Logistics plan creation method and logistics plan creation apparatus

Abstract

To provide a physical distribution plan generation method and a physical distribution plan generation device capable of generating a physical distribution plan which contributes to energy saving after guaranteeing the establishment of an operation.SOLUTION: This physical distribution plan generation method comprises: acquiring input information; updating the mounting temperature of a slab to a heating furnace on the basis of the surface temperature of the slab when it is extracted from a continuous casting machine, initial inventory information at a slab yard, and a facility item value between a steel making process and a rolling process by the continuous casting machine; generating physical distribution plan candidates at the slab yard on the basis of the mounting plan to the heating furnace; executing simulation for the physical distribution plan candidates; and selecting a physical distribution plan with heating constraints taken into account.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] This disclosure relates to a method and apparatus for creating a logistics plan. In particular, this disclosure relates to a method and apparatus for creating a logistics plan that takes into account the state of the slab when it is charged into a heating furnace, prior to a rolling process in which hot rolling is performed. [Background technology]

[0002] Many slabs cast during the steelmaking process are stored in a yard (hereinafter referred to as a slab yard) where they are temporarily allowed to dissipate heat before being rolled. After being incorporated into the logistics plan, the slabs are reheated in a furnace to a temperature suitable for rolling before being rolled. While stored in the slab yard, heat dissipation progresses through radiation and heat transfer, causing the temperature to drop. Reheating the slabs to the highest possible temperature is useful not only for improving manufacturing efficiency but also for saving energy by suppressing heat dissipation.

[0003] Patent Document 1 describes a method for calculating the temperature change of a slab from the torch cutting time of the slab, the slab temperature during continuous casting, the transport plan, and stacking information in the slab yard, and predicting the slab's furnace charging temperature.

[0004] The technology described in Patent Document 2 involves storing slabs to be cooled and slabs to be heated together in a slab yard, and when these steel billets are stacked on top of each other, the difference between the current temperature of each steel billet and the target temperature is expressed as a cost function. The stacking state of each steel billet is determined to minimize the cost function, and the steel billets are rearranged according to the determined stacking state. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Patent No. 6380510 [Patent Document 2] Patent No. 6354952 [Overview of the Initiative] [Problems that the invention aims to solve]

[0006] However, the technology described in Patent Document 1 predicts the slab charging temperature, but does not provide a means to further improve the charging temperature. Furthermore, while the technology described in Patent Document 2 can implement transport planning guidance aimed at improving the temperature of the entire slab in the yard, its cost function does not take into account the transport load in the slab yard.

[0007] In light of these circumstances, the purpose of this disclosure is to provide a logistics planning method and a logistics planning apparatus that can create a logistics plan that contributes to energy conservation while ensuring the success of operations. [Means for solving the problem]

[0008] (1) A logistics plan creation method according to one embodiment of the present disclosure is: A method for creating a logistics plan for a slab yard that stores slabs extracted from a continuous casting machine and loaded into a heating furnace, or slabs that are extracted from the heating furnace and loaded back into the heating furnace without undergoing the hot rolling process, in a rolling process in which slabs are hot-rolled in a hot-rolling mill, To acquire input information including inventory information, casting information, heating information, rolling information, and equipment information, Based on the surface temperature of the slab extracted from the continuous casting machine included in the casting information, the initial inventory information in the slab yard included in the inventory information, and the equipment specifications between the steelmaking process by the continuous casting machine and the rolling process included in the equipment information, the charging temperature of the slab into the heating furnace is updated. Based on the heating information and the rolling information, a candidate logistics plan for the slab yard is created. This includes running simulations on the candidate logistics plans and selecting a logistics plan that takes heating constraints into consideration.

[0009] (2) As one embodiment of the present disclosure, in (1), The consideration of the heating constraint is performed by selecting a logistics plan based on an evaluation formula including a term related to improving the charging temperature of the slab into the heating furnace and a term related to reducing the difference in the charging temperature of adjacent slabs in the heating furnace.

