS) of a company, in order to design a new distribution network and location of its current supply centers, allowing economic and time improvements. Using this methodology, companies will optimize the customer’s service level without neglecting its quality proposal; the distribution centers will enhance their capacity as well as the use of their resources, and the decision makers will simulate their models using operations research to define optimal policies. Moreover, we will present a proposed model (TO-BE) to the company. The comparison between the AS-IS and TO-BE models indicates a reduction in the delivery times and costs, currently being the main problems of the company. The contribution of this work lies in the optimization process of the current model and its proposals.
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- 2021
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7. Text Mining-Based Association Rule Mining for Incident Analysis: A Case Study of a Steel Plant in India
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Sammangi Vinay, Jhareswar Maiti, Chawki Djeddi, and Sobhan Sarkar
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050210 logistics & transportation ,Association rule learning ,Computer science ,business.industry ,05 social sciences ,computer.software_genre ,Accident (fallacy) ,Text mining ,Incident analysis ,Steel mill ,0502 economics and business ,0501 psychology and cognitive sciences ,Artificial intelligence ,Causation ,business ,Categorical variable ,Model building ,computer ,050107 human factors ,Natural language processing - Abstract
Although a large amount of accident data in terms of categorical attributes and free texts are available across large enterprises involving high-risk operations, the methodology for analyzing such mixed data is still under development. The present study proposed a new methodological approach to extract useful inherent patterns or rules for accident causation using association rule mining (ARM) of both incident narratives (unstructured texts) and categorical data. Incidents data from an integrated steel plant for a period of four years (2010–2013) are used for model building and analysis. In the first phase, the text mining approach is employed to find out the basic events that could lead to the occurrences of faults or incident events. In the second phase, text-based ARM has been used to extract the useful rules from unstructured texts as well as structured categorical attributes. A total of 23 best item-set rules are extracted. The findings help the management of the plant to augment the cause and effect analysis of accident occurrences as well as quantifying the effects of the causes, which can also be automated to minimize the human involvement.
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- 2021
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8. Use of Artificial Neural Network to Predict the Yield of Sinter Plant as a Function of Production Parameters
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G. C. Das, Chanchal Biswas, Saugata Dhar, Rajib Dey, and Arghya Majumder
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Blast furnace ,Cost efficiency ,business.industry ,Steel mill ,Process (computing) ,Environmental science ,Production (economics) ,Process variable ,Raw material ,Process engineering ,business ,Productivity - Abstract
Now a day’s an effective process management system is essential for the sustainability of integrated steel plant. Their effective process enhances quality of product and increases the cost efficiency. The nature of the raw material, its mix proportion, size, chemical composition and process parameter plays a very vital role in sinter mineralogy. The main objective of this study is to optimize the sinter plant process parameters to get the best productivity of Sinter Plant. Sinter has a very vital role for the production of hot metal in blast furnace. A huge number of industrial parameters as large as 106 numbers control the productivity of sinter plant in a very complex manner. As such there is not much study on the prediction of sinter yield as function of those parameters combined. Perhaps it is for the first time an attempt has been made to predict the sinter yield by using Artificial Neural Networking (ANN), with large number of industrial data available at Vizag Steel over a fairly long period of time. One of the most important achievement of this paper is that the reduction in the number of parameters using metallurgical knowledge and experience (without using any sophisticated optimization technique). The prediction of sinter yield with this reduced number of parameters is almost as good as that predicted by using the exhaustive number of 106 parameters within the framework of ANN.
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- 2021
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9. Automation of Assembly Batches Installation in Hot Rolling Mills
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Alexander Galkin and Vladimir Istomin
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Set (abstract data type) ,Production planning ,business.industry ,Computer science ,Steel mill ,Genetic algorithm ,Process (computing) ,Rolling mill ,Process engineering ,business ,Automation - Abstract
The study presents the process of forming assembly batches installation in a hot rolling mill. There has been developed an algorithm for the optimal formation of assembly batches at a hot rolling mill based on the genetic algorithm considering technological restrictions imposed on the production process. The optimization of the set of assembly batches consists of the construction of a set with maximum productivity, which is achieved by reducing the time for the reconstruction of the equipment when switching to different width and thickness of rolling stock. A program for automatic formation of assembly batches at a hot-rolled steel mill has been implemented. It is now possible to save each batch included in the generated set to a separate file, as well as write general information about the entire set to a file. The algorithm was tested when forming assembly batches from a set of slabs available at the warehouse. Calculations on the formation of optimal assembly batches have been carried out. The presented results of the study show the increase of the formed assembly batches’ productivity and their compliance with all technological restrictions.
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- 2021
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10. Analytics with Stochastic Optimization: Experimental Results of Demand Uncertainty in a Process Industry
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Manoj Kumar Tiwari, Goutam Dutta, Krishnendranath Mitra, and Narain Gupta
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User Friendly ,Decision support system ,Analytics ,business.industry ,Computer science ,Steel mill ,Stochastic optimization ,IBM ,Solver ,business ,Industrial engineering ,Stochastic programming - Abstract
The key objective of the research is to report the results of testing of a two stage stochastic linear programming (SLP) model with recourse using a multi scenario, multi period, menu driven user friendly DSS in a North American steel company. The SLP model and the DSS is generic which can be applied to any process industry. It is capable of configuring multiple materials, multiple facilities, multiple activities and multiple storage areas. The DSS is developed using 4th Dimension programming language, and the SLP model was solved using the IBM CPLEX solver. The value of the SLP solution derived from the experimentation of the DSS with a real-world instance of one steel mill is 1.61%, which is equivalent to a potential benefit of US$ 24.61 million.
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- 2021
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11. Toward 100% Recycling of Steelmaking Offgas Solid Wastes by Reallocating Zinc-bearing Materials
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Naiyang Ma
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Basic oxygen steelmaking ,Waste management ,chemistry ,business.industry ,Steel mill ,chemistry.chemical_element ,Environmental science ,Zinc ,business ,Cooling effect ,Steelmaking - Abstract
High-zinc concentration in basic oxygen furnace steelmaking offgas solid wastes has been one of the major barriers hindering in-plant recycling of the solid wastes in an integrated steel mill. Therefore, zinc concentration is an important recyclability indicator of the steelmaking offgas solid wastes. In this study, zinc flow analysis was carried out, and crucial zinc-bearing materials were identified. After the crucial zinc-bearing materials were reallocated, most of the steelmaking offgas solid wastes became internally recyclable in the sintering-blast furnace ironmaking process for utilization of iron and fluxes. The rest of the steelmaking offgas solid wastes could be recycled internally in the briquetting-basic oxygen furnace steelmaking process for cooling effect and externally in cement industry for iron. As a result, 100% recycling of the steelmaking offgas solid wastes was achieved.
