Abstract
This work presents a multiobjective optimization model to support the assembly of the raw materials budget for blast furnaces consumption in the production of pig iron, the main material for steelmaking. Given a set of materials and fabrication constraints, such as materials availability, their chemical compositions, the required features for the final product, etc, the objective of the model is to determine the amount of each material that generates the lowest cost solution with minimum wasteful. Due to conflicting objectives, defined by fabrication cost and slag rate, and based on characteristics of decision variables that formulate the problem, some of them in percentage form, an evolutionary multi-objective model has been developed associated with a projection onto a simplex technique aiming to improve the encoding of the genetic solutions. This projection is used in the genetic algorithm-based evolutionary model, wherein each new generated individual, their genes with percentage values are projected onto a simplex, a Euclidean space where the sum of all variables is the unit. The projection allows an intrinsic strategy to deal with percentage constraint of the model variables, increasing significantly the number of feasible individuals generated by the evolutionary procedure. The model has shown to be very effective and useful in determining several scenarios to support decisions making for the raw materials budget.
Highlights
The fabrication of pig iron is a highly complex process and is responsible for the majority of production expenses
The blast furnace is the most important equipment and has the objective to withdraw the oxygen from iron oxides, making a metallic metal with high iron content named pig iron
It is important to stand out that the blast furnace steelmaking route is the primary source for worldwide steel production, since the electric arc process route consumes a huge amount of electrical energy, which impacts on production cost (COUDURIER; HOPKINS; WILKOMIRSKY, 1985)
Summary
The fabrication of pig iron is a highly complex process and is responsible for the majority of production expenses. Several challenges appear in the optimization of this operation, such as logistic problems, supplying chain, burden scheduling, and selection of the raw materials. The raw materials loaded to blast furnace are the metallic burden (iron ore, pellets, sinter), limestone (bauxite, calcite, dolomite), and fuel (coke or coal). The first provides iron, the second is responsible for removing impurities from the metallic burden, producing the slag, and the last provides heat and energy inside the furnace. A wide range of materials, with different chemical compositions are available for acquisition, providing many combinations that can satisfy all product requirements and guarantee the stability of the process at affordable prices. The selection of a costeffective arrangement is not an easy task since when purchasing materials, aspects such as availability of the material, their chemical compositions, supplier contract demands, storage condition, etc, should take into account. The optimization model determines several potential mixtures, allowing a post-decision by the specialist according to the production demands
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