Distribution plan creation device, distribution plan creation method, and operation method of a steel mill

Abstract

The present invention provides a distribution planning device, a distribution planning method, and a steel mill operation method that can evaluate the cost of processing impurities and optimize the distribution of raw materials to each manufacturing site. [Solution] The distribution plan creation device includes: an input data acquisition unit (101) that acquires input data which is data relating to the purchase quantity and components of raw materials and the production plan at each of the multiple manufacturing sites; a cost calculation unit (102) that evaluates the distribution of raw materials based on the input data using the cost of removing impurities at each of the multiple manufacturing sites; a constraint creation unit (103) that creates a constraint condition that the sum of the amounts of the main components of the raw materials determined based on the production plan at each of the multiple manufacturing sites is within the range of the purchase quantity of raw materials; a plan creation unit (104) that creates an optimized distribution plan that satisfies the constraint condition; and an output unit (105) that outputs the optimized distribution plan.

Description

[Technical Field]

[0001] This disclosure relates to an allocation plan creation device, an allocation plan creation method, and a method for operating a steel mill. In particular, this disclosure relates to an allocation plan creation device, an allocation plan creation method, and a method for operating a steel mill for optimizing the allocation of raw materials in a steel mill. [Background technology]

[0002] In the steel industry, manufacturers have multiple production bases (steel mills) within the country and import large quantities of raw materials, including iron ore, from abroad and distribute them to each mill. Many proposals have been made regarding the procurement and distribution of raw materials in the steel industry. For example, technologies have been proposed that improve efficiency by conducting simulations using operational plans and equipment capacity as inputs and reflecting the simulation results in operations.

[0003] For example, Patent Document 1 proposes optimizing operations at a single steelworks by combining models of a smelting plant and a steelmaking plant via the amount of iron tapped and the molten iron component. For example, Patent Documents 2 and 3 propose methods for finding an exact optimal solution when the constraints of each steelworks include nonlinear ones, by methods such as repeatedly solving local linear programming problems. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2005-055997 [Patent Document 2] Japanese Patent Publication No. 2016-081195 [Patent Document 3] Japanese Patent Publication No. 2013-254329 [Overview of the project] [Problems that the invention aims to solve]

[0005] Generally, when steel products are manufactured at multiple steel mills, the equipment at each mill is not identical, and there are differences in manufacturing capacity or processing equipment. For example, the capacity of equipment for removing impurities differs at each mill, and processing costs also differ at each mill. Therefore, if the processing costs of such impurities are not considered when allocating raw materials, it is not possible to minimize the overall cost. Patent documents 1 to 3 do not examine the processing costs of such impurities. Here, impurities refer to components such as P, Si, and S contained in iron ore that need to be removed during the refining process.

[0006] This disclosure is made in view of these circumstances and aims to provide an allocation plan creation device, an allocation plan creation method, and a steel mill operation method that can evaluate the cost of processing impurities and optimize the allocation of raw materials to each manufacturing site. [Means for solving the problem]

[0007] (1) An allocation plan creation device according to one embodiment of the present disclosure is A distribution plan creation device that creates a distribution plan, which is a plan for distributing raw materials to multiple manufacturing sites, An input data acquisition unit acquires input data which is data relating to the purchase quantity and composition of the raw materials and the production plan at each of the multiple manufacturing sites. A cost calculation unit evaluates the distribution of the raw materials based on the input data, using the cost of removing impurities at each of the multiple manufacturing sites. A constraint creation unit calculates the amount of the main component of the raw materials determined based on the production plan at each of the multiple manufacturing sites, and creates a constraint condition that the sum of the amounts of the main component at each of the multiple manufacturing sites is within the range of the raw material purchase quantity. A planning unit that creates an optimized allocation plan that satisfies the aforementioned constraints, The system includes an output unit that outputs the optimized allocation plan.

[0008] (2) As one embodiment of the present disclosure, in (1), The apparatus further includes an objective function creation unit that creates an objective function including the total cost at the plurality of manufacturing bases. The planning unit sets the distribution plan that minimizes the objective function as the optimized distribution plan.

[0009] (3) The distribution plan creation method according to an embodiment of the present disclosure is a distribution plan creation method executed by a distribution plan creation apparatus that creates a distribution plan that is a plan for distributing raw materials to a plurality of manufacturing bases, an input data acquisition step of acquiring input data that is data related to the purchase amount and components of the raw materials and the production plan at each of the plurality of manufacturing bases; a cost calculation step of evaluating the distribution of the raw materials using the cost for removing impurities at each of the plurality of manufacturing bases based on the input data; a constraint condition creation step of calculating the amount of the main component of the raw materials determined based on the production plan at each of the plurality of manufacturing bases and creating, as a constraint condition, that the total amount of the main components at each of the plurality of manufacturing bases is within the range of the purchase amount of the raw materials; a planning step of creating the optimized distribution plan that satisfies the constraint condition; and an output step of outputting the optimized distribution plan.