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- 2020
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12. Optimization and Management of On-Site Power Plants Under Time-of-Use Power Price: A Case Study in Steel Mill
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Zefei Zhang, Xiancong Zhao, Huanmei Yuan, and Hao Bai
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Mathematical optimization ,Electricity generation ,Linear programming ,Power station ,business.industry ,Computer science ,Steel mill ,Scheduling (production processes) ,Tariff ,Electricity ,business ,Energy storage - Abstract
The implementation of time-of-use (TOU) power tariff in Chinese steel industry provides an opportunity for steel mills to reduce electricity bills through an optimal collaboration between the on-site power plant (OSPP) and energy storage equipment (gasholders). In this paper, a mixed-integer linear programming (MILP) based scheduling model was proposed to achieve the optimal operation of OSPP and gasholders in a steel mill under TOU tariff. Compared with previous models, we considered the influence of TOU power tariff on the optimal scheduling of OSPP. The results of a case study demonstrate that the optimization model can achieve better peak-valley shifting of the electricity generation and decrease the electricity purchasing cost by 7.5% with improved gasholder stability. In addition, the overall power generation efficiency can be increased by 2.13% using the proposed model, which indicates that the byproduct gases can be effectively and efficiently used.
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- 2020
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13. Study on the Relationship Between Process Reconstruction and Energy Saving of Iron and Steel Manufacturing Process in China
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Anjun Xu, Shuangping Wu, Ji Li, and Qi Zhang
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Energy conservation ,Set (abstract data type) ,Consumption (economics) ,Computer science ,Energy flow ,Steel mill ,Process (computing) ,Manufacturing engineering ,Energy (signal processing) ,Material flow - Abstract
As people pay more and more attention to environmental protection, energy conservation in the whole process of steel manufacturing has become a hot research object. China’s steel manufacturing process has a history of energy conservation for more than 40 years. The total energy consumption per ton of steel of large and medium-sized enterprises has dropped from 1.646tce/t to 555.24kgce/t. This paper puts forward a new theory of process reconstruction, which is mainly explained from the following three aspects: analysis-optimization of the set of procedures’ functions, coordination-optimization of the set of procedures’ relations, and reconstruction-optimization of the set of process’ procedures. Then, the paper expounds the relationship between process reconstruction and energy saving from two aspects: interface technology and synergy of material flow and energy flow. After applying the new process reconstruction technology, the energy-saving effect of about 5% was achieved in the steel plant experiment. Finally, the research direction of energy conservation in steel manufacturing process is proposed.
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- 2020
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14. Production of Iron in the Blast Furnace
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José Ignacio Verdeja González, Luis Felipe Verdeja González, and Daniel Fernández González
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Blast furnace ,Materials science ,Pig iron ,Conventional casting ,fungi ,Metallurgy ,technology, industry, and agriculture ,Raw material ,engineering.material ,Corex Process ,Continuous casting ,Steel mill ,Smelting ,engineering - Abstract
The Iron Age began when the humans, probably by chance, discovered iron sponge when they were heating iron ores that were easily reduced. From that moment, the technologies to produce iron/steel have been significantly developed. This way, nowadays, there are three routes: the utilization of Direct Reduction Iron, the electric furnace steel plant, and the integrated iron and steel route. This last one is the most important as it represents 65% of the steel produced worldwide and follows the sequence blast furnace–converter–secondary metallurgy to produce steel by means of continuous casting or conventional casting. The smelting reduction in the blast furnace is the most important option to produce the pig iron (raw material for the production of steel), although the Corex process is the single alternative, and, for that reason, this chapter is entirely dedicated to the production of pig iron in the blast furnace.
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- 2020
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15. Large Data and AI Analysis Based Online Diagnosis System Application of Steel Ladle Slewing Bearing
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Fengshou Gu, Wei Hu, and Shiqi Chen
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Ladle ,Bearing (mechanical) ,Computer science ,business.industry ,Structural engineering ,Residual ,computer.software_genre ,Expert system ,law.invention ,Slewing bearing ,law ,Steel mill ,Turret ,business ,computer - Abstract
Setting the default diagnosis and residual longevity of steel ladle turret bearing as the research subject, this article developed a large data and fusion of data mining with expert system based AI default diagnosis system, which has been successfully applicated in the default diagnosis of steel ladle turret bearing of a steel, saving tremendous time for steel mill’s decisive equipment maintenance by precisely predict the residual longevity of the equipment.
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- 2020
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16. Goal-Oriented, Inverse Design Method—The Horizontal Integration of a Multistage Hot Rod Rolling System
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Anand Balu Nellippallil, Janet K. Allen, Farrokh Mistree, B. P. Gautham, and Amarendra K. Singh
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Horizontal integration ,Goal orientation ,Computer science ,Steel mill ,fungi ,Process requirements ,technology, industry, and agriculture ,Process (computing) ,Mechanical engineering ,Production (economics) ,Inverse ,Rod - Abstract
Steel mills are involved in the production of semi-products such as sheets or rods with certain grades of steel. Process designers are very much aware of the operating constraints and process requirements for each of the operations as they are involved in the whole process day-in and day-out.
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- 2020
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17. Prediction Model of End-Point Molten Steel Temperature in RH Refining Based on PCA-CBR
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Dongfeng He, Anjun Xu, Maoqiang Gu, Kai Feng, and Hongbing Wang
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Back propagation neural network ,End point ,Materials science ,Steel mill ,Principal component analysis ,Molten steel ,Range (statistics) ,Case-based reasoning ,Biological system ,Refining (metallurgy) - Abstract
The end-point temperature prediction model of molten steel for RH refining process, based on principal component analysis (PCA) and case-based reasoning (CBR), was established for the precise control of end-point molten steel temperature. Six principal components were selected from eleven factors influencing molten steel temperature based on PCA, which were taken as the principal component analysis and case-based reasoning (PCA-CBR) model inputs to construct the corresponding model. The precision of the model was verified by the actual production data of a steel plant, which was compared with the prediction model based on conventional CBR model as well as the back propagation neural network (BPNN) model. The results show that the precision of the model based on PCA-CBR reaches 69.67%, 83.67%, and 97%, respectively, when its prediction error is in the range of [−5, 5], [−7, 7], and [−10, 10], respectively. Therefore, the model can predict the end-point temperature of molten steel for RH refining process more precisely.
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- 2020
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18. Iron- and Steel-Making Process
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Debasish Sarkar and Subir Biswas
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Carbon steel ,business.industry ,media_common.quotation_subject ,Alloy steel ,engineering.material ,Steelmaking ,Upgrade ,Steel mill ,New product development ,engineering ,Quality (business) ,business ,Process engineering ,Refractory (planetary science) ,media_common - Abstract
With extensive changing in the operating practice due to stringent control in product quality, introduction of new product mix and demand for high productivity, it is indeed to upgrade the refractory quality to cope up with the changed environment and refractory life improvement. Hence, starting with the master plan, it was decided to provide a brief introduction on modern iron- and steel-making practice along with background of refractory choice in Chap. 2, to amalgam the relation of refractory performance with changed escalating demand on safe performance. As small blast furnaces have been closed and replaced by large-size furnaces, open-hearth steel making has been replaced by high-productive basic oxygen furnaces (BOF), RH (Ruhrstahl Heraeus)—degasser is the most popular for making ultra-low carbon steel. Additional Composition Adjustment by Sealed argon bubbling with Oxygen Blowing (CAS-OB) is started to operate in many integrated and large-size steel plant to produce high-quality alloy steel; the operating processes of those equipment has been discussed in detail.