[0010] (3) As one embodiment of the present disclosure, in (1) or (2), Creating candidates for the logistics plan is performed in consideration of the grasping constraints of the crane and the stacking constraints.

[0011] (4) As one embodiment of the present disclosure, in any one of (1) to (3), The update of the charging temperature is performed by predictive calculation of the charging temperature of the slab into the heating furnace using a heat dissipation model formula of the slab assuming no heat transfer between slabs.

[0012] (5) As one embodiment of the present disclosure, in (4), The heat dissipation model formula is a regression formula based on the residence time until being charged into the heating furnace, and the difference between the predicted value and the actual value of the slab temperature at the time of charging into the heating furnace.

[0013] (6) A logistics plan creation device according to one embodiment of the present disclosure is A logistics plan creation device that creates a logistics plan for a slab yard that stores slabs extracted from a continuous casting machine and charged into a heating furnace or slabs that are extracted from the heating furnace and then charged back into the heating furnace without performing hot rolling in a rolling process of performing hot rolling on slabs by a hot rolling mill, An acquisition unit that acquires input information including inventory information, casting information, heating information, rolling information, and equipment information, Based on the surface temperature of the slab when extracted from the continuous casting machine included in the casting information, the initial inventory information in the slab yard included in the inventory information, and the equipment specifications values between the steelmaking process by the continuous casting machine and the rolling process included in the equipment information, the charging temperature of the slab into the heating furnace is updated. Based on the charging plan for the heating furnace included in the heating information and the rolling information, create candidates for the logistics plan of the slab yard. It includes an arithmetic unit that performs a simulation on the candidates for the logistics plan and selects a logistics plan in consideration of heating constraints.

[0014] (7) As one embodiment of the present disclosure, in (6), The consideration of the heating constraints is performed by selecting a logistics plan based on an evaluation formula including a term related to improving the charging temperature of the slab into the heating furnace and a term related to reducing the difference in the charging temperature of adjacent slabs in the heating furnace.

[0015] (8) As one embodiment of the present disclosure, in (6) or (7), The creation of the candidates for the logistics plan is executed in consideration of the grasping constraints of the crane and the stacking constraints.

[0016] (9) As one embodiment of the present disclosure, in any one of (6) to (8), The update of the charging temperature is performed by predictive calculation of the charging temperature of the slab into the heating furnace using a heat dissipation model formula of the slab assuming no heat transfer between slabs.

[0017] (10) As one embodiment of the present disclosure, in (9), The heat dissipation model formula is a regression formula based on the residence time until being charged into the heating furnace and the difference between the predicted value and the actual value of the slab temperature at the time of charging into the heating furnace. [Effect of the Invention]

[0018] According to the present disclosure, it is possible to provide a logistics plan creation method and a logistics plan creation device that can create a logistics plan that contributes to energy saving while ensuring the operation is established. [Brief Description of the Drawings]

[0019] [Figure 1]Figure 1 is a diagram illustrating a manufacturing line to which a logistics planning method according to one embodiment of this disclosure is applied. [Figure 2] Figure 2 is a schematic diagram of the slab yard. [Figure 3] Figure 3 is a diagram showing an example of the configuration of a logistics plan creation device and a processing flow of a logistics plan creation method according to one embodiment of the present disclosure. [Figure 4A] Figure 4A is a diagram illustrating heat transfer in a slab. [Figure 4B] Figure 4B is a diagram illustrating heat transfer in a slab. [Figure 4C] Figure 4C is a diagram illustrating heat transfer in a slab. [Figure 5] Figure 5 shows the process for determining candidate logistics plans. [Figure 6] Figure 6 shows the process flow for creating a list of candidate materials to be replaced. [Figure 7] Figure 7 shows the process for determining the feasible rearrangement order candidates. [Figure 8] Figure 8 is a diagram illustrating the difference in slab width. [Figure 9] Figure 9 shows the process for determining feasible logistics plan candidates. [Figure 10] Figure 10 shows examples of potential rearrangements. [Figure 11] Figure 11 shows the difference in error depending on whether or not the correction formula is applied. [Figure 12] Figure 12 is a table of physical properties based on carbon concentration. [Figure 13] Figure 13 shows the weighting coefficients based on carbon concentration. [Figure 14] Figure 14 shows the equipment specifications. [Figure 15] Figure 15 is a reference table for stacking constraints within a slab yard. [Figure 16] Figure 16 shows information about the slabs in the slab yard. [Figure 17] Figure 17 shows information regarding the casting plan. [Figure 18] Figure 18 shows information regarding the installation plan. [Figure 19] Figure 19 shows information regarding the updated installation plan. [Figure 20] Figure 20 shows examples of possible personnel changes. [Figure 21] Figure 21 shows a candidate logistics plan for pattern P1. [Figure 22] Figure 22 shows a candidate logistics plan for pattern P2. [Figure 23] Figure 23 shows a candidate logistics plan for pattern P3. [Figure 24] Figure 24 is a table of physical properties. [Figure 25] Figure 25 shows information regarding the charging plan based on pattern P1. [Figure 26] Figure 26 shows information regarding the charging plan based on pattern P3. [Figure 27] Figure 27 is a version of Figure 26 with actual temperatures added. [Modes for carrying out the invention]

