Multicriterial optimization of the batch composition for steel-smelting arc furnaces

Логунова, О. С.; Филиппов, Е. Г.; Pavlov, I. V.; Pavlov, V. V.

doi:10.3103/s0967091213010051

Cited by 8 publications

(4 citation statements)

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“…The disadvantages of the mathematical models given in [4][5][6] are: 1) the model is limited by the conditions of steel melting for one type of EAF: EAF-180; 2) the limited number of constituents of charge materials with basic raw materials (scrap metal, liquid and solid cast iron, hot briquetted iron);…”

Section: Components Of the Deterministic And Stochastic Model Of The mentioning

confidence: 99%

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Deterministic and Stochastic Model in the Structuring of Batch Within an Arc Furnace for Multi Objective Optimization

Sibileva¹,

Логунова²,

Kuhta³

2017

dtetr

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Abstract. The traditional technology of preparation of charge materials does not include an intellectual component and is conducted only on the basis of an evaluation of the results of an industrial experiment. This study has the following purpose: increasing the efficiency of the steelmaking process in large capacity arc furnace on the basis of implementation a new decision-making system about the composition of charge materials. Authors proposed a diagram of an interactive intelligent builder which is capable to solve problems of optimizing the composition of charge materials in the presence of several different targets.

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Section: Components Of the Deterministic And Stochastic Model Of The mentioning

confidence: 99%

“…In [4][5][6], the authors considered mathematical models for the selection of the structure of charge materials:…”

Section: Components Of the Deterministic And Stochastic Model Of The mentioning

confidence: 99%

Deterministic and Stochastic Model in the Structuring of Batch Within an Arc Furnace for Multi Objective Optimization

Sibileva¹,

Логунова²,

Kuhta³

2017

dtetr

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“…In the present work, we develop recommendations regarding energy efficient arc furnace smelting with variation in batch composition, in the light of experi ence with batch optimization in [7][8][9]. This entails monitoring the operation of ac arc furnaces when In addition, on the basis of the information, we cal culate the total mass of batch in the metal charge; the proportion of each batch component in the total mass; and the proportion of solid phase in the metal charge.…”

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confidence: 99%

Selecting the batch composition in arc furnaces for energy-saving operation

2014

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Monitoring of the energy consumption in an arc smelting furnace when using various materials permits the optimization of the batch composition. To this end, the corresponding multicriterial optimization problem is analyzed, and a method is proposed for determining the energy saving batch composition. This method consists of six main steps, including the following: collection and organization of the technological information; plotting of cause and effect diagrams; and description of the electrical consumption by means of a multicriterial optimization problem containing a system of constraints with empirical coefficients.

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“…When building the system, there is a need for the organization and maintenance of specialized software for an automated system of technical preparation of production, including the formation of a database with a ready-made solutions [9]. Compliance with the requirements for the chemical composition of steel, the cost of finished products, the saving of energy resources leads to the formulation of disparate tasks of multi-criteria optimization that do not have a relationship between the obtained solutions [10][11][12][13]. That is why, there is a need to create a system of continuous monitoring and process management [5], which requires automation of management processes and decisionmaking in the automated mode at all stages of metallurgical operations.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Support System of Steel Technical Preparation in an Arc Furnace: Functional Scheme of Interactive Builder of the Multi Objective Optimization Problem

Логунова

Sibileva

2017

IOP Conf. Ser.: Mater. Sci. Eng.

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Artificial neural networks in predicting current in electric arc furnaces M Panoiu, C Panoiu, A Iordan et al. The purpose of the study is to increase the efficiency of the steelmaking process in large capacity arc furnace on the basis of implementation a new decision-making system about the composition of charge materials. The authors proposed an interactive builder for the formation of the optimization problem, taking into account the requirements of the customer, normative documents and stocks of charge materials in the warehouse. To implement the interactive builder, the sets of deterministic and stochastic model components are developed, as well as a list of preferences of criteria and constraints.

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Multicriterial optimization of the batch composition for steel-smelting arc furnaces

Cited by 8 publications

References 0 publications

Deterministic and Stochastic Model in the Structuring of Batch Within an Arc Furnace for Multi Objective Optimization

Deterministic and Stochastic Model in the Structuring of Batch Within an Arc Furnace for Multi Objective Optimization

Selecting the batch composition in arc furnaces for energy-saving operation

Intelligent Support System of Steel Technical Preparation in an Arc Furnace: Functional Scheme of Interactive Builder of the Multi Objective Optimization Problem

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