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- 2020
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19. Integrated Design Exploration of Materials, Products, and Manufacturing Processes Using Goal-Oriented, Inverse Design Method
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Farrokh Mistree, Amarendra K. Singh, Anand Balu Nellippallil, B. P. Gautham, and Janet K. Allen
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Integrated design ,Process (engineering) ,business.industry ,Computer science ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Deformation (meteorology) ,Microstructure ,Material flow ,Lead (geology) ,Casting (metalworking) ,Steel mill ,Process engineering ,business ,ComputingMethodologies_COMPUTERGRAPHICS - Abstract
Steel manufacturers focus on developing new grades of steel with improved properties and performance. The careful managing of material processing during steel manufacturing will lead to the development of steels with a range of mechanical properties resulting in the improved performance of products. A round rod is produced after passing the raw steel through several manufacturing processes such as casting, reheating, rolling, and cooling. This round rod forms the input material for gear production. The chemical composition of the steel including the segregation of alloying elements, the deformation history during rolling, the cooling after rolling, and the microstructure generated define the end properties of the rolled product. The presence of large numbers of design variables, constraints and bounds, conflicting goals, and sequential information/material flow during material processing makes the steel rod making process chain highly complex. Many plant trials are therefore required to produce a new steel grade with desired properties and performance. These trials are usually expensive and time-consuming. An alternative is to carry out simulation-based, integrated design exploration of the different manufacturing processes involved in exploiting the advances in computational modeling and identifying a ranged set of solutions that satisfy the requirements, both of the steel manufacturing process and the end rod product.
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- 2020
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20. Engineering Solutions for the Use of Air Enriched with Oxygen in Power Engineering Complexes of Power Plants Operating on Secondary Gases
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Evgeniy B. Agapitov, M. S. Sokolova, and Artem E. Agapitov
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Blast furnace ,Waste management ,Power station ,Steel mill ,Turboexpander ,Boiler (power generation) ,food and beverages ,Environmental science ,Coke ,Combustion ,complex mixtures ,Superheater - Abstract
The article analyzes the efficiency of using oxygen-enriched air to control combustion in a steam boiler of a steam-blowing power plant of PJSC “Magnitogorsk Iron and Steel Works”. In the boilers of a steam-blowing power plant, a mixture of three gases is burned: natural, coke and blast furnace. In the case of a change in the ratio of gases, the combustion conditions and the geometric characteristics of the flame change. In some cases, this leads to an undesirable increase in the heat load in the boiler elements, especially in the superheater. Since the task of boilers of a steam blower power plant is to provide blast furnace production with air blast enriched with oxygen, the work of turbo expanders is directly related to the rhythm of the blast furnace. In the case of reducing the load of the blast furnace, there is an excess of air blast, which can be used to solve other problems, in particular, to control the combustion process in the boiler furnace. The article presents the results of numerical simulation of thermal fields in the furnace of an energy boiler of a steam-blowing power plant using oxygen enriched air.
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- 2020
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21. Refractories for Iron and Steel Plant
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Subir Biswas and Debasish Sarkar
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Materials science ,Ground granulated blast-furnace slag ,visual_art ,Steel mill ,Metallurgy ,Mixing (process engineering) ,visual_art.visual_art_medium ,Slag ,Context (language use) ,Raw material ,Flue ,Corrosion - Abstract
Refractories are the essential lining materials for working interfaces and backup zone of furnaces during manufacturing of iron and steel, in specific sequential and consecutive operation of forming, holding, mixing and transporting hot metal, liquid steel and slag. Despite refractory-metal direct interactions, refractory has to successively experience high temperature and corrosive environment through flues, stack or shaft and ducts. In this context, this chapter deals with the classification and description of acidic, neutral and basic refractories for different environment and application zones for iron- and steel-making processes. Prior to considering the refractories, recent market trend, designing parameters including predominant mechanical and thermal behaviour are explicitly discussed to provide a better insight of the subject. Modern class of both shaped and unshaped refractories is highlighted starting from raw materials to installation practice. Refractory corrosion mechanism influenced by blast furnace slag, and primary and secondary steel-making slag, is analysed in order to understand and develop next-generation refractories.
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- 2020
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22. Treatment of Clayey Soils with Steel Furnace Slag and Lime for Road Construction in the South West of Iran
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Zahra Hosseinzadeh, Hadiseh Mansouri, and Ebrahim Asghari-Kaljahi
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Metallurgy ,Compaction ,Slag ,Atterberg limits ,engineering.material ,Compressive strength ,visual_art ,Steel mill ,Soil water ,visual_art.visual_art_medium ,engineering ,Environmental science ,Water content ,Lime - Abstract
The fine-grained soils of Arvand free zone in the south west of Iran contains more than 95% fine grained particles. These soils cannot be considered as a proper material for earth works due to problems caused by clay soils such as high expansive, volumetric shrinkage, high settlement under loading and high moisture absorption. Meanwhile, there are no coarse-grained soil resources for using in the earth works around in this area. Khuzestan steel plant makes enormous amount of steel furnace slag as waste product and is available for any use. This study evaluates the treatment of fine grained soil by adding steel furnace slag and lime. For this purpose, soil was mixed with 10, 20 and 30% slag and 2, 4 and 6% hydrated lime. After curing the mixed soil, the change in soil characteristics were tested through Atterberg limits, compaction, unconfined compressive strength (UCS) and CBR tests. The test results showed that the soil plasticity and optimum moisture content decrease and maximum dry density, UCS and CBR increase by increasing slag and lime. The UCS of the soil is 147 kPa in the maximum density and is reaching to 267, 417 and 456 kPa by adding 30% slag and 2, 4 and 6% lime, respectively. The soaked CBR tests indicated that adding 20% slag and 4% lime provide a CBR more than 30%. This mixture is suitable from technical and economical views and is recommended for soil treatment of the study area and using in earth works, such road construction.
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- 2019
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23. Pattern Extraction Using Proactive and Reactive Data: A Case Study of Contractors’ Safety in a Steel Plant
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C. S. Promod, Sobhan Sarkar, Jhareswar Maiti, and Numan Ejaz
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Naive Bayes classifier ,Work (electrical) ,Risk analysis (engineering) ,Computer science ,Hazardous waste ,Occupational accident ,Steel mill ,k-means clustering ,Audit ,Cluster analysis - Abstract
With the emergence of machine learning algorithms, a large amount of studies have been carried out in occupational accident analyses. Almost all of these previous studies have explored the analyses on workers’ safety. However, the analysis of contractors, an important part of any organization, is mostly ignored. The contractors are more exposed to hazardous situations at work rather than permanent workers due to the nature of their jobs. Hence, contractors’ safety is a vital issue for the safety perspective of any organization. To ensure their safety, the study proposes a methodology that uses both proactive data (i.e., contractor safety audit) and reactive data (i.e., investigation report) for analyzing the causes of incidents occurred. A tree-augmented Naive Bayes (TANB) algorithm is used to predict incident outcomes for contractors on the merged dataset obtained from both reactive and proactive datasets. In addition, based on the average number of violations and average severity, all the contractors are categorized into four types of clusters using k-means clustering algorithm. Results reveal that the proposed model is capable of showing effective results in extracting important patterns of occupational incidents.