[0020] A logistics plan creation method and logistics plan creation apparatus 10 (see Figure 3) according to one embodiment of the present disclosure will be described below with reference to the drawings.

[0021] Figure 1 illustrates a manufacturing line to which the logistics planning method according to this embodiment is applied. Slabs obtained by casting from molten steel in a continuous casting machine are transported by traverse carts to the hot rolling mill line. Each slab is heated in a heating furnace before being rolled in the hot rolling mill. Here, slabs arriving at the hot rolling mill are divided into direct-load materials that are loaded directly into the heating furnace via a transport table after arrival, and non-direct-load materials that are temporarily stored in the slab yard before being loaded. The slab yard can be used to temporarily store the arriving slabs.

[0022] Figure 2 is a schematic diagram of the slab yard. When non-direct materials are brought into the slab yard for temporary storage, the slabs on the traverse trolley are lifted by a crane and then piled up inside the slab yard (hereinafter sometimes referred to as "inside the yard"). The slabs in the yard are incorporated into the rolling plan, and when it is time to load them into the heating furnace, they are unloaded from the yard onto the traverse trolley by a crane and loaded into the heating furnace. If the target slab is not on the top of the pile during unloading, a rearrangement operation is performed to move the slabs stacked above the target slab to another pile, and then the unloading operation is performed. This rearrangement makes it possible to load the slabs into the heating furnace in an order different from the order in which they arrived from the continuous casting machine. After being loaded into the heating furnace, the slabs are heated to the appropriate temperature and then removed from the heating furnace. In the heating furnace, the slabs are removed in a first-in, first-out order and hot-rolled.

[0023] Figure 3 is a diagram showing an example configuration of the logistics planning device 10 according to this embodiment, and the arrows indicate the processing flow of the logistics planning method executed by the logistics planning device 10. As described above, the logistics planning device 10 creates a logistics plan for the slab yard in the rolling process in which slabs are hot-rolled in a hot rolling mill. The slab yard stores slabs that are not directly shipped, such as slabs extracted from a continuous casting machine and charged into a heating furnace, or slabs that are extracted from the heating furnace and then charged back into the heating furnace without being hot-rolled. In this embodiment, in the manufacturing line to which the logistics planning method is applied, the steelmaking process using a continuous casting machine and the rolling process in which slabs cast by the continuous casting machine are hot-rolled in a hot rolling mill are operated synchronously.

[0024] The logistics planning device 10 comprises an acquisition unit 11, a calculation unit 12, and an output unit 13. The logistics planning device 10 may be a computer as its hardware configuration. The logistics planning device 10 may also have the following software configuration: One or more programs used to control the operation of the logistics planning device 10 are stored in a storage device accessible from the logistics planning device 10. When the programs stored in the storage device are read by the processor (e.g., a CPU) of the logistics planning device 10, the processor is made to function as the acquisition unit 11, the calculation unit 12, and the output unit 13.