[0010] (4) As an embodiment of the present disclosure, in (3), the method further includes an objective function creation step of creating an objective function including the total cost at the plurality of manufacturing bases, and the planning step sets the distribution plan that minimizes the objective function as the optimized distribution plan.

[0011] (5) The operation method of a steelworks according to an embodiment of the present disclosure is distributing the raw materials based on the optimized distribution plan created by the distribution plan creation method of (3) or (4), and the raw materials are iron ores having Fe as a main component.

Advantage of the Invention

[0012] According to the present disclosure, it is possible to provide a distribution plan creation device, a distribution plan creation method, and an operation method of a steelworks that can evaluate the impurity treatment cost and optimize the distribution of raw materials to each manufacturing site.

Brief Description of the Drawings

[0013] [Figure 1] FIG. 1 is a diagram showing a schematic configuration of a distribution plan creation device including its relationship with a higher-level system. [Figure 2] FIG. 2 is a diagram showing improvements in an embodiment.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, a distribution plan creation device, a distribution plan creation method, and an operation method of a steelworks according to an embodiment of the present disclosure will be described with reference to the drawings. The distribution plan creation device and the distribution plan creation method according to the present embodiment are applicable to creating a plan for distributing raw materials to a plurality of manufacturing sites in the manufacturing industry, and do not limit the manufacturing industry and the types of raw materials. However, hereinafter, an example of distributing iron ore (an example of raw material) to a plurality of steelworks (an example of manufacturing sites) in the steelmaking industry (an example of the manufacturing industry) will be described.

[0015] As described above, in the steelmaking industry, iron ore imported from abroad is distributed to each steelworks. The iron ore arriving at the steelworks is blended to have a desired composition and charged into a sintering machine or a blast furnace. The iron ore is distributed so as to satisfy the production plan of each steelworks. The production volume of each steelworks can be treated as being determined in advance if there is no influence of unplanned troubles. Therefore, the amount of the main component of iron ore required by each steelworks, that is, the amount of Fe, is determined in the production plan in advance.

[0016] Furthermore, long-term contracts are made in advance for the purchase of iron ore, often several months ahead. Therefore, when creating an allocation plan, the amount of iron ore to be purchased is often already determined. In other words, among the costs related to the allocation of iron ore, the purchase cost (the cost of purchasing iron ore) can be treated as constant overall, regardless of how the iron ore is allocated to the steelworks. Also, if we ignore short-term fluctuations and consider the transportation of iron ore to each steelworks over the long term, the logistics cost (the cost of transporting iron ore) can also be treated as constant overall, since the amount of iron ore to be purchased and the amount required by each steelworks are already determined.

[0017] Here, the equipment at each steelworks is not identical, and there are differences in manufacturing capacity or processing equipment. The capacity of the equipment for removing impurities also differs at each steelworks, and processing costs vary from one steelworks to another. From a long-term perspective, the processing costs for removing impurities such as P, SiO2, or Al2O3 after iron ore blending also differ at each steelworks and vary greatly depending on the iron ore distribution. Therefore, when creating a plan to optimize the allocation to each steelworks in order to minimize overall costs, it is necessary to consider the impurity removal capacity at each steelworks. For example, by concentrating varieties with high impurity content at steelworks where the cost of impurity removal is lower compared to other steelworks, the overall allocation of iron ore can be optimized.

[0018] In the following explanation, costs are assumed to be monetary costs. However, costs are not limited to monetary costs and may include time costs and costs related to production efficiency. Time costs may, for example, be the work time required to remove a certain amount of impurities. Costs related to production efficiency may, for example, be the man-hours (the value obtained by multiplying the number of workers by the time) or the amount of electricity required to remove a certain amount of impurities. Therefore, the monetary cost reductions described below can be addressed by reducing work time, reducing man-hours, and reducing electricity consumption.

[0019] Figure 1 shows a schematic configuration of the allocation plan creation device, including its relationship with the higher-level system. The allocation plan creation device creates an allocation plan, which is a plan for distributing raw materials to multiple manufacturing sites, by executing the processing of the allocation plan creation method. The arrows in Figure 1 simply show the flow of data movement and processing. In this embodiment, the allocation plan creation device creates an allocation plan for six months.