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- 2019
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24. Forecast Scrap Generation and Emission Reduction of China’s Steel Industry
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Minxi Wang, Runbo Zhou, Xin Li, Yuhang Tian, Ya-nan Liang, and Yinda Luo
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Consumption (economics) ,Waste management ,Material flow analysis ,0211 other engineering and technologies ,Scrap ,02 engineering and technology ,010501 environmental sciences ,engineering.material ,01 natural sciences ,Iron ore ,Steel mill ,engineering ,Environmental science ,Production (economics) ,021108 energy ,China ,0105 earth and related environmental sciences ,Electric arc furnace - Abstract
The efficient recycling of metal resources will greatly reduce impact on environment. Analyzing the structures of steel manufacturing processes and evaluating the consumption of iron and steel scrap will provide support for China to increase the efficiency of steel resources recycling. Based on the dynamic material flow analysis (DMFA) method, the Weibull distribution was used in this paper to calculate the theoretical amount of old scrap in China from 1949 to 2025 according to historical consumption data. Compared with traditional processes, the EAF (Electric Arc Furnace) production has better energy-saving potential. The results showed that during 1949–2017, domestic cumulative consumption of iron resources was 7.72 billion tons, the average consumption of construction industry accounted for 58.4% of total social consumption, and the accumulated old scrap was 946 million tons. The accumulated quantity of old scrap accounted for only 12.4% of the total consumption. A great number of scrap will be generated in the future. By 2025, the total supply of steel scrap will be about 200 million tons, of which more than 80% will come from old scrap. In the scenario of the ratio of EAF production reach of 25%, 120 million tons of iron ore, 130 million tons of CO\(_2\) emissions and 57 million tons of solid wastes will be reduced.
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- 2019
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25. Recycling Steel Manufacturing Wastewater Treatment Solid Wastes via In-process Separation with Dynamic Separators
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Naiyang Ma
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Waste management ,chemistry ,business.industry ,Scientific method ,Steel mill ,chemistry.chemical_element ,Environmental science ,Sewage treatment ,Work in process ,business ,Carbon ,Steelmaking - Abstract
In steel manufacturing, various solid wastes are generated in wastewater treatment. Iron, carbon, and fluxes (CaO and MgO) are the main beneficial components in these solid wastes for recycling in the ironmaking and steelmaking process. However, the wastewater treatment solid wastes often also contain some undesirable components. Separation of those unwanted components from the wastewater treatment solid wastes is a prerequisite to recycle the solid wastes safely, economically, and environmentally. In this contribution, producing clean wastewater treatment solid wastes via dynamic separation at ArcelorMittal is reviewed and discussed, and some case studies are presented.
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- 2019
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26. Carbon Capture and Storage: Most Efficient Technologies for Greenhouse Emissions Abatement
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Pasquale Cavaliere and Cavaliere, Pasquale
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Waste management ,business.industry ,Greenhouse gas ,Steel mill ,Fossil fuel ,Carbon capture and storage ,Capital cost ,Environmental science ,Energy mix ,Energy consumption ,business ,Efficient energy use - Abstract
Steel production is a very energy-intensive process, and it requires large amounts of natural resources. In fact, energy costs account for up to 40% of the total cost in some countries. Therefore, optimizing process efficiency is one of the most effective ways to reduce energy consumption and lower costs, with the added benefit of reducing the steel industry’s impact on the environment. Iron and steel industry is the main CO2 emitter among the most CO2-intensive industrial sectors. The iron and steel industry accounts for about 19% of final energy use and about a quarter of direct CO2 emissions from the industry sector. The CO2 relevance is high due to a large share of coal in the energy mix. Unlike power plants, where CO2 is emitted from a single source, an integrated steel mill has multiple sources of CO2. The emissions are located at several stacks and occur from start to end of the iron and steel production. CCS is one of the most open fields for the reduction of greenhouse emissions in primary steelmaking. It is necessary for continuing to use fossil fuels. In the iron and steel industry, CCS faces many uncertainties regarding cost, efficiency, and technology choice. Obviously many solutions are under investigation to capture CO2 and to store it avoiding its emission in the atmosphere. Selection of capture equipment will depend on factors including CO2 capture rate, possible requirements for secondary gas treatment, energy consumption, reliability, and operational and capital costs. In the present chapter, the most innovative solutions related to energetic issues and off-gases type are described. The gas utilization depending on the plant section source and composition is underlined. The CO2 abatement potential and the various solutions costs are indicated.
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- 2019
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27. Tracking Efficiency of the Indian Iron and Steel Industry
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Aparna Sawhney and Piyali Majumder
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Waste management ,Steel mill ,Energy intensity ,Environmental science ,Scrap ,Energy consumption ,Raw material ,Track (rail transport) ,Poor quality ,Efficient energy use - Abstract
Recycling of steel scrap has been one of the key drivers of improving energy efficiency in steel manufacturing worldwide. Energy intensity of Indian steel plants is higher than the world average, and the strategy of scrap recycling to enhance energy efficiency has gained policy momentum. We track the energy intensity of Indian steel plants during the period 1999–2014, to determine whether scrap-use provided energy-saving benefits. We consider energy intensity as a function of various plant characteristics, while controlling for plant heterogeneity and industry sub-group (by 5-digit National Industrial Classification). We find that energy-intensity of Indian steel plants has declined significantly over the years, and more so for privately-owned steel plants, but the use of scrap in the production process has not helped reduce energy consumption. Indeed scrap users have lower energy-efficiency that may be driven by poor quality of raw materials which our analysis is unable to capture.
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- 2019
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28. Electric Arc Furnace: Most Efficient Technologies for Greenhouse Emissions Abatement
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Pasquale Cavaliere and Cavaliere, Pasquale
- Subjects
Waste management ,Pig iron ,business.industry ,Fossil fuel ,Scrap ,Energy consumption ,Direct reduced iron ,engineering.material ,Electricity generation ,Steel mill ,engineering ,Environmental science ,business ,Electric arc furnace - Abstract
In the electric arc furnace, steel is produced only through scrap fusion. Scraps, direct reduced iron, pig iron, and additives are melted through high-power electric arcs formed between a cathode and the anodes. The emissions levels are normally mainly related to the indirect emissions due to the high energy consumption of the process. The EAF process has become increasingly cost and quality competitive to the integrated steel mills through process and technology innovations, which have significantly lowered power consumption and increased productivity while satisfying the customers’ quality needs of steels. The appropriate GHG reduction strategy is strongly influenced by the source of electricity generation (i.e., fossil fuel or nuclear). Reduction of indirect GHG emissions requires reducing electrical energy consumption by such methods as burner optimization, post-combustion, scrap preheating, and other process efficiency measures. Other dangerous emissions are due to inorganic compounds such as iron oxide dusts and heavy metal and to organic compounds such as PCB and PCDD/Fs. The current trend towards increased addition of fuel and oxygen has resulted in chemical energy sources supplying a greater proportion of the furnace’s energy inputs. Potential fuel sources include natural gas, carbon, hydrocarbons, and iron carbide. Scrap quality is fundamental for the process efficiency, energy consumption, and steel quality. Oxyfuel burners utilization and flue gas utilization are described in this chapter. Scrap preheating techniques are employed to reduce the energy consumption. Bottom stirring and heat recovery are discussed.