[0025] The logistics planning device 10 is configured to communicate with a higher-level system 20. The higher-level system 20 is a system that manages and controls a manufacturing line, including, for example, continuous casting and hot rolling, and may be composed of a different computer from the logistics planning device 10. The logistics planning device 10 acquires various data from the higher-level system 20, including the input information described later, which is necessary for calculations (simulation, charging temperature prediction using a model, etc.) for creating the logistics plan. The logistics planning device 10 also outputs the results of the calculations, including the created logistics plan, to the higher-level system 20.

[0026] The acquisition unit 11 acquires input information. The input information includes inventory information, casting information, heating information, rolling information, and equipment information. The inventory information includes information on slabs in the slab yard and slabs in transit. The inventory information includes initial inventory information, which is information on the inventory in the slab yard at the start of the calculation for creating the logistics plan performed by the calculation unit 12. The casting information includes information on the dimensions and steel type of the cast slabs. The casting information also includes information on the surface temperature of the slab at the time of torch cutting. The surface temperature at the time of torch cutting is the surface temperature of the slab that has been cast in a continuous casting machine and torch-cut to a predetermined length, and may be described as the surface temperature when extracted from the continuous casting machine. The heating information includes information on the slab in the heating furnace and the heating status. The heating information includes the scheduled time for charging into the heating furnace, which constitutes part of the plan for charging into the heating furnace. The heating information may also include the actual temperature value (measured temperature value) of the slab before charging into the heating furnace. The rolling information includes the rolling plan and rolling constraints. The plan for charging into the heating furnace may constitute part of the rolling plan. The rolling plan may be created, for example, by a known planning method by a higher-level system 20. The logistics planning device 10 can extract the heating furnace charging plan from the rolling plan and create a logistics plan for the slab yard in accordance with the heating furnace charging plan and in an operational manner. Equipment information includes whether each piece of equipment is faulty, equipment capacity specifications, and space constraints.

[0027] The calculation unit 12 receives input information from the acquisition unit 11 and performs calculations to create a logistics plan. In this embodiment, the calculations include a logistics simulation. The calculation unit 12 may determine whether the operation is feasible based on the simulation and exclude candidates that it determines are not feasible. The function unit of the calculation unit 12 that performs the simulation may be described as the simulator unit (logistics simulator). The calculations performed by the calculation unit 12 are not limited to simulations, and it may perform various calculations, judgments, and decisions related to the creation of a logistics plan. In this embodiment, the calculation unit 12 predicts the slab loading temperature using a model (calculation formula). The calculation unit 12 can also perform the optimization described later. The function unit of the calculation unit 12 that performs calculations and optimizations using the model may be described as the model unit.

[0028] The output unit 13 outputs the result of the calculation performed by the calculation unit 12. The result includes a logistics plan selected from the candidates created by the calculation unit 12. By receiving the logistics plan selected by the calculation unit 12 and controlling the manufacturing line according to that logistics plan, it is possible to improve manufacturing efficiency and save energy by suppressing heat dissipation.

[0029] The following describes the general processing in the calculation unit 12. The model unit creates candidate logistics plans within the yard at timings corresponding to events (e.g., plan changes) or at periodic intervals. Here, the approximate slab arrival time in front of the yard and the yard discharge time limit are defined. The approximate slab arrival time in front of the yard is a value calculated using past performance data, etc., for the time when the slab arrives in front of the slab yard via the traverse trolley. The yard discharge time limit is the time when the slab can be discharged in time for the scheduled time of charging into the heating furnace, and is a value calculated using past performance data, etc. More specifically, the yard discharge time limit is calculated from the lead time from the discharge command to arrival in front of the heating furnace, etc., based on past performance data, etc. The model unit passes the created candidate logistics plans to the simulator unit. Here, it is preferable that the model unit passes the candidate logistics plans to the simulator unit after excluding candidates that are clearly impossible to execute.