[0020] The allocation plan creation device comprises an input data acquisition unit 101, a cost calculation unit 102, a constraint condition creation unit 103, a plan creation unit 105, and an output unit 106. The allocation plan creation device may further include an objective function creation unit 104.

[0021] The higher-level system comprises an operations management computer 201 and a process computer 202. The operations management computer 201 is a computer that manages operations based on the production plan of the steelworks and allocates raw materials (i.e., iron ore mainly composed of Fe) based on an optimized allocation plan created by an allocation plan creation method executed by an allocation plan creation device. The operations management computer 201 also manages data related to the operations of the steelworks. The data related to the operations of the steelworks includes input data, which will be described later. The raw material allocation determined by the allocation plan creation device is transmitted to the operations management computer 201. Furthermore, the determined raw material allocation is transmitted as input information to the process computer 202, which controls each raw material manufacturing facility. The process computer 202 controls the manufacturing facilities of the steelworks to produce steel products according to instructions from the operations management computer 201.

[0022] The input data acquisition unit 101 executes an input data acquisition step. The input data acquisition step acquires input data, which is data relating to the purchase quantity and composition of raw materials, and the production plan at each of the multiple manufacturing sites. The input data acquisition unit 101 receives input data from the operation management computer 201. In this embodiment, the purchase quantity of raw materials is for six months. In this embodiment, the production plan is a six-month pig iron production plan. The input data may also include information on the cost of removing impurities at each of the multiple manufacturing sites. The input data may directly include information on the purchase quantity, composition of raw materials, and production plan at each manufacturing site, or it may include indirect information. For example, the input data may include at least one of the origin, brand, and purchase price of the raw materials as indirect information indicating the composition of the raw materials. In the following description, the input data includes the brand of the raw materials, and the brand indicates the composition of the raw materials.

[0023] The cost calculation unit 102 performs a cost calculation step. Based on the input data, the cost calculation step evaluates the distribution of raw materials using the cost of removing impurities at each of the multiple manufacturing sites. Examples of impurities include P, S, and Si. These impurities need to be removed through processes such as steelmaking. Since the refining methods differ from one steelworks to another, for example, the dephosphorization methods differ from one steelworks to another, there are differences in the cost of removing impurities. In this embodiment, it is assumed that the removal method for phosphorus (P) differs from one steelworks to another. In this case, the cost calculation unit 102 may create a formula for the dephosphorization cost in advance, calculate the cost using the created formula, and perform an evaluation based on the calculated cost. The evaluation may be, for example, by normalizing the calculated cost (specifically, by showing it as a score from 0 to 100). Furthermore, if the removal method for sulfur (S) also differs from one steelworks to another, the cost calculation unit 102 may add the desulfurization cost to the evaluation. Furthermore, if the method for removing silicon (Si) among the impurities differs among steel mills, the cost calculation unit 102 may include the desiliconization cost in its evaluation.

[0024] The constraint creation unit 103 executes the constraint creation step. The constraint creation step calculates the amount of the main component of the raw materials determined based on the production plan at each of the multiple manufacturing sites, and creates a constraint that the sum of the amounts of the main components at each of the multiple manufacturing sites is within the range of the raw material purchase quantity. For each of the multiple manufacturing sites, after the allocated iron ore has been blended, the constraint creation unit 103 generates a constraint equation that the amount of Fe, which is the main component after blending, must satisfy. The constraint creation unit 103 may generate constraint equations for components other than the main component of the raw materials. The constraint creation unit 103 may generate constraint equations that define the upper and lower limits of SiO2 or Al2O3 after it has become sintered ore. The constraint creation unit 103 may also generate constraint equations for the components of the slag.

[0025] The objective function creation unit 104 executes the objective function creation step. The objective function creation step creates an objective function that includes the sum of costs across multiple manufacturing sites. The objective function is used to create an optimized allocation plan, and specific examples will be described later.

[0026] The planning unit 105 executes the planning step. The planning step creates an optimized allocation plan that satisfies the constraints. The planning unit 105 may consider the allocation plan that minimizes the objective function as the optimized allocation plan.

[0027] The output unit 106 executes an output step. The output step outputs an optimized allocation plan. The output unit 106 may also output the results obtained from each of the above steps to a display or the like as a text file or graph. For example, the output unit 106 may output the calculated costs as a bar graph comparing them to the results of a conventional method to a display or the like.

[0028] The specific formulas used by the cost calculation unit 102, the constraint creation unit 103, the objective function creation unit 104, and the plan creation unit 105 are described below.