- Published
- 2019
29. Construction and Practice on Energy Flow Network of New Generation Recyclable Iron and Steel Manufacturing Process
- Author
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Fuming Zhang
- Subjects
business.industry ,Circular economy ,Process (computing) ,chemistry.chemical_element ,chemistry ,Steel mill ,Energy flow ,Energy transformation ,Environmental science ,Production (economics) ,Process engineering ,business ,Carbon ,Waste disposal - Abstract
Shougang Jingtang iron and steel plant is a new generation recyclable iron and steel plant designed according to the concept and principle of circular economy. The steel plant is provided with the comprehensive functions of high quality steel product manufacture, high-efficiency energy conversion and waste disposal. In order to realize the cooperation and high efficiency of iron and steel manufacturing process, a full process energy flow network with carbon flow as the core is designed and constructed to realize energy high efficiency conversion and low carbon green manufacturing. Since Jingtang steel plant was put into production, the efficiency of energy conversion has been continuously improved, and remarkable results have been obtained in high-efficiency energy utilization and high value conversion. The emission of CO2 and pollutants has been greatly reduced, and cleaning production and low-carbon metallurgy have been realized.
- Published
- 2019
- Full Text
- View/download PDF
30. Stack Shuffling Optimization of Steel Bars by Using Genetic Algorithms
- Author
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Bojan Rupnik, Jakob Marolt, and Tone Lerher
- Subjects
Order picking ,Mathematical optimization ,Branch and bound ,Linear programming ,Computer science ,Steel mill ,Container (abstract data type) ,Production schedule ,Simulated annealing ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Overhead crane - Abstract
A steel plant company producing steel bars has large assortment of the end products, with similar appearance and attributes. The steel bars are stored on the floor in a stacking frame. For the order picking of steel bars, an overhead crane is used for reshuffling all the necessary steel bars to get access to the required product. While the production schedule allows for anticipating the storage occupancy, a stochastic transport arrival prevents optimal product stacking for efficient order-picking operation. Due to this, any order-picking sequence may require reshuffling of the stacked material, which increases working cost, order-picking times, and complicates material tracking. This paper presents a method for minimizing the order-picking times by overhead crane movements through proper reshuffling of the steel bars. Similar research was done on container yard pre-marshalling and reshuffling problem, while the presented approach handles with the special situation in the steel plant. Various optimization approaches including linear programming, simulated annealing, taboo search, branch and bound and genetic algorithms were used by researchers to solve comparable problems. The proposed method for solving the specific problem of reshuffling steel bars uses genetic algorithms to find a feasible solution in real-time. The proposed solution reduces intralogistics cost and increases order-picking efficiency.
- Published
- 2019
- Full Text
- View/download PDF
31. Deep Learning-Based Identification of Steel Products
- Author
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Li-Wei Kang, Wei Chen Jhong, Chao-Yung Hsu, and You Ting Chen
- Subjects
Production line ,0209 industrial biotechnology ,Engineering drawing ,Industry 4.0 ,business.industry ,Computer science ,media_common.quotation_subject ,Deep learning ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,02 engineering and technology ,Identification (information) ,020901 industrial engineering & automation ,Steel mill ,0202 electrical engineering, electronic engineering, information engineering ,Key (cryptography) ,020201 artificial intelligence & image processing ,Quality (business) ,Artificial intelligence ,business ,Feature learning ,media_common - Abstract
To achieve smart manufacturing in Industry 4.0 for steel industry (or Steel 4.0), this paper proposes a smart steel manufacturing framework, where a deep learning-based automatic identification tracking method for steel products is developed. Automatically online tracking and identifying steel products on a production line is essential for smart manufacturing management since those products might be frequently moved and processed everywhere on the product flow. Existing approaches usually rely upon marking or embedding a series of identification codes on the steel surfaces. However, steel-making is usually processed under a very high temperature environment, making it difficult to well embed the identification codes with acceptable quality for further automatically online recognizing them. To tackle this problem, this paper presents a vision-based automatic identification tracking method without needing to embed any identification codes onto the steel product surfaces. The key idea is to utilize the essential identity of a steel product without extrinsic information embedded, achieved by automatically and deeply learning visual features from the steel image. The presented preliminary results have verified the efficiency of the proposed method.
- Published
- 2018
- Full Text
- View/download PDF
32. Financial Valuation of Production Diversification in the Steel Industry Using Real Option Theory
- Author
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Bartłomiej Gaweł, Iwona Skalna, and Bogdan Rębiasz
- Subjects
Geometric Brownian motion ,Present value ,Stochastic process ,020209 energy ,Steel mill ,0202 electrical engineering, electronic engineering, information engineering ,02 engineering and technology ,Business ,Volatility (finance) ,Real options theory ,Industrial organization - Abstract
Steel industry is subject to significant volatility in its output prices and market demands for different ranges of products. Therefore, it is common practice to invest in various assets, which gives the opportunity to diversify production and generate valuable switch options. This article investigates the incremental benefit of product switch options in steel plant projects. The options are valued using Monte Carlo simulation and modeling the prices of and demand for steel products as Geometric Brownian Motion (GBM). Our results show that the product switch option can generate a significant increase in the net present value (NPV) of metallurgical projects.
- Published
- 2018
- Full Text
- View/download PDF
33. Development of the Odra River in the Context of Its Use for Conveying of Bulk Materials with Intermodal Transport Technologies
- Author
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Sylwester Markusik and Aleksander Sobota
- Subjects
Environmental protection ,business.industry ,Steel mill ,Sea transport ,Environmental science ,Context (language use) ,Coal ,Coke ,Inland navigation ,China ,business ,Transport corridor - Abstract
Demand for transport of bulk materials in the north-south relation and transport forecasts on this route, justify the launch of intermodal connection to customers located in the south of Europe, using the Baltic Adriatic Transport Corridor (CETC), the AGN network and the Oder waterway (E30). Transport of valuable bulk cargoes (coking coal, coke, fertilizers), exported from the Upper Silesia area, south to river, rail and sea transport to customers located in SouthEastern Europe, and even further, in Egypt, India, and in China (coking plants, steel mills).