[0030] The simulator unit performs logistics simulations for each candidate logistics plan provided, using a discrete event model based on processing logic that includes queuing. The simulator unit removes candidates for logistics plans that include yard redistribution from the candidate group if they are unfeasible, for example, if the redistribution cannot be completed in time for the scheduled loading time or if the crane operating capacity is insufficient. It also simulates the arrival time of non-direct materials in the slab yard based on torch cutting time and equipment specifications, calculates the number of piles that can be received upon arrival, and creates candidate groups based on the number of possible piles. The simulator unit corrects the execution time of each transport command in the candidate group according to the simulation results and then selects the feasible plan candidates. The feasible plan candidates are sent to the model unit.

[0031] The model unit updates the temperature trend in accordance with the corrected transport time and predicts the loading temperature. For each slab temperature obtained from the loading temperature prediction, the model unit sets a function (evaluation formula) related to loading, performs optimization calculations, and finally selects one logistics plan, which is output via the output unit 13.

[0032] The details of the process are explained below. The creation of candidate logistics plans in the model unit may be performed at the following timings: the estimated arrival time of each slab in front of the slab yard, the scheduled time of charging each slab into the heating furnace, when the charging plan is updated, when determining whether the cast slabs are direct or not, and at regular time intervals. The logistics plan includes rearrangement patterns for charging. Slabs stacked above the material to be moved during rearrangement (hereinafter referred to as the material to be rearranged) may be returned to their original pile after the move, or they may remain moved. Crane gripping constraints and stacking constraints are considered when creating rearrangement in the candidate logistics plan. Figure 5 shows the process for determining candidate logistics plans, and rearrangement candidates are also created following the flow in Figure 5. For the process of creating the handling candidate group in Figure 5, the model unit reads the crane constraint parameters given in the input information and creates what combinations of crane movement are possible for the material to be rearranged, according to Figure 6. The crane grip width difference constraint and the crane grip length difference constraint are crane grip constraints regarding the difference in width and length of the slab, respectively, as described later. The crane grip weight constraint is a crane grip constraint regarding the weight of the slab. The crane grip thickness constraint is a crane grip constraint regarding the thickness of the slab. The model unit creates a group of handling candidates (i.e., a group of candidates for materials to be relocated and the equipment to transport the materials to be relocated) that satisfy all of these constraints. At this stage, the order of relocation is not considered, and the group of handling candidates is created from the perspective of how many materials to be relocated are transported simultaneously. The model unit performs the process shown in Figure 7 on the created group of candidates. In other words, the model unit creates a list of relocation order candidates and narrows down the number of feasible relocation destinations using various constraints. If there are multiple relocation destinations, the model unit may select the closest one. This allows for localized minimization of the handling load. The various constraints include constraints on the width and length when stacking the materials. For example, the difference in slab width is determined by comparing the width ω1 of the upper slab of the mountain with the width ω2 of the smallest slab in the lower slab, as shown in Figure 8, and is set as ω1-ω2. The width constraint is that this width difference must be less than or equal to the given maximum allowable width difference. Similar constraints apply to the length. In addition, the height is constrained to be less than or equal to the maximum allowable height.The model unit reads a reference table regarding stacking constraints (see Fig. 15) and narrows down candidates for assignment in consideration of stacking constraints.

[0033] In the simulator unit, a simulation of assignment is carried out for each pattern sent from the model unit, and the payout of the material to be loaded is also verified according to the loading time. The simulator unit deletes candidates for the logistics plan where the payout of the material to be loaded is not in time. Also, in order to determine an acceptable stack, the simulator unit conducts a simulation considering the arrival time of non-direct materials and deletes plan candidates without an acceptable stack as shown in Fig. 9. The simulator unit sets the candidate group narrowed down by these processes as executable plan candidates. Also, the simulator unit determines the predicted execution time of the conveyance order for each plan based on the simulation results. The executable plan candidates including the determined predicted execution time of the conveyance order are sent to the model unit.

[0034] The model unit performs predictive calculation of the loading temperature for the executable plan candidates from the simulator unit using the following formulas (1) to (3).

