Casting device, casting method, and program

Abstract

To provide a technique capable of efficiently executing the cast organization of an intermediate product made of plural steel grades.SOLUTION: A cast organization apparatus (1) for determining a production order of an intermediate product of a slab, a bloom or a billet comprises: a data input unit (110) for accepting input of information about an alignment sequence among plural steel grades of an intermediate product produced by continuous casting using plural strands; and a rough cast organization unit (120) for creating an intermediate cast organization plan based on the information. The rough cast organization unit (120) comprises: a creation unit (121), about an intermediate product included in the plural steel grades in which the alignment sequence is continuous, for creating information for specifying an intermediate product distributing to each of the plural strands and plural production orders of the intermediate product produced in each strand; and an evaluation unit (122) for deriving an evaluation value regarding production efficiency about each of the created production orders.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a casting scheduling device, a casting scheduling method, and a program.

Background Art

[0002] In the steel manufacturing process, the pig iron produced in the blast furnace is transported to the converter. After the components are adjusted in units of ladles (charges) in the converter, the molten steel poured into the tundish is continuously cast and cut to produce intermediate products such as slabs, blooms, or billets. At this time, the process of continuously casting and cutting is called the continuous casting process, and the unit (production lot) that continuously manufactures intermediate products without interrupting the continuous casting of molten steel in the continuous casting process is called a cast. Also, the casting order (production schedule) of intermediate products within each production lot is called casting scheduling, which is determined based on the size, quality, delivery date, etc. of the intermediate products. The intermediate products produced by the continuous casting process are transported to the next process, the hot rolling process, heated to a temperature at which rolling is possible in a heating furnace, and then rolled into thin plates, thick plates, or shaped steel.

[0003] For example, in Patent Document 1, information on provisional slabs that are expected to become slabs manufactured corresponding to orders for casting scheduling and information on steel grades that can be blown in the same charge as the provisional slabs are read. For each steel grade of the provisional slabs, a steel grade priority evaluation table is created by aggregating the amounts of provisional slabs whose tapping required dates are within the required date range from the casting scheduled date, taking into account the amounts of steel grades that can be blown in the same charge as the provisional slabs. Based on the steel grade priority evaluation table, the steel grade with the highest manufacturing priority is selected, and for the selected steel grade, a cast that satisfies the constraint conditions is created, and the casting scheduling is disclosed.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

[0005] However, the technology disclosed in Patent Document 1 is only for casting one type of steel, and does not allow for casting multiple types of steel at once.

[0006] One aspect of the present invention has been made in view of the above-mentioned problems, and aims to provide a technology for efficiently performing the casting of intermediate products consisting of multiple types of steel. [Means for solving the problem]

[0007] To solve the above problems, a cast assembly apparatus according to one aspect of the present invention is a cast assembly apparatus for determining the manufacturing order of any intermediate product, which is a slab, a bloom, or a billet, and comprises: a data input unit for inputting information on the arrangement order of the intermediate product among a plurality of steel types to be manufactured by continuous casting using a plurality of strands; and a rough cast assembly unit for generating an intermediate cast assembly plan based on the information, wherein the rough cast assembly unit includes a generation unit for generating information that identifies the intermediate product to be distributed to each of the plurality of strands for the intermediate product included in the plurality of steel types whose arrangement order is consecutive, and a plurality of manufacturing orders for the intermediate product to be manufactured in each strand, and an evaluation unit for deriving an evaluation value related to manufacturing efficiency for each of the generated manufacturing orders.

[0008] A cast scheduling method according to one aspect of the present invention is a cast scheduling method for determining the manufacturing order of any intermediate product, such as a slab, bloom, or billet, and includes the steps of: inputting information regarding the order in which the intermediate product is arranged among a plurality of steel grades to be manufactured by continuous casting using a plurality of strands; generating information that identifies the intermediate product to be distributed to each of the plurality of strands for the intermediate product included in the plurality of steel grades whose order is consecutive; and generating a plurality of manufacturing orders for the intermediate product to be manufactured on each strand; and deriving an evaluation value regarding manufacturing efficiency for each of the generated manufacturing orders.

[0009] Each aspect of the present invention may be implemented by a computer, in which case the cast organization program for the cast organization device, which enables the computer to implement the cast organization device by operating the computer as each part (software element) of the cast organization device, and a computer-readable recording medium on which the program is recorded also fall within the scope of the present invention. [Effects of the Invention]

[0010] According to one aspect of the present invention, a technique can be provided for efficiently performing the casting and assembly of intermediate products consisting of multiple types of steel. [Brief explanation of the drawing]

[0011] [Figure 1] This figure shows a schematic configuration of a manufacturing schedule determination device including a cast assembly device according to an embodiment of the present invention. [Figure 2] This is a block diagram showing the configuration of a cast assembly apparatus according to an embodiment of the present invention. [Figure 3] This is a conceptual diagram illustrating a method by which a generation unit according to an embodiment of the present invention generates combinations of manufacturing sequences. [Figure 4] This is a conceptual diagram illustrating one example of a method for distributing a slab contained in one steel grade into two strands. [Figure 5] This diagram shows the combinations of arranging slabs, which have been distributed to two strands, in ascending and descending order of width. [Figure 6] This figure shows patterns of slab manufacturing order that combine a method of distributing into two strands and an arrangement method that combines ascending and descending order by width. [Figure 7] This diagram schematically shows the processes performed by the generation unit and evaluation unit according to the embodiment. [Figure 8] This flowchart shows the flow of the cast formation method according to the embodiment. [Figure 9]This flowchart shows a more general cast formation method according to the embodiment. [Modes for carrying out the invention]

[0012] [Embodiment 1] One embodiment of the present invention will be described in detail below. This embodiment relates to a cast forming apparatus and a cast forming method used in the steel manufacturing process, particularly in the manufacturing process of intermediate products including slabs, blooms, or billets.

[0013] In this embodiment, a cast is a unit for continuously manufacturing (casting) intermediate products, and this unit corresponds to one manufacturing lot. In other words, one cast produces a group of intermediate products consisting of multiple intermediate products manufactured in one continuous operation. Typically, each intermediate product has a different composition and size according to customer requirements. Grouping these products according to a predetermined tolerance range of composition is also called a "material" or "steel grade." In other words, multiple intermediate products belonging to any given steel grade may have a different composition in at least one of them from the others. Intermediate products included in a group of steel grades are manufactured from one or more charges whose composition has been adjusted to the tolerance range of that steel grade.