- Published
- 2018
- Full Text
- View/download PDF
34. Steel Surface Defects Detection Based on Deep Learning
- Author
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Chih-Yang Lin, Wei-Yang Lin, Chao-Yung Hsu, and Guan-Shou Chen
- Subjects
Surface (mathematics) ,business.industry ,Computer science ,Deep learning ,fungi ,Binary number ,Wavelet transform ,Feature selection ,Pattern recognition ,Quality enhancement ,Steel mill ,Segmentation ,Artificial intelligence ,business - Abstract
Surface defects detection plays a significant role in quality enhancement in steel manufacturing. However, manual inspection of steel surface slows down the entire manufacturing process and is time consuming. Currently, many methods have been proposed for automatic defect detection on hot-rolled steel surfaces. These methods usually follow two steps: pre-processing and segmentation. The pre-processing step is intended to overcome the uneven illumination of images while the segmentation step generates a binary map to identify defects. This kind of method heavily depends on feature selection approaches, but the defect features are usually not easy to obtain. In this paper, we propose an automatic steel surface defects detection method based on deep learning. Two deep learning models for defect detection are evaluated. The experimental results show that the evaluated methods can detect steel surface defects more effectively and accurately than the traditional methods. This approach can be also applied to other industrial applications.
- Published
- 2018
- Full Text
- View/download PDF
35. A Review of Simulation Usage in the New Zealand Electricity Market
- Author
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Golbon Zakeri and Geoff Pritchard
- Subjects
Demand response ,Consumption (economics) ,business.industry ,Steel mill ,Electricity market ,Electricity ,Environmental economics ,business - Abstract
In this chapter, we outline and review the application of simulation on the generation offer and consumption bids for the New Zealand electricity market (NZEM). We start by describing the operation of the NZEM with a particular focus on how electricity prices are calculated for each time period. The complexity of this mechanism, in conjunction with uncertainty surrounding factors such as consumption levels, motivates the use of simulation. We will then discuss simulation–optimization methods for optimal offer strategies of a generator, for a particular time period, in the NZEM. We conclude by extending our ideas and techniques to consumption bids and interruptible load reserve offers for major consumers of electricity including large manufacturers such as the steel mill.
- Published
- 2018
- Full Text
- View/download PDF
36. Research of Digital Platform and Process Guidance Model in EAF Steelmaking Process
- Author
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Guangsheng Wei, Rong Zhu, Kai Dong, and Yang Lingzhi
- Subjects
business.industry ,Computer science ,Process (computing) ,Information technology ,02 engineering and technology ,021001 nanoscience & nanotechnology ,Steelmaking ,020501 mining & metallurgy ,0205 materials engineering ,Steel mill ,Component (UML) ,Process control ,0210 nano-technology ,business ,Process engineering ,Electric arc furnace ,Information integration - Abstract
As a shortage of information technology support, steel plant is unable to real-time tracking production cost of each working procedure, and can’t form the information feedback in time. Information integration technology for dynamic monitoring becomes a development trend of process control in advanced iron and steel enterprise. The paper based on the characteristics of EAF steelmaking process and requirements build the digital platform and process guidance model, which is designed to solve for smelting composition control, cost control, and optimizing guide in EAF steelmaking process. The model is including: data acquisition module, cost monitoring and calculation module, EAF endpoint carbon control module, alloy material optimization module, component monitoring and forecast module, process guidance module, data maintenance and query module.
- Published
- 2018
- Full Text
- View/download PDF
37. ‘De proletarios a propietarios…’ Neoliberal Hegemony, Labour Commodification, and Family Relationships in a ‘Petty’ Steel Workers’ Firm
- Author
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Julia Soul
- Subjects
Proletariat ,Labour economics ,060101 anthropology ,Delegate ,Hegemony ,Commodification ,media_common.quotation_subject ,05 social sciences ,0507 social and economic geography ,06 humanities and the arts ,050701 cultural studies ,Working class ,Steel mill ,Political science ,Ethnography ,0601 history and archaeology ,Steel workers ,media_common - Abstract
The chapter discusses the working class dynamic in Argentina, through an ethnographic approach to a group of steel workers of the former state owned steel mill. The analysis focuses on one of the microfirms, the first one with a union delegate elected by its employees. In the interplay between the daily experience of labor subsumption and domination that subcontracted workers experience, and the improvement in wages and working conditions that direct workers obtain through the union, young workers abandon entrepreneur expectations and assume the proletarian ones. Thus, the new working-class generation is part of an uneven and slow process of class reorganization, involving the struggle for the improvement of daily labor relationships.
- Published
- 2018
- Full Text
- View/download PDF
38. A Laboratory Study and Full-Scale Testing of Brex in Direct Reduction Iron (DRI) Production
- Author
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Ivan Kurunov and Aitber Bizhanov
- Subjects
Continuous casting ,Mill scale ,Briquette ,Waste management ,Steel mill ,digestive, oral, and skin physiology ,technology, industry, and agriculture ,Pellets ,Environmental science ,Production (economics) ,Raw material ,Pelletizing ,complex mixtures - Abstract
The process of mini steel mills using oxidized pellets as a feedstock includes production of metallized pellets, which are used further for the production of direct reduction iron (DRI), production of steel in electric arc furnaces (EAF), and its continuous casting and rolling. Companies that are importing large amounts of iron ore pellets annually for DRI production and also during the course of the transportation, stockpiling, and charging of the pellets into metallization reactors, as well as the discharging of the metallized pellets, generate tens of thousands of tons of fine materials containing iron every year. Pellets fines and DRI sludge are usually dumped in piles and EAF dust and mill scale are sold to a third party. The results of a preliminary analysis indicate that the recycling of such materials in the form of briquettes would help to produce additional quantities of steel, and would also free up a significant area occupied by dumped wastes. Recovery of these wastes would generate additional revenues, surpassing revenue from direct sales of wastes.
- Published
- 2017
- Full Text
- View/download PDF
39. Haze-Related Air Pollution and Impact on the Stock Returns of the Listed Steel Companies in China
- Author
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John Thomas Delaney, Kai Liu, and Ying Li
- Subjects
Finance ,050208 finance ,Financial economics ,business.industry ,05 social sciences ,Operating margin ,Net asset value ,Air Pollution Index ,Steel mill ,0502 economics and business ,Profitability index ,Stock market ,Business ,050207 economics ,Air quality index ,Stock (geology) - Abstract
The purpose of this paper is to study the effects of air pollution, especially the haze, on the stock returns of steel mills. This study collects data from air quality index, variables represent characteristic of the eleven steel mills in China and the stock returns ratio from the stock market etc. SPSS19.0 is utilized to conduct a descriptive analysis of the correlation between the principal air pollution(including PM\(_{2.5}\), PM\(_{10}\)), the variables represent charactering(monetary funds, net assets, liabilities, operating margin, financial leverage, and total asset growth) of the elven steel mills in China and the stock returns ratio from the stock market etc. Hence, through the research on the air pollution index, analysis of the listed company’s earnings and stock price, and by using the linear regression analysis method, research shows that the serious air pollution have a negative impact on the profitability of iron and steel enterprises through the emotion and expectations of investors. It is imperative for people to tackle air pollution urgently.