[0035] [Number]

[0036] Here, T t is the slab surface temperature (°C) at time t. T t-τ is the slab surface temperature (°C) at time t - τ. Δτ is the time interval for temperature update (seconds). C p is the specific heat of the slab (kJ / (kg·K)). W is the weight of the slab (kg). S is the surface area of the slab (m 2 ). θ is the slab surface temperature (°C). T a is the slab ambient temperature (°C). σ is the Stefan-Boltzmann constant (5.67×10 -8 E / (m 2 K 4 )). ε is the emissivity of the slab. α is the heat transfer coefficient between the slab and the atmosphere (W / (m 2The temperature is K). D is the slab thickness (m). λ is the thermal conductivity (W / (mK)). T is the mean cross-sectional temperature of the slab (°C).

[0037] Equations (1) and (2) are heat dissipation model equations for slabs, derived from the steady-state heat conduction equation, Fourier's law, or Newton's cooling method. Equation (3) is an equation for converting between slab surface temperature and cross-sectional mean temperature. Here, it is assumed that there is no heat transfer between slabs, and the surface area S of the slab changes depending on the position of the stacked slabs as shown in Figures 4A to 4C. Figure 4A shows that the slab is located in the middle of the stack in the yard, and heat transfer occurs from the four horizontal sides. D is the length of the slab in the direction in which the slabs are stacked (height direction) in the stack, and is the slab thickness mentioned above. W is the length in the width direction of the slab, i.e., the slab width. L is the length in the direction perpendicular to the height and width directions of the slab, i.e., the slab length. Figure 4B shows that the slab is located in the top or bottom of the stack in the yard, and heat transfer occurs from a total of five sides: four horizontal sides and one top or bottom side. Figure 4C shows that the slab forms a single mountain within the yard, and that heat transfer occurs from a total of six surfaces: four horizontal and two vertical.

[0038] Also, the slab atmosphere temperature (T a ) is given as a constant, such as an estimated value based on past performance. Specific heat of the slab (C p The specific heat (C) and thermal conductivity (λ) of a slab are generally known to depend on the carbon concentration and temperature. p The specific heat (C) and thermal conductivity (λ) of the slab are determined using a physical property table summarized for each carbon concentration of the slab, as shown in Figure 12. Here, the specific heat (C) of the slab is determined. p The temperature (λ) and thermal conductivity (λ) may be determined by linear interpolation when the temperature or carbon concentration is not found in the material properties table. When the mean cross-sectional temperature (T) of the slab lies between T1 and T2, the weighting coefficients q1 and q2 used in the interpolation are determined using equations (4) and (5).

[0039]

number

[0040] Furthermore, a table like the one in Figure 12 shows the carbon concentration c A , c B , c C If present for, the weight coefficient p A , p B , p C This is represented as shown in Figure 13. For example, the interpolation formula for thermal conductivity λ is expressed as (6).

[0041]

number

[0042] Here, .'' n1 (n=A, B, C) represents the carbon concentration c n This is the value of the thermal conductivity at temperature T1 in the table. Also, λ n2 (n=A, B, C) represents the carbon concentration c n This is the value of the thermal conductivity at temperature T2 in the table.

[0043] The model unit is optimized using the following equation (7). Here, equation (7) considers maximizing the charging temperature of each slab and reducing the load on combustion control. In other words, selecting a logistics plan that takes the maximum or minimum value (minimum value in this embodiment) in an evaluation formula like equation (7) corresponds to considering the heating constraint. Here, when using the evaluation formula of equation (7), a near-optimal solution may be evaluated as the optimal value. That is, even if it is not necessarily the maximum or minimum value, if the value of the evaluation formula is near the maximum or minimum value, it may be evaluated as the optimal value. Thus, the consideration of heating constraints is performed by selecting a logistics plan based on the evaluation formula. The first term of equation (7) is a term relating to reducing the difference in charging temperature between adjacent slabs in the heating furnace. The second term of equation (7) is a term relating to improving the charging temperature of slabs into the heating furnace.