[0014] In this embodiment, cast organization refers to determining the manufacturing order of a group of intermediate products of various sizes, consisting of multiple steel types, included in each cast (manufacturing lot), based on the size, steel type, and delivery date of the intermediate products.

[0015] In this embodiment, a slab is an intermediate product manufactured during the casting of steel, and refers to a slab that is cut from molten steel that has been cast into a long, rectangular cross-section. The slab is then rolled in the next step, wound into a coil, and then processed in yet another step to become various products.

[0016] The size of the slab refers to the lengths of the short side and the long side when the slab is viewed in plan view in this embodiment. Particularly important is the length of the short side. The length of the short side is the length in the direction orthogonal to the direction in which the cast slab is conveyed by the strand, and hereinafter this length is referred to as the width. The long side corresponds to the length of the slab.

[0017] Note that a bloom is smaller than a slab and has a ratio of width to thickness of the cross section close to 1 (close to a square). Also, a billet has a rectangular cross section and is smaller in size than a bloom. The width of a bloom and a billet is defined in the same manner as that of a slab.

[0018] Also, a strand is a casting line and includes a mold into which molten steel is poured from a tundish and a series of forming rolls that form the cast piece while conveying it out of the mold.

[0019] [[ID=eleven]] The combinations of steel grades and sizes of intermediate products required by a large number of customers are very numerous. Furthermore, due to the operational constraints of the casting line, it is not easy to determine an efficient product arrangement for various intermediate products. Since it is difficult in terms of time to evaluate all combinations, it is required to select and evaluate combinations of manufacturing sequences that seem to be efficient. The cast scheduling device and the cast scheduling method according to this embodiment are a device and a method for determining the manufacturing sequence of intermediate products of either a slab, a bloom or a billet so as to achieve the best possible manufacturing efficiency.

[0020] (Manufacturing Schedule Determination Device) The following describes the cast assembly apparatus 1 according to this embodiment, but first, the positioning of the cast assembly apparatus 1 will be explained. In the following, the case where the intermediate product is a slab will be used as an example. Figure 1 is a schematic diagram showing the general configuration of the manufacturing schedule determination apparatus 100, which includes the cast assembly apparatus 1 according to this embodiment. Each part of the manufacturing schedule determination apparatus 100 may be implemented, for example, in a dedicated computer system, or as application software in a general-purpose computer system such as a personal computer. Alternatively, each component of the manufacturing schedule determination apparatus 100 may be distributed and implemented on multiple computers connected via a network such as a LAN (Local Area Network) or the Internet. Furthermore, some or all of the components of the manufacturing schedule determination apparatus 100 may be located on the cloud and connected to each other in a way that enables information communication.

[0021] The manufacturing schedule determination device 100 includes a cast assembly device 1 and a constraint violation resolution unit 130. The cast assembly device 1 includes a data input unit 110 and a rough cast assembly unit 120. As described above, the cast assembly device 1 is a device that constitutes a part of the manufacturing schedule determination device 100. The manufacturing schedule determination device 100 is a device that determines the manufacturing schedule for primary products in the first step of a steel product manufacturing process, which includes a first step of manufacturing primary products (intermediate products) and a second step of manufacturing secondary products from primary products. The functions of each part of the manufacturing schedule determination device 100 in the embodiment shown in Figure 1 are realized by one or more processors that operate according to a program, and an interface for inputting and outputting data to the processor.

[0022] The manufacturing schedule determination device 100 reads the slab information file 101, the steel type cast information file 102, and the coil information file 103 used for processing, through operations by an operator or automatic input instructions at set times. The manufacturing schedule determination device 100 records the results of the processing performed based on the information recorded in these files in the cast assembly result file 104. The manufacturing schedule determination device 100 also reads the assembly condition file 105 in the processing performed by the rough cast assembly unit 120 and the constraint violation resolution unit 130.

[0023] These files are recorded, for example, in the memory built into the computer, or on a removable recording medium that can be connected to the computer. Furthermore, some or all of the above files may be stored in an information processing device different from the manufacturing schedule determination device 100. In that case, the contents of these files may be read into or written to the manufacturing schedule determination device 100 via communication using a telecommunications line such as a LAN or the Internet.

[0024] The slab information file 101 is a file for storing information about each slab to be manufactured, including at least the slab width. Specifically, for each slab, the slab information file 101 includes, for example, a slab ID (information identifying the slab), slab width, slab length, slab weight, material, and other manufacturing specifications, as well as process information such as the desired date and time for passing through the process and the deadline date and time for passing through. The slab width includes the width specified by the customer and the range of widths that are permissible during the slab manufacturing process. The latter range of widths may also be used as a target during slab manufacturing. This is because the slab width can be adjusted to within the range of widths specified by the customer during the rolling process or other processes after the slab has been manufactured.

[0025] The cast information file 102 is a file for storing information about the charge for each cast of the same steel type. Specifically, for each cast of the same steel type, the cast information file 102 includes, for example, the cast ID, charge count, weight limit, weight limit, material, and manufacturing order. Of these, information about the predetermined manufacturing order is mandatory. The coil information file 103 is a file for storing planned information about coils to be rolled. Specifically, for each coil, the coil information file 103 includes, for example, the slab ID, coil width, coil length, coil thickness, and furnace temperature.

[0026] (constraints) The configuration conditions file 105 includes, as an example, constraints on the slab manufacturing schedule in the continuous casting process and constraints on the coil manufacturing schedule in the hot rolling process. The constraints on the slab manufacturing schedule include width transition conditions and part placement conditions.

[0027] In this embodiment, width transition refers to changing the width of the slab being manufactured. As an example, there are two width transition conditions. The first width transition condition is that the change in width of adjacent slabs in the manufacturing sequence is less than a predetermined threshold. This is because, due to equipment constraints on the strand, it is difficult to change the width of the slab beyond a predetermined width in a continuous casting process.

[0028] Furthermore, the second condition for width transition is that the number of changes in the direction of width transition should be small. Due to equipment constraints on the strand, it is preferable that the direction of width transition be as unidirectional as possible. In other words, if an operation is performed to increase the width, it is preferable that the next operation also increases the width. Similarly, if an operation is performed to decrease the width, it is preferable that the next operation also decreases the width. The reason for this is that, for example, changing the direction of width transition is time-consuming.