- Published
- 2017
- Full Text
- View/download PDF
40. Quality Assurance Production Based Problem: A Process Improvement in the Rolling Mill Line for Steel Manufacturing Company in the Philippines
- Author
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Yoshiki B. Kurata, Tennessee N. Pening, Darrel B. Cedron, Marjorie R. Navales, and Michael J. Marcelino
- Subjects
Production line ,Downtime ,Engineering ,business.industry ,Process (engineering) ,Steel mill ,Production (economics) ,business ,Work sampling ,Productivity ,Quality assurance ,Industrial engineering ,Manufacturing engineering - Abstract
Productivity among manufacturing production lines can be considered as a crucial part since this can result in an improved production and utilization of the available resources. Competition intensifies and this compels engineers to continually seek for process improvement. Process improvement denotes to turning a process to more effective, efficient, and transparent. As for the steel manufacturing company, one major concern is the downtime occurrences which had a large impact on their productivity. Necessary data were gathered through problem solving tools to show the company’s present condition. To reduce the clerical time needed, work sampling was utilized. It has been found out that the company cannot keep up with the projected production run and failed to produce forty (40) metric tons per hour. From the present methods, proposed methods were made by the researchers to solve the existing problems in the company resulting to less downtime savings, increase the efficiency of the plant and the operator, and increase their productivity per unit of time.
- Published
- 2017
- Full Text
- View/download PDF
41. Stalinist Vision for Economy and Environment in Hungary in the 1950s
- Author
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Viktor Pál
- Subjects
Industrialisation ,Economy ,Political science ,Five year plan ,Steel mill ,Context (language use) ,Industrial district ,Water scarcity - Abstract
In this chapter Pal explains the economic and technological context of Stalinist industrialization in Hungary. He concentrates on the First Five Year Plan in Hungary, and points out the environmental aspect of that rapid economic and industrial program. Pal focuses on local impacts of Stalinist industrialization and he analyses the economic, technological, and environmental changes in Hungary’s primate industrial district built by the communists in the Borsod Basin, Northeast Hungary. He analyses the dynamics of water shortage and water pollution in the Borsod Basin. At the end of this chapter Pal analyzes the communists’ economic and technological measures to curtail pollution issues by focusing on the Lenin Metallurgical Plan in Diosgyőr, one of Hungary’s largest steel mills.
- Published
- 2017
- Full Text
- View/download PDF
42. Influence of Ruhrstahl Heraeus Refining Process on Aluminum Consumption in Interstitial-Free Steel Smelting Process
- Author
-
Siyuan Zhang, Lu Lin, Yan-ping Bao, Wei Xiao, and Chaojie Zhang
- Subjects
Materials science ,chemistry ,Aluminium ,Scientific method ,Steel mill ,Metallurgy ,Deoxidization ,chemistry.chemical_element ,Smelting process ,Positive correlation ,Oxygen ,Refining (metallurgy) - Abstract
In order to decrease high aluminum consumption in Interstitial-Free (IF) steel production in a steel plant, Ruhrstahl Heraeus (RH) process data from 2428 heats were analyzed by statistical methods. The results showed that the blowing oxygen quantity and oxygen activity, before the RH and before deoxidization, have positive correlations with aluminum consumption, especially the blowing oxygen quantity. Waiting time before refining also has a positive correlation with aluminum consumption when it exceeds 7 min. On the contrary, steel temperature before RH has a significant negative correlation with aluminum consumption, when it is between 1600 and 1630 °C. According to the statistical results, the RH refining process was optimized when the steel temperature before RH was controlled between 1630 and 1645 °C, waiting time was controlled at less than 7 min, blowing oxygen quantity was controlled to less than 100 m3, and the oxygen activity before RH was controlled between 0.050–0.075%. After optimization, the reduction of aluminum consumption was remarkable. Average aluminum consumption decreased from 1.45 to 1.17 kg/t steel.
- Published
- 2017
- Full Text
- View/download PDF
43. Prediction and Optimal Scheduling of Byproduct Gases in Steel Mill: Trends and Challenges
- Author
-
Qi Shi, Zhancheng Guo, Xiancong Zhao, and Hao Bai
- Subjects
Engineering ,Key factors ,business.industry ,Production cost ,Steel mill ,Optimal scheduling ,Scheduling (production processes) ,business ,Process engineering ,Energy source ,Steelmaking ,Manufacturing engineering ,Optimal management - Abstract
Byproduct gases generated during the iron and steel making process are important energy sources in steel plant, which accounted for 30% of total energy consumption. With the increasing need for production cost control in steel industry, the refined management of byproduct gases has become prominent. The prediction and optimal scheduling of byproduct gases are two key factors in the optimal management of byproduct gases. However, due to the complexity and dispersivity of byproduct gas generation and consumption, it is difficult to build a comprehensive and reasonable prediction and scheduling model. This paper reviews current methods in the prediction and scheduling of byproduct gas system and discusses some of the key factors and opportunities in improving the model. Emerging trends that are likely to influence the current or future byproduct gas prediction and scheduling are also discussed.
- Published
- 2017
- Full Text
- View/download PDF
44. Green Manufacturing Process of Shougang Jingtang Steel Plant
- Author
-
Jianxin Xie and Fuming Zhang
- Subjects
Production line ,business.industry ,Steel mill ,Circular economy ,Environmental science ,Energy consumption ,business ,Green manufacturing ,Process engineering ,Engineering design process ,Steelmaking - Abstract
Shougang Jingtang Steel Plant is the project which is built based on the concept of new generation recycling iron and steel process, with characteristics of “three functions”, namely iron and steel product manufacture, high efficient conversion of energy, and disposal of wastes by reutilization. In engineering design, on the strength of theory of metallurgical process engineering, the advanced iron and steel manufacturing process of static process structure has been established by construction of two blast furnaces, one steel making plant and two hot rolling production lines, the advanced interface technology on ironmaking and steelmaking process has been developed, and the complete process of energy flow networking framing technology has been created. Energy consumption is reduced, with sufficient recovery of gas, heat and surplus energy during iron and steel manufacturing process, as well as emission reduction of dust and pollutant so as to achieve green iron and steel manufacturing and recycling economy, and energy utilization efficiency has an outstanding improvement. This paper introduces the green iron and steel manufacturing process of Shougang Jingtang Iron & Steel Plant, and establishment of its energy flow network.
- Published
- 2017
- Full Text
- View/download PDF
45. Industrial Chemistry of Steel
- Author
-
Rama Bommaraju
- Subjects
Engineering ,Pig iron ,business.industry ,Metallurgy ,Pie chart ,Industrial chemistry ,engineering.material ,Manufacturing engineering ,Steelmaking ,law.invention ,law ,Steel mill ,business ,Physical metallurgy - Abstract
This chapter on the Industrial Chemistry of Steel is a general overview of steel, its manufacturing and usage. A significant amount of the material in this chapter is presented in a tabular form and/or pie charts for the sake of brevity and clarity. There are several publications (Coudurier et al., Fundamentals of metallurgical processes; SIms, Electric furnace steelmaking, vol II: theory and fundamentals; Lankford et al., The making, shaping and treating of steel, United States steel; Gaines, BOF steel making, vol 1, introduction, theory and design Part 1; Clark and Varney, Physical metallurgy for engineers), monographs and brochures in the open literature covering almost all aspects of steel manufacturing. The interested reader is referred to that published literature for an in-depth understanding of the technology and further details.