[0044]

number

[0045] Here, I represents the set of slabs whose installation order has been determined. Also, T i is the charging temperature (°C) of slab "i". Optimization calculates all slab temperatures for each logistics plan, allowing for exhaustive search to derive the best solution. This method allows for the selection of an optimized charging plan while considering logistics. This enables improved manufacturing efficiency and energy savings through reduced heat dissipation.

[0046] The effects of this disclosure will be described in detail below based on the examples, but this disclosure is not limited to these examples.

[0047] Figure 14 shows the equipment specifications. Figure 15 shows the reference table for stacking constraints in the slab yard. Figure 16 shows the slab attributes and slab location information placed in the slab yard when input information is read. Figure 16 corresponds to the initial inventory information in the slab yard. Slabs are distinguished by a slab number, which is a unique number for each slab. For example, a slab with slab number 5 is written as slab "5". There are a maximum of 7 piles in the slab yard, and the names of the piles are defined as D1, D2, ..., D7 from the traverse trolley side. A maximum of 9 slabs can be stacked in one pile. The stacking order of slabs in a pile is such that the bottom layer is 1. For example, in a certain pile, the stacking order of the third slab from the bottom is 3. The ambient temperature in the slab yard (slab ambient temperature) is set to 700°C. Conveyor tables are managed in separate sections, and the separated conveyor tables have names such as TB1, TB2, ...

[0048] Figure 17 shows information regarding the planned casting schedule at 8:00:00 on August 1, 2021, which is the starting point for the plan update. Figure 18 shows information regarding the charging plan at the starting point for the plan update. Directly shipped materials are indicated as "Direct" in the Directly Shipped Materials (Direct / Non-Direct) column. Non-directly shipped materials are indicated as "Non-Direct" in the Directly Shipped Materials (Direct / Non-Direct) column. The logistics plan may be updated at the timing of the estimated arrival time in front of the slab yard obtained from the casting information and charging information, and the yard discharge time limit for each slab to be charged within the slab yard. In this embodiment, let's assume that the charging plan was updated to Figure 19 at 8:05:00 on August 1, 2021. In relation to the charging plan in Figure 19, the slab that needs to be rearranged is slab "4" from Figure 16. That is, slab "4" has a stacking order of 1 and is located at the bottom of the pile (D2). The materials to be rearranged are the other slabs "5" and "6" stacked in pile (D2). Based on the crane constraints in Figure 14, handling is created to transport slab "6" first, followed by slab "5", as shown in P1 and P2 in Figure 20. In addition, a total of three patterns are created, including a handling that transports slabs "5" and "6" simultaneously, as shown in P3 in Figure 20.

[0049] Next, potential relocation candidates that can be transported from each handling are created. The stacking standard value table is narrowed down to the possible relocation destinations, and for each handling command, the pile with the shortest transport distance among the possible relocation destinations is selected, as shown in Figure 10. Here, in Figure 10, "D" corresponds to slab "4", "E" to slab "5", and "F" to slab "6".

[0050] The simulator unit performs logistics simulations for three patterns. For P1 and P2, non-direct materials are received at D4, and candidate logistics plans including the predicted execution time of transport orders shown in Figures 21 and 22 are obtained. For P3, a candidate logistics plan shown in Figure 23 is obtained. Here, P2 was removed from the candidates because the disbursement of slab "5" was not completed in time for the scheduled loading time. Therefore, P1 and P3 were treated as feasible plan candidates. The model unit predicted the loading temperature for P1 and P3. Calculations were performed using the above formula and the physical property table in Figure 24, and loading plan information for P1 and P3 shown in Figures 25 and 26 was obtained. Through optimization calculations using formula (7), the evaluation value for P1 was calculated using formula (8). The evaluation value for P3 was calculated using formula (9).

[0051]

number

[0052] As a result, the P3 logistics plan was selected. Here, by feeding back the temperature actually measured during charging to the predicted charging temperature, the formulas for calculating the charging temperature prediction from the predicted and actual values ​​can be expressed as formulas (10) and