[0029] In this embodiment, the location arrangement condition means, for example, that at a predetermined manufacturing sequence position in each strand, it is necessary to place slabs with a relatively larger or larger tolerance range for slab composition than the predetermined range. For example, at the beginning and end of a cast, and before and after changes in the charge (ladle) or steel type, it is required to place slabs with a wide tolerance range for composition. This is because at such positions, molten steel of different compositions is likely to mix, causing the slab composition to deviate from the set value. If the tolerance range for composition is sufficiently wide, even if there is a deviation from the set value of the composition, it may still fall within the tolerance range.

[0030] (Cast formation device) Based on the above, the cast organization apparatus 1 according to this embodiment will be described with reference to the drawings. Figure 2 is a block diagram showing the configuration of the cast organization apparatus 1 according to this embodiment. As shown in the figure, the cast organization apparatus 1 includes a data input unit 110 and a rough cast organization unit 120. The rough cast organization unit 120 includes a generation unit 121 and an evaluation unit 122. The rough cast organization unit 120 is a device that generates an intermediate cast organization proposal (first-order solution) of the cast. As described above, the intermediate cast organization proposal generated by the rough cast organization unit 120 is modified by the constraint violation resolution unit 130 to resolve the constraint violations. In other words, the rough cast organization unit 120 generates an intermediate cast organization proposal that allows for constraint violations based on the information input from the data input unit.

[0031] The data input unit 110 inputs information regarding the order of multiple steel types in intermediate products (slabs) manufactured by continuous casting using multiple strands to the rough cast assembly unit 120. The information regarding the order of multiple steel types can be rephrased as information regarding the order of steel types in the intermediate products corresponding to the manufacturing order of the multiple intermediate products. As mentioned above, it is preferable to cast the slabs in an order in which the steel types do not change significantly, so the order of the steel types is predetermined. The data input unit 110 reads the information regarding the order of steel types from the steel type cast information file 102 and inputs it to the rough cast assembly unit 120. The data input by the data input unit 110 may be recorded in a memory (not shown) provided by the cast assembly device 1.

[0032] Furthermore, as mentioned above, it is preferable to manufacture the slabs in a sequence that does not significantly change their width. For this reason, the data input unit 110 inputs information regarding the width of the slabs. This information regarding the width of the slabs refers to the manufacturing specifications of the slabs, specifically including the slab width, slab length, slab weight, material, and other manufacturing specifications. The data input unit 110 reads the information regarding the width of the slabs from the slab information file 101 and inputs it into the rough cast assembly unit 120. The data input unit 110 may also input a provisional manufacturing order of slabs within the steel grade into the rough cast assembly unit 120.

[0033] (Generation part) The generation unit 121 of the rough cast assembly unit 120 generates information that identifies which slabs to distribute to each of the multiple strands, and multiple manufacturing sequences for the slabs produced on each strand, for slabs (intermediate products) included in multiple steel grades with a consecutive order. In other words, the generation unit 121 determines which of the multiple strands will be used to manufacture all slabs belonging to the cast. That is, the generation unit 121 generates information that identifies which slabs to distribute to each of the multiple strands. Next, the generation unit 121 generates multiple manufacturing sequences for the slabs to be produced on each strand as evaluation candidates. Here, combinations are generated without considering the constraints mentioned above. Then, the evaluation unit 122, which will be described next, derives an evaluation value and selects one based on that evaluation value.

[0034] In most cases, two strands branch off from a single tundish. Therefore, the following explanation will use the case with two strands as an example. However, the number of strands is not limited to two; there can be more than two. For example, three or more strands may be provided from a single tundish, or three or more strands may be formed by providing multiple tundishes. An example using three or more strands will be discussed later.

[0035] (Evaluation Department) The evaluation unit 122 of the rough cast assembly unit 120 derives an evaluation value related to manufacturing efficiency for each of the generated manufacturing sequences. Specifically, the evaluation unit 122 refers to the constraints on the slab manufacturing schedule obtained from the assembly condition file 105 and derives a higher evaluation value for each manufacturing sequence the fewer parts that violate the constraints. This is because the fewer parts that violate the constraints (parts that do not satisfy the constraints), the higher the overall manufacturing efficiency of the slabs included in the cast is evaluated.

[0036] The evaluation value is derived, for example, by assigning a cost to the points where constraints are violated. For example, the evaluation unit 122 treats the slabs to be manufactured as nodes and the routes connecting the nodes in the manufacturing order as edges, and evaluates the cost of each edge for each stage of the manufacturing order. Specifically, it evaluates the cost of whether or not the width transition condition is violated based on the change in width between the first slab to be manufactured and the second slab to be manufactured. If the difference in width between the first and second slabs violates the width transition condition, a large cost is assigned to that edge; if it does not violate the width transition condition, a small cost is assigned to that edge. The same evaluation is then performed for the difference in width between the nth slab and the (n+1)th slab (where n is an integer of 2 or greater).

[0037] The difference in width can be positive or negative; a positive value indicates an increase in width, while a negative value indicates a decrease. Whether the direction of width change is constant is also a factor in cost evaluation. In other words, edges that change from positive to negative, or from negative to positive, are valued highly in terms of cost. Furthermore, cost may be evaluated not only by the number of locations that violate the width transition condition, but also by considering the degree (weight) of the violation.

[0038] Furthermore, significant costs are incurred at points where the charge changes or at edges where the steel type changes, as the slab composition is more likely to change. The cost may also vary depending on the extent to which the composition is likely to change. Generally, the less the composition changes, the lower the cost. In addition, relatively higher costs may be incurred if certain components with small tolerance widths are included.

[0039] In this way, the cost is derived for all manufacturing sequences and converted into an evaluation value. A lower cost results in a higher evaluation value. Note that the method for deriving the evaluation value is not limited to the above method, as long as it can evaluate the degree to which the constraints are violated. As an example of another method, the simulated annealing method may be used for evaluation. The simulated annealing method uses the slabs included in one manufacturing sequence as variables, expresses constraints such as width transition conditions and part arrangement conditions using these variables, and finds the combination of variables that minimizes the sum of the weighted constraints (evaluation value).