- Published
- 2017
- Full Text
- View/download PDF
46. Hybrid Associative Classification Model for Mild Steel Defect Analysis
- Author
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S. V. Patel and Veena N. Jokhakar
- Subjects
Association rule learning ,Computer science ,business.industry ,Machine learning ,computer.software_genre ,Random forest ,Distance correlation ,Causality (physics) ,Electromagnetic coil ,Steel mill ,A priori and a posteriori ,Artificial intelligence ,business ,computer ,Algorithm ,Associative property - Abstract
Quality of the steel coil manufactured in a steel plant is influenced by several parameters during the manufacturing process. Coiling temperature deviation defect is one of the major issues. This defect causes steels metallurgical properties to diverge in the final product. In order to find the cause of this defect, various parameter values sensed by sensors are stored in database. Many approaches exist to analyze these data in order to find the cause of the defect. This paper presents a novel model HACDC (Hybrid Associative Classification with Distance Correlation) to analyze causality for coiling temperature deviation. Due to the combination of association rule, distance correlation and ensemble techniques we achieve an accuracy of 95 % which is quite better than other approaches. Moreover, to the best of our knowledge, this is the first implementation of random forest algorithm in analyzing steel coil defects.
- Published
- 2016
- Full Text
- View/download PDF
47. Optimization and Management of Byproduct Gas Distribution in Steel Mills Under Time-of-Use (TOU) Electricity Price
- Author
-
Xiancong Zhao, Hao Bai, Qi Shi, and Zhancheng Guo
- Subjects
Microeconomics ,Product (business) ,Electricity generation ,Electricity price ,business.industry ,Steel mill ,Economics ,Distribution (economics) ,Electricity ,Environmental economics ,Time of use ,business ,Integer programming - Abstract
Reducing electricity cost is important for energy intensive industries such as the iron and steel industry. With the implementation of time-of-use (TOU) electricity price, plenty of attention has been paid to the optimal management of byproduct gases. The time-of-use (TOU) electricity price is the practice of implementing different prices for different times of use. It is possible to reduce electricity cost by adjusting the amount of product gases stored or used for power generation throughout the day. In this paper, a novel mixed integer linear programming (MILP) model concerning the TOU electricity price is proposed to optimize byproduct gas use. Compared with previous models, this model considers the optimal load shift between gasholders and boilers under TOU electricity price. The case study of a steel plant demonstrates that the electricity purchase cost can be reduced by more than 30% after optimization.
- Published
- 2016
- Full Text
- View/download PDF
48. Recent Progress and Future Trends of CO2 Breakthrough Iron and Steelmaking Technologies for CO2 Mitigation
- Author
-
Raja Ariffin Raja Ghazillaa, Shamsuddin Ahmed, and M. Abdul Quader
- Subjects
Engineering ,business.industry ,Management science ,020209 energy ,Global warming ,0211 other engineering and technologies ,Economic feasibility ,02 engineering and technology ,Environmental economics ,Steelmaking ,Steel mill ,Greenhouse gas ,0202 electrical engineering, electronic engineering, information engineering ,Environmental impact assessment ,business ,021102 mining & metallurgy ,Efficient energy use - Abstract
Iron and steel manufacturing is one of the most energy-intensive and CO2 emitting industries in the world. In order to contribute to the prevention of global warming, the reduction of CO2 from the steel works becomes a major issue imposed on the steel industry. A number of technologies have been developed in the past decade under worldwide CO2 breakthrough program for the reduction of carbon emissions. This chapter focuses on present needs, recent progress, and future trends of energy efficient new iron and steelmaking technologies. This study presents a comparative analysis of CO2 breakthrough programs including the present technological development and effects of application, economic feasibility, and environmental impact assessment. In addition, a brief analysis on ULCOS innovative ironmaking technologies has been done. Finally, significant CO2 reductions can be achieved by combining a number of the available energy efficient technologies with Bio-CCS.
- Published
- 2016
- Full Text
- View/download PDF
49. Technological Methods to Protect the Environment in the Ukrainian BOF Shops
- Author
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I. V. Synegin, L. S. Molchanov, and B. M. Boichenko
- Subjects
Waste management ,business.industry ,Condensation ,Scrubber ,chemistry.chemical_element ,Raw material ,Steelmaking ,chemistry ,Hazardous waste ,Steel mill ,Venturi effect ,Environmental science ,business ,Carbon - Abstract
BOF process is one of the most productive ways of steel manufacturing. Byproducts of this process are metallurgical slag, gases (volatile-rich oxide and other chemical compounds), metallurgical dust, and excessive heat. Nevertheless there are developed a large number of waste gas cleaning systems and recycling technologies, these factors still have negative impact on whole biosphere. The greatest effect it makes on the atmosphere since during melting, a substantial amount of carbon and nitrogen oxides are released into the environment. The steelmaking dust can be classified by its origin. The main types of waste dust include: fragments of the raw material (as a result of technological overload and crushing of the raw materials), products of evaporation and condensation (vaporized molten slag and graphite ripe). For their capture in conditions of Ukrainian manufacturing developed a number of specific technological schemes involving precipitation of dust component in special units (Venturi tubes, cyclones, and scrubbers). Their use can reduce the concentration of hazardous substances and to the regulated legal framework limit.
- Published
- 2016
- Full Text
- View/download PDF
50. CFD Modeling of a Ladle with Top Stirring Lance
- Author
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Bin Wu, Hoyong Hwang, Megan Pratt, Haibo Ma, Xia Chen, Chenn Q. Zhou, Russel J. Mulligan, and Guangwu Tang
- Subjects
Ladle ,Materials science ,business.industry ,Steel mill ,Flow (psychology) ,Metallurgy ,Multiphase flow ,Volume of fluid method ,Transient (oscillation) ,Computational fluid dynamics ,Process engineering ,business ,Steelmaking - Abstract
Steel cleanliness is very important for the quality of final products. Stirring ladles have been widely used to ensure the good quality steel produced from liquid iron in steelmaking industry. Proper stirring is crucial for obtaining clean steel. In this study, three-dimensional computational fluid dynamics (CFD) technique is used to study the transient multiphase flow inside a working ladle at a steel plant. The study presents a comparison of three different methods to model multi phase flow, i .e. the volume of fluid (VOF) method, the Eulerian-Eulerian method, and the Eulerian-Lagrangian method. The simulation results are compared with ex perimental data obtained from a working ladle. The best simulation method, which gives the most accurate results within a reasonable amount of computational time, will be applied to optimize operating parameters under various conditions.
- Published
- 2016
- Full Text
- View/download PDF
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