[0029] The following equation (1) is a formula for the dephosphorization cost that is prepared in advance by the cost calculation unit 102.

[0030]

number

[0031] Here, i is an index representing each of the multiple manufacturing sites. If I is the set of all manufacturing sites, then i∈I holds. i ΔP is the dephosphorization cost at manufacturing site i. i This is the amount of phosphorus component to be adjusted at manufacturing site i, and can be calculated using the following equation (9).

[0032] The following equations (2) to (9) are constraint equations etc. created by the constraint creation unit 103.

[0033]

number

[0034] Equation (2) is a constraint equation for the amount of iron ore purchased. Equation (3) is a constraint equation for the amount of SiO2 in sintered ore. Equation (4) is a constraint equation for the amount of Al2O3 in sintered ore. Equation (5) is a constraint equation for the amount of Fe in sintered ore. Equation (6) is a constraint equation for the amount of Fe. Equation (7) is an auxiliary calculation formula for the amount of molten iron slag. Equation (8) is a constraint equation for the basicity of the slag. Equation (9) is a formula for calculating the adjustment amount of phosphorus.

[0035] Here, j is an index that represents each of the multiple brands. If J is the set of all brands, including auxiliary ingredients, then j ∈ J. j is the purchase quantity of brand j. "Fine Ore" is the set of powdered ore. "Ore" is the set of iron ore. "Fine Ore" ∈ J and "Ore" ∈ J hold true. x ij This represents the allocation of brand j to manufacturing site i. SOSiO2L i This is the lower limit of the SiO2 component in the sintered ore at manufacturing site i. SOSiO2U i This is the upper limit of the SiO2 component in the sintered ore at manufacturing site i.j is the content of the SiO2 component of brand j. SOAl2O3L i is the lower limit of the Al2O3 component of the sinter ore at production base i. SOAl2O3U i is the upper limit of the Al2O3 component of the sinter ore at production base i. al2o3 j is the content of the Al2O3 component of brand j. fe j is the content of the Fe component of brand j. SOFe i is the amount of the Fe component of the sinter ore at production base i. Fe i is the amount of the Fe component required at production base i. cao j is the content of the CaO component of brand j. mgo j is the content of the MgO component of brand j. Slag i is the amount of slag at production base i. B1 i is the slag basicity constant at production base i. p j is the content of the P component of brand j. TP i is the allowable amount of the phosphorus component at production base i. Here, it is assumed that there is no initial inventory at each production base. Also, it is assumed that all the iron ore distributed to each production base is used and no Fe component is contained in the auxiliary raw materials.

[0036] The following formula (10) is the objective function created by the constraint condition creation unit 103. The objective function includes the total cost at a plurality of production bases (in this example, the dephosphorization cost in formula (1)).

[0037]

Number

[0038] Here, a j is the purchase price of brand j which is an auxiliary raw material. A is the set of auxiliary raw materials, and A ∈ J holds. In this embodiment, the optimal distribution of the iron ore to each production base is determined by solving an optimization problem that minimizes the objective function in formula (10) while satisfying the constraint conditions in formulas (2) to (9).

[0039] In other words, the planning unit 105 solves an optimization problem that minimizes (or maximizes) the objective function created by the objective function creation unit 104 while satisfying the constraint equations created by the constraint condition creation unit 103. The planning unit 105 may use linear programming to solve optimization problems with first-order constraint equations. As shown in the example formula above, the planning unit 105 may use a genetic algorithm or a particle swarm optimization method if the optimization problem includes constraint equations of order two or higher.

[0040] (Examples) In this example, an allocation plan was created to distribute six months' worth of purchased iron ore to three manufacturing sites (site A, site B, and site C) using the allocation plan creation method according to the above embodiment. Figure 2 shows the improvements in this example. In Figure 2, a comparison is made with an allocation plan created using the conventional technology (comparative example), and the difference from the comparative example is used to determine whether the cost was reduced (improved) or increased (worsened).

[0041] Purchasing costs are the costs of purchasing iron ore. Dephosphorization costs are the costs of removing phosphorus (P) from the impurities. Auxiliary material costs are the costs of purchasing auxiliary materials that are blended with iron ore at each manufacturing site. Total is the sum of purchasing costs, dephosphorization costs, and auxiliary material costs. Also, total sites are the sum of sites A, B, and C.

[0042] Regarding purchasing costs, the value is 0 at all locations as there is no change. For other items, both cost reductions (improvements) and cost increases (deteriorations) are observed, but as shown for all locations in the total, an overall cost reduction (improvement) effect has occurred. In this embodiment, the method for removing phosphorus (P) among the impurities differs from one steelworks to another. By allocating more of the ore requiring dephosphorization to location C, which has low dephosphorization costs, an overall cost reduction was achieved. Furthermore, allocation is possible not only based on cost but also on processing capacity. By allocating iron ore according to the pre-processing capacity, such as dephosphorization, processing beyond capacity is not required for pre-processing, thus reducing the error in adjusting the composition of molten iron for decarburization refining. Therefore, the load on decarburization refining is reduced, high-precision composition adjustment is always possible, and this contributes to the manufacture of high-quality steel products.

[0043] As described above, the distribution plan creation apparatus, distribution plan creation method, and steel mill operation method according to this embodiment can optimize the distribution of raw materials to each manufacturing site by evaluating the cost of impurity treatment. The distribution plan creation apparatus and distribution plan creation method according to this embodiment are particularly used when raw materials are distributed to each manufacturing site for processing in a manufacturing process that requires multiple manufacturing sites, and are also applicable to the operation method of a steel mill. The distribution plan creation apparatus, distribution plan creation method, and steel mill operation method according to this embodiment can perform an evaluation using the cost incurred to remove impurities at each of the multiple manufacturing sites and create a plan in which the overall distribution cost is minimized. In other words, it is possible to create a distribution plan that optimizes the overall production cost by taking into account the differences in impurity treatment costs between steel mills.

[0044] While embodiments relating to this disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art will find it easy to make various modifications or alterations based on this disclosure. Therefore, it should be noted that these modifications or alterations are included within the scope of this disclosure. For example, the functions included in each component or step can be rearranged in a logically consistent manner, and multiple components or steps can be combined into one or divided. Embodiments relating to this disclosure can also be realized as programs executed by a processor in the device or as storage media recording such programs. These should also be understood to be included within the scope of this disclosure. [Explanation of symbols]

[0045] 101 Input data acquisition unit 102 Cost Calculation Section 103 Constraint Creation Section 104 Objective Function Creation Section 105 Planning Department 106 Output section 201 Operations Management Computer 202 Process Computers

Claims

1. A distribution plan creation device that creates a distribution plan, which is a plan for distributing raw materials to multiple manufacturing sites, An input data acquisition unit acquires input data which is data relating to the purchase quantity and composition of the raw materials and the production plan at each of the multiple manufacturing sites. A cost calculation unit evaluates the distribution of the raw materials based on the input data, using the cost of removing impurities at each of the multiple manufacturing sites. A constraint creation unit calculates the amount of the main component of the raw materials determined based on the production plan at each of the multiple manufacturing sites, and creates a constraint condition that the sum of the amounts of the main component at each of the multiple manufacturing sites is within the range of the raw material purchase quantity. A planning unit that creates an optimized allocation plan that satisfies the aforementioned constraints, A distribution plan creation device comprising: an output unit that outputs the optimized distribution plan;

2. The system further includes an objective function creation unit that creates an objective function that includes the sum of the aforementioned costs at the multiple manufacturing sites. The allocation plan creation device according to claim 1, wherein the planning unit makes the allocation plan that minimizes the objective function an optimized allocation plan.

3. A distribution plan creation method executed by a distribution plan creation device that creates a distribution plan which is a plan for distributing raw materials to multiple manufacturing sites, An input data acquisition step involves acquiring input data which is data relating to the purchase quantity and components of the raw materials and the production plan at each of the multiple manufacturing sites. A cost calculation step in which, based on the input data, the distribution of the raw materials is evaluated using the cost of removing impurities at each of the multiple manufacturing sites, A constraint creation step involves calculating the amount of the main component of the raw materials determined based on the production plan at each of the multiple manufacturing sites, and creating a constraint condition that the sum of the amounts of the main component at each of the multiple manufacturing sites is within the range of the raw material purchase quantity. A planning step to create an optimized allocation plan that satisfies the aforementioned constraints, A method for creating an allocation plan, comprising an output step of outputting the optimized allocation plan.

4. The method further includes an objective function creation step of creating an objective function that includes the sum of the aforementioned costs at the aforementioned multiple manufacturing sites, The method for creating an allocation plan according to claim 3, wherein the allocation plan that minimizes the objective function is the optimized allocation plan.

5. A method for operating a steel mill, comprising allocating the raw materials based on an optimized allocation plan created by the allocation plan creation method described in claim 3 or 4, wherein the raw materials are iron ore mainly composed of Fe.

Images