[0040] As described above, the evaluation unit 122 derives an evaluation value related to manufacturing efficiency for each manufacturing sequence generated by the generation unit 121.

[0041] Next, the method by which the generation unit 121 generates the slab manufacturing sequence will be described. In this embodiment, the data input unit 110 further inputs information regarding the slab width to the rough cast and weld unit 120, and the generation unit 121 generates the manufacturing sequence for each strand by referring to the information regarding the slab width. As mentioned above, the information regarding the slab width is information regarding the slab manufacturing specifications. With this configuration, it is possible to generate a manufacturing sequence that easily satisfies the width transition conditions. The method will be described below.

[0042] (Distribution and arrangement) Figure 3 is a conceptual diagram showing how the generation unit 121 generates the manufacturing sequence of slabs. First, the data input unit 110 reads information about the width of the slabs from the slab information file 101 and inputs it. The input information about the width of the slabs is temporarily recorded in a memory (not shown) or a storage unit such as the cast assembly result file 104 provided by the cast assembly device 1.

[0043] Figure 3, section 301, is a schematic diagram showing slabs within two steel grades arranged in manufacturing order. Specifically, from top to bottom, the diagram shows slab detail data sorted in descending order of width for slabs included in the first steel grade to be manufactured, and slab detail data sorted in descending order of width for slabs included in the second steel grade to be manufactured. Note that the order of the slab detail data at this stage is provisional. This is because the manufacturing order at this stage may change when constraint violations are resolved. As shown in the diagram, sorting the manufacturing order so that the width is in ascending or descending order is also called smoothing the width transition. In these diagrams, one rectangle represents one slab, and the longer side of the rectangle represents the width of the slab as a relative length.

[0044] For example, the slab detail data for steel type 1 is arranged in order of width: seven slabs with the widest width, three slabs with the next widest width, four slabs with the next widest width, and two slabs with the smallest width. Similarly, the slab detail data for steel type 2 is also arranged in order of width, from widest to narrowest. The slab detail data for steel type 3 and beyond is similar, but is not shown in the illustration.

[0045] The schematic diagram shown in Figure 3, section 301, illustrates that in reality, the data for each slab temporarily recorded in the slab information file 101, etc., includes data showing the result of sorting the slab detail data by width. The state in which data is recorded in the slab information file 101, etc., will be described below in the manner shown in the figure.

[0046] The generation unit 121 refers to the data recorded in memory or the cast assembly result file 104 and distributes each slab into two strands, A and B, as shown in 302 of Figure 3. The schematic diagram shown in 302 of Figure 3 shows that, in reality, the data for each slab recorded in memory or the cast assembly result file 104 is associated with either strand A or strand B as the strand that will manufacture that slab.

[0047] As shown in the diagram, in steel type 1, the slabs distributed to strand A are arranged in order from the widest to the widest slabs, and the slabs distributed to strand B are arranged in order from the widest to the narrowest slabs. In steel type 2, conversely, the slabs distributed to strand A are arranged in order from the widest to the narrowest slabs, and the slabs distributed to strand B are arranged in order from the widest to the widest slabs. By arranging them in this way, it becomes easier to satisfy the aforementioned width transition condition.

[0048] The gray-colored rectangles in the diagram indicate slabs whose composition is prone to variation. Specifically, slabs manufactured at the beginning and end of a production run, slabs immediately after a change in width, and slabs before and after a change in charge or steel type are prone to compositional variations. The gray-colored locations (areas) are areas where it is preferable to place slabs with the largest possible allowable composition range to easily satisfy the aforementioned location arrangement conditions.

[0049] Therefore, in this embodiment, among the slabs to be incorporated in the cast, slabs that satisfy the aforementioned part arrangement conditions are preferentially assigned to the gray-colored positions. Violations of the part arrangement conditions are difficult to resolve if attempted after all slabs have been arranged, as this would change the length of the cast or the slabs corresponding to each part. If the constraints cannot be resolved with the slabs to be incorporated in the cast, the violation of the constraints is resolved by inserting slabs not tied to an order (also referred to as "extra material"). However, excessive use of extra material is undesirable because it necessitates adding slabs to the cast, making the cast longer, preventing the manufacture of some of the slabs to be incorporated in the cast, and reducing manufacturing efficiency. Therefore, in this embodiment, the generation unit 121 prioritizes generating arrangements that satisfy the part arrangement conditions.

[0050] In the diagram shown at 302 in Figure 3, the slabs are arranged in ascending or descending order of width. However, as mentioned above, the part arrangement conditions take precedence, so the width order does not necessarily have to follow ascending or descending order. The resolution of violations of the width transition conditions is performed by the aforementioned constraint violation resolution unit 130 after the rough cast assembly.

[0051] (Distribution method) Figure 4 is a conceptual diagram showing an example of a method for distributing slabs included in one steel grade to two strands A and B. Figure 401 shows a repeating distribution method in which slabs sorted by width in slab detail data are alternately assigned to strands A and B from top to bottom. Figure 402 shows a divided distribution method in which, for any steel grade, the entire slab sorted by width (ascending or descending in width in Figure 4) is divided in half and distributed to strands A and B respectively. Both of these distribution methods maintain the arrangement in width order. It is preferable that the part arrangement conditions are also satisfied after distribution, so if necessary, the arrangement of slabs with a large allowable composition range may be corrected at the distribution stage.

[0052] (Arrangement method) Next, the generation unit 121 generates the manufacturing order for each strand of a slab distributed to multiple strands for any given steel type. As mentioned above, it is preferable that the manufacturing order of the slabs in each strand progresses in one direction, and it is preferable to select either ascending or descending order of slab width. In that case, when manufacturing one steel type using two strands, ascending or descending order can be selected for each strand, resulting in 2 × 2 = 4 possible combinations of manufacturing orders. This is illustrated in Figure 5.

[0053] Figure 5 shows combinations of arranging multiple slabs belonging to the same steel type, distributed to strands A and B, in ascending and descending order of width. In Figure 5, the shaded areas for each strand represent sets of multiple slabs. When the width of the shaded area decreases sequentially from the top to the bottom of the page, it indicates that the multiple slabs are arranged in descending order. Conversely, when the width of the shaded area increases sequentially from the top to the bottom of the page, it indicates that the multiple slabs are arranged in ascending order. That is, 501 in Figure 5 shows a combination of manufacturing order in which the slabs distributed to strand A are arranged in descending order and the slabs distributed to strand B are arranged in descending order. Similarly, 502 shows a combination of manufacturing order in which the slabs distributed to strand A are arranged in descending order and the slabs distributed to strand B are arranged in ascending order. 503 shows a combination of manufacturing order in which the slabs distributed to strand A are arranged in ascending order and the slabs distributed to strand B are arranged in descending order. 504 represents a combination of manufacturing sequences in which the slabs distributed to strand A are arranged in ascending order, and the slabs distributed to strand B are also arranged in ascending order. Thus, for each steel grade, there are 2 x 2 = 4 combinations of manufacturing sequences in which the slabs are arranged in ascending or descending order on the two strands.

[0054] (Manufacturing pattern) Therefore, in the example above, for each steel grade, if that grade contains multiple slabs, there are combinations of how the slabs are distributed to the two strands and four manufacturing sequences. Thus, as shown in Figure 6, there are 2 × 4 = 8 manufacturing patterns in terms of which slabs are manufactured on each strand and in what order, and the manufacturing of each steel grade will be carried out in one of these manufacturing patterns. More specifically, Figure 6 is a diagram showing the manufacturing patterns of slabs for the same steel grade, combining the distribution method explained using Figure 4 and the arrangement method explained using Figure 5. As mentioned above, there are two ways to distribute to strands A and B, and four combinations of arranging the distributed slabs in ascending and descending order of width. Therefore, as shown in 601 of Figure 6, a total of eight manufacturing patterns are generated: four manufacturing patterns in which repeatedly distributed slabs are arranged in ascending and descending order of width, and four manufacturing patterns in which divided and distributed slabs are arranged in ascending and descending order of width. Figure 601 shows the manufacturing pattern for a slab of one steel type, and Figure 602 shows the manufacturing pattern for a slab of two steel types. Thus, when multiple steel types are included in one cast, eight manufacturing patterns are generated for each steel type. Therefore, if the number of steel types is m, then 8 to the power of m manufacturing patterns can be obtained for slabs of all steel types.

[0055] However, as the number of steel grades m increases, the number of combinations (8 to the power of m) also increases. Therefore, deriving evaluation values ​​for all combinations to select one from this enormous number of combinations would take a long time and be impractical. For this reason, the manufacturing patterns obtained are limited by referring to the width of the slab, as follows.

[0056] (Combination of manufacturing patterns for multiple steel grades) In this embodiment, the generation unit 121 obtains the optimal manufacturing order for each manufacturing pattern of the last steel type among a series of consecutive steel types, which has the highest evaluation value. The generation unit 121 then generates a new combination of manufacturing patterns by connecting this optimal manufacturing order with the manufacturing pattern of the slab included in the next steel type to be manufactured among the series of consecutive steel types. The evaluation unit 122 then derives an evaluation value for each of these new combinations of manufacturing patterns. This process will be explained using Figure 7.

[0057] Figure 7 is a schematic diagram showing the processes performed by the generation unit 121 and evaluation unit 122 described above. As shown in 701 of Figure 7, there are eight manufacturing patterns for the first type of steel slab generated by the generation unit 121: 1a, 1b, ..., 1h. Similarly, 702 shows the manufacturing patterns for the second type of steel slab generated by the generation unit 121: 2a, 2b, ..., 2h, and 703 shows the manufacturing patterns for the third type of steel slab: 3a, 3b, ..., 3h.

[0058] First, the combinations of slabs for steel type 1 and steel type 2 are evaluated. The generation unit 121 generates combinations that lead to manufacturing pattern 2a for steel type 2. Specifically, there are eight combinations: 1a-2a, 1b-2a, 1c-2a, 1d-2a, 1e-2a, 1f-2a, 1g-2a, and 1h-2a. The evaluation unit 122 derives an evaluation value for each of the above combinations generated by the generation unit 121. Then, the generation unit 121 acquires the combination with the highest evaluation value among the eight combinations as the optimal manufacturing order for manufacturing pattern 2a.

[0059] Similarly, the generation unit 121 generates combinations that lead to the manufacturing pattern 2b for the second steel type, and the evaluation unit 122 derives an evaluation value for each of these combinations. Then, the generation unit 121 acquires the combination with the highest evaluation value from among the eight combinations that lead to the manufacturing pattern 2b as the optimal manufacturing order for the manufacturing pattern 2b.

[0060] By performing the same processing as described above on the remaining manufacturing patterns (2c to 2h) for the second steel type, the evaluation unit 122 acquires the combination with the highest evaluation value among the combinations that connect to each manufacturing pattern from manufacturing pattern 2a to manufacturing pattern 2h for the second steel type, as the optimal manufacturing pattern. In this way, for each of the eight manufacturing patterns for the second steel type, the combination with the manufacturing pattern of the first steel type that has the highest evaluation value (eight optimal manufacturing patterns) is acquired.

[0061] Specifically, for example, among the combinations 1a-2e, 1b-2e, 1c-2e, 1d-2e, 1e-2e, 1f-2e, 1g-2e, and 1h-2e, which lead to manufacturing pattern 2e for the second steel type, let's assume that the evaluation value for the combination 1f-2e was the highest. Therefore, as shown by the thick lines in 701 and 702 of Figure 7, let's assume that 1f-2e is obtained as the optimal combination leading to manufacturing pattern 2e for the second steel type. In this case, the generation unit 121 fixes the combination 1f-2e. That is, only 1f-2e is retained (saved) as the optimal manufacturing sequence for the combination leading to manufacturing pattern 2e. In the diagram, only the combinations that lead to manufacturing pattern 2e are shown with dotted and thick lines (thick lines indicate combinations that are retained). The generation unit 121 performs this process for manufacturing patterns 2a, 2b, ... 2h, leaving one optimal combination for each of the manufacturing patterns 2a, 2b, ... 2h. Therefore, at this stage, eight optimal combinations remain.

[0062] Next, the generation unit 121 generates combinations that lead to each manufacturing pattern of the three steel types. In this case, the generation unit 121 generates only the optimal combination of steel type 1 and steel type 2, and combinations with each manufacturing pattern of steel type 3. Specifically, the generation unit 121 generates 2a-3a, 2b-3a, 2c-3a, 2d-3a, 2e-3a, 2f-3a, 2g-3a, and 2h-3a as combinations that lead to manufacturing pattern 3a. However, each of 2a, 2b, ... 2h is associated with a manufacturing pattern of steel type 1 that is fixed as the optimal combination.

[0063] Similarly, the generation unit 121 generates combinations that lead to manufacturing pattern 3b, combinations that lead to manufacturing pattern 3c, ... combinations that lead to manufacturing pattern 3h. There are 8 × 8 = 64 such combinations. The evaluation unit 122 then derives evaluation values ​​for these 64 combinations. The generation unit 121 retains only the combination with the highest evaluation value among the combinations that lead to each of the manufacturing patterns 3a, 3b, ... 3h.

[0064] In the examples shown in Figures 7, 702 and 703, only combinations that lead to manufacturing pattern 3b are shown with dotted and thick lines (thick lines indicate combinations that remain). In this figure, manufacturing pattern 2e has the highest evaluation value among the combinations that lead to manufacturing pattern 3b. In this case, the generation unit 121 retains only the combination 1f-2e-3b as the optimal combination that leads to manufacturing pattern 3b. Such optimal combinations remain for each of the manufacturing patterns 3a, 3b, ..., 3h. Therefore, even after the optimal combinations have been determined for up to three steel types, eight optimal combinations remain. It is also acceptable for one optimal combination for up to two steel types to be combined in common with multiple manufacturing patterns for three steel types.

[0065] The same process is followed for the fourth steel type and beyond, evaluating the 64 combinations obtained by combining the optimal combination remaining for the steel type immediately preceding the target steel type with the eight manufacturing patterns for the target steel type. The optimal combination for each manufacturing pattern is then retained as the optimal manufacturing order. Finally, for the last steel type, the combination with the highest evaluation value among the optimal combinations obtained for each manufacturing pattern is selected as the combination (manufacturing order) with the highest evaluation value for the entire cast.

[0066] If the above-described narrowing of combinations is not performed, then, if the number of steel types is m, it would be necessary to evaluate 8 to the power of m combinations. However, by performing the above narrowing, the optimal solution can be obtained with the same accuracy as when no narrowing is performed, by evaluating 64 × (m-1) combinations. In other words, this process reduces the number of combinations to be evaluated compared to evaluating all combinations.

[0067] The above can be explained more specifically as follows. First, the generation unit 121 generates information that identifies the intermediate products to be distributed to each of the multiple strands for the intermediate products included in the first steel grade to be manufactured and the intermediate products included in the second steel grade to be manufactured, as well as the manufacturing patterns of the intermediate products to be manufactured in each strand. The evaluation unit 122 derives an evaluation value for each of the generated combinations.

[0068] Next, the generation unit 121 generates a new combination of manufacturing patterns for intermediate products included in the nth (where n is an integer greater than or equal to 3)th steel grade for each manufacturing pattern of the (n-1)th steel grade, by combining the manufacturing patterns of the 1st to (n-1)th steel grades with the highest evaluation values ​​and the manufacturing patterns of the intermediate products included in the nth steel grade.

[0069] Next, the evaluation unit 122 derives an evaluation value for each of the newly generated manufacturing pattern combinations.

[0070] The generation unit 121 determines whether it has generated all combinations of manufacturing patterns for all steel types and derived evaluation values. If it is determined that it has generated all combinations of manufacturing patterns for all steel types and derived evaluation values, an output unit (not shown) outputs the manufacturing pattern combinations and their evaluation results. If it is determined that it has not generated all combinations of manufacturing patterns for all steel types and derived evaluation values, the generation unit 121 increments the value of n by 1 and generates new combinations of manufacturing patterns. The evaluation unit 122 derives an evaluation value for each of these combinations. This process is repeated until the last steel type (until n reaches the number of planned steel types). Then, among the combinations that lead to each manufacturing pattern of the nth steel type, the one with the highest evaluation value is selected as the rough cast configuration result.

[0071] The evaluation value of the combination of the manufacturing patterns for the (n-1)th steel types and the manufacturing pattern for the nth steel type can be calculated by summing the evaluation values ​​of the manufacturing patterns for the (n-1)th steel types and the evaluation values ​​for manufacturing the nth steel type using each manufacturing pattern immediately following the last slab of the (n-1)th steel type. In this case, the summed evaluation value V is calculated using the following formula (1), where v(k) is the evaluation value when manufacturing using the manufacturing pattern for the kth steel type.

number

[0072] Alternatively, the comparison could be made using only the evaluation values ​​when the nth steel type is manufactured in each manufacturing pattern following the last slab of the (n-1)th steel type.

[0073] The above processing method reduces the number of items to be evaluated compared to evaluating all possible combinations of manufacturing sequences.

[0074] In the embodiments described above, slabs were used as an example of intermediate products, but the same can be applied to cast intermediate products such as blooms or billets.

[0075] (Effect of the cast formation device) The cast assembly device 1 described above enables efficient cast assembly of intermediate products consisting of multiple steel types. Furthermore, by limiting the manufacturing patterns based on information regarding the width of the intermediate products, the number of combinations of manufacturing sequences for intermediate products consisting of multiple steel types included in the cast can be reduced. Therefore, it is possible to search for a combination with a high probability of being the optimal solution in a shorter time compared to considering all possible manufacturing sequence combinations.

[0076] (Casting method) Next, the casting method according to this embodiment will be described with reference to the drawings. The casting method according to this embodiment is a casting method for determining the manufacturing order of any intermediate product, such as a slab, bloom, or billet.

[0077] Figure 8 is a flowchart showing the flow of the cast organization method S1. The cast organization method S1 includes the following steps. In this embodiment, it is assumed that one or more processors (specifically, the data input unit 110, the generation unit 121, the evaluation unit 122, etc.) execute each of the steps described later. In step S11, information regarding the order of multiple steel grades among the intermediate products manufactured by continuous casting using multiple strands is input. The information regarding the order of intermediate products and steel grades is as described above. Specifically, for example, the data input unit 110 inputs information including the order of multiple steel grades among the intermediate products manufactured by continuous casting using multiple strands into the rough cast assembly unit 120.

[0078] In step S12, for intermediate products included in multiple steel grades with a consecutive order, information is generated to identify the intermediate products to be distributed to each of the multiple strands, and multiple manufacturing patterns for the intermediate products to be manufactured in each strand are generated. Specifically, for example, the generation unit 121 generates combinations of intermediate products to be manufactured in each of the multiple strands and the manufacturing order of the intermediate products to be manufactured in each strand.

[0079] In step S13, an evaluation value related to manufacturing efficiency is derived for each of the generated manufacturing patterns. Specifically, for example, the evaluation unit 122 derives an evaluation value related to manufacturing efficiency for each of the generated combinations. The derived evaluation values ​​are recorded in the cast formation result file 104, etc.

[0080] Figure 9 is a flowchart showing the flow of a more general cast formation method S2. Cast formation method S2 includes the following steps.

[0081] In step S21, information regarding the order of multiple steel grades among intermediate products manufactured by continuous casting using multiple strands is entered.

[0082] In step S22, information is generated to identify the intermediate products to be distributed to each of the multiple strands, and the manufacturing patterns of the intermediate products to be manufactured in each strand, for the intermediate products included in the first steel grade to be manufactured and the intermediate products included in the second steel grade to be manufactured.

[0083] In step S23, for intermediate products included in the nth (where n is an integer greater than or equal to 3)th steel grade to be manufactured, a new combination of manufacturing patterns is generated for each manufacturing pattern of the (n-1)th steel grade by combining the manufacturing patterns of the 1st to (n-1)th steel grades with the highest evaluation values ​​and the manufacturing patterns of the intermediate products included in the nth steel grade.

[0084] In step S24, an evaluation value is derived for each of the newly generated manufacturing pattern combinations. The derived evaluation values ​​are recorded in the cast formation result file 104, etc.

[0085] In step S25, it is determined whether or not all combinations of manufacturing patterns for all steel types have been generated and evaluation values ​​have been derived. If it is determined in step S25 that all combinations of manufacturing sequences for all steel types have been generated and evaluation values ​​have been derived, the process proceeds to step S26. If it is determined in step S25 that all combinations of manufacturing sequences for all steel types have not been generated and evaluation values ​​have not been derived, the process returns to step S23.

[0086] In step S26, the result is output and the cast formation process is terminated.

[0087] (Effects of cast formation method) According to the casting methods S1 and S2 described above, the casting of intermediate products consisting of multiple types of steel can be carried out efficiently.

[0088] As explained using Figure 1, the rough cast assembly result with the highest evaluation value obtained by the cast assembly device 1 is further subjected to constraint violation resolution by the constraint violation resolution unit 130. The constraint violation resolution by the constraint violation resolution unit 130 may, for example, rearrange the slabs in areas where the width transition condition has not been resolved using an empirically based algorithm, or it may be possible to search for the optimal solution by randomly rearranging the slabs using a simulated annealing method or the like. As mentioned above, the tolerance range for width is large at the stage of manufacturing slabs. Therefore, rearranging slabs to resolve width transition condition violations is easier than rearranging slabs to resolve part arrangement condition violations. Through such constraint violation resolution processing, it is possible to determine a manufacturing order for casts that is more efficient to manufacture.

[0089] [Embodiment 2] Other embodiments of the present invention are described below. For the sake of clarity, components having the same function as those described in the above embodiments will be denoted by the same reference numerals, and their descriptions will not be repeated.

[0090] In the above-described embodiment 1, the case where the number of strands is 2 was used as an example. However, the number of strands may be 3 or more.

[0091] For example, when distributing slabs to three strands, there will be three destinations for the slabs, as shown in Figure 4. There are two distribution methods: one where the slabs are distributed sequentially to each of the three strands, and another where the whole is divided into three parts and then distributed. Furthermore, as shown in Figure 5, there are 2 × 2 × 2 = 8 possible manufacturing patterns for arranging the slabs in ascending or descending order by width, since each of the three strands has both ascending and descending order combinations.

[0092] Therefore, for each steel type, there are 2 × 8 = 16 possible manufacturing patterns. The generation unit 121 generates 16 manufacturing patterns for each steel type. The evaluation unit 122 derives evaluation values ​​for the manufacturing order of the slabs of the first and second steel types. The generation unit 121 then obtains the optimal manufacturing order, which is the combination of manufacturing patterns with the highest evaluation value for each of the 16 manufacturing patterns of the second steel type. Furthermore, the generation unit 121 generates combinations of manufacturing patterns by combining the 16 optimal manufacturing orders up to the second steel type and the 16 manufacturing patterns of the third steel type, and the evaluation unit 122 derives evaluation values ​​for 16 × 16 combinations. The generation unit 121 obtains the optimal combinations connected to each of the 16 manufacturing patterns of the third steel type. The process is similar for subsequent steps.

[0093] Even if the number of strands increases further, the process of generating combinations of manufacturing sequences starting with the first steel type to be manufactured using the method described above, deriving evaluation values, and obtaining the optimal combination can be repeated.

[0094] A cast assembly device having the above configuration also produces the same effects as the cast assembly device 1 described in Embodiment 1.

[0095] [Examples of implementation using software] The function of the cast arrangement device 1 (hereinafter referred to as "the device") is a program that causes a computer to function as the device, and can be realized by a program that causes a computer to function as each control block of the device (especially each part included in the rough cast arrangement unit 120).

[0096] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., memory) as hardware for executing the program. By executing the program using this control device and storage device, the functions described in each of the embodiments are realized.

[0097] The above program may be recorded on one or more computer-readable recording media, not temporary ones. These recording media may or may not be provided by the above device. In the latter case, the program may be supplied to the above device via any wired or wireless transmission medium.

[0098] Furthermore, some or all of the functions of each of the above control blocks can also be realized by logic circuits. For example, an integrated circuit in which logic circuits functioning as each of the above control blocks are formed is also included in the scope of the present invention. In addition, it is also possible to realize the functions of each of the above control blocks by, for example, a quantum computer.

[0099] Furthermore, each process described in the above embodiments may be performed by AI (Artificial Intelligence). In this case, the AI ​​may operate on the control device described above, or it may operate on other devices (for example, an edge computer or a cloud server).

[0100] The present invention is not limited to the embodiments described above, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention. [Explanation of Symbols]

[0101] 1... Casting device 100... Manufacturing schedule determination device 101... Slab Information File 102... Casting information file for the same steel type 103... Coil Information File 104... Casting Results File 105...Formation Condition File 110...Data entry section 120...Rough Casting Department 121...Generation section 122…Evaluation Department 130...Constraint Violation Resolution Unit S1…A flowchart showing the process of cast formation. S2…A flowchart showing the general process for casting a cast.

Claims

1. In a cast assembly apparatus that determines the manufacturing sequence of any intermediate product, such as a slab, bloom, or billet, A data input unit that inputs information regarding the order of multiple steel grades of the intermediate product manufactured by continuous casting using multiple strands, The system comprises a rough cast arrangement unit that generates an intermediate cast arrangement plan based on the aforementioned information, The aforementioned rough cast arrangement unit is A generating unit that generates information identifying the intermediate product to be distributed to each of the multiple strands, and multiple manufacturing sequences of the intermediate product to be manufactured in each strand, for the intermediate product included in the multiple steel grades in the aforementioned consecutive order, and Includes an evaluation unit that derives an evaluation value related to manufacturing efficiency for each of the generated manufacturing sequences, The generation unit generates a manufacturing pattern for the intermediate product included in the first steel grade to be manufactured and the intermediate product included in the second steel grade to be manufactured, including the manufacturing order of the intermediate product distributed to each of the multiple strands in ascending and descending order. For the intermediate product included in the nth (where n is an integer of 3 or more)th steel grade to be manufactured, for each manufacturing pattern of the (n-1)th steel grade, it generates a new manufacturing pattern combination by connecting the manufacturing pattern combination of the 1st to (n-1)th steel grades with the highest evaluation value and the manufacturing pattern of the intermediate product included in the nth steel grade, and repeats this process until n is the last steel grade. The evaluation unit derives the evaluation value for each of the new manufacturing pattern combinations until n becomes the last steel type. The combination of new manufacturing patterns that has the highest total evaluation value, or the evaluation value when manufacturing the nth steel type in each manufacturing pattern following the last intermediate product of the (n-1)th steel type, is selected as the proposed intermediate cast configuration. Casting device.

2. The data input unit further inputs at least one of the following: information regarding the width of the intermediate product and information regarding the permissible range of the composition of the intermediate product. The cast knitting apparatus according to claim 1, wherein the generating unit generates the ascending and descending manufacturing order for each strand by referring to at least one of the information relating to the width of the intermediate product and the information relating to the permissible range of the composition of the intermediate product.

3. The production unit distributes the intermediate product contained in one of the steel grades to each of the plurality of strands by repeatedly distributing by alternately assigning it to each strand in order of width, The cast assembly apparatus according to claim 1 or 2, wherein the assembly is performed using either of the following methods: dividing the continuous intermediate products sorted by width into the number of strands and distributing them to each strand; or

4. In a casting organization method for determining the manufacturing order of any intermediate product, such as a slab, bloom, or billet, A step of inputting information regarding the order of multiple steel grades of the intermediate product manufactured by continuous casting using multiple strands, The process includes a rough cast formation step of generating an intermediate cast formation proposal based on the aforementioned information, The aforementioned rough cast formation step is, The steps include generating information that identifies the intermediate product to be distributed to each of the multiple strands, and a plurality of manufacturing sequences for the intermediate product to be manufactured in each strand, for the intermediate product included in the multiple steel grades having a consecutive arrangement. For each of the generated manufacturing sequences, the steps include: deriving an evaluation value related to manufacturing efficiency; Includes, In the generation step described above, for the intermediate product included in the first steel grade to be manufactured and the intermediate product included in the second steel grade to be manufactured, a manufacturing pattern is generated that includes the manufacturing order of the intermediate product distributed to each of the multiple strands in ascending and descending order. For the intermediate product included in the nth (where n is an integer of 3 or more)th steel grade and subsequent steel grades to be manufactured, for each manufacturing pattern of the (n-1)th steel grade, a new combination of manufacturing patterns is generated by combining the manufacturing patterns of the 1st to (n-1)th steel grades with the highest evaluation value and the manufacturing pattern of the intermediate product included in the nth steel grade. This process is repeated until n is the last steel grade. In the step of deriving the evaluation value, for each of the new combinations of manufacturing patterns, the evaluation value is derived until n is the last steel type. The combination of new manufacturing patterns that has the highest total evaluation value, or the evaluation value when manufacturing the nth steel type in each manufacturing pattern following the last intermediate product of the (n-1)th steel type, is selected as the proposed intermediate cast configuration. Casting method.

5. In a cast scheduling program that determines the production sequence for any intermediate product, such as a slab, bloom, or billet, On the computer, A process for inputting information regarding the order of multiple steel grades of the intermediate product manufactured by continuous casting using multiple strands, Based on the aforementioned information, a rough cast formation process is performed to generate an intermediate cast formation proposal. The aforementioned rough cast organization process is, A process for generating information that identifies the intermediate product to be distributed to each of the multiple strands, and a multiple manufacturing order of the intermediate product to be manufactured in each strand, for the intermediate product included in the multiple steel grades having the aforementioned consecutive order. For each of the generated manufacturing sequences, a process is performed to derive an evaluation value related to manufacturing efficiency, Execute, In the generation process described above, for the intermediate product included in the first steel grade to be manufactured and the intermediate product included in the second steel grade to be manufactured, a manufacturing pattern is generated that includes the manufacturing order of the intermediate product distributed to each of the multiple strands in ascending and descending order. For the intermediate product included in the nth (where n is an integer of 3 or more)th steel grade to be manufactured, for each manufacturing pattern of the (n-1)th steel grade, a new combination of manufacturing patterns is generated by combining the manufacturing patterns of the 1st to (n-1)th steel grades with the highest evaluation value and the manufacturing pattern of the intermediate product included in the nth steel grade. This process is repeated until n is the last steel grade. In the process of deriving the evaluation value, for each combination of the new manufacturing pattern, the evaluation value is derived until n becomes the last steel type. The combination of new manufacturing patterns that has the highest total evaluation value, or the evaluation value when manufacturing the nth steel type in each manufacturing pattern following the last intermediate product of the (n-1)th steel type, is selected as the proposed intermediate cast configuration. Casting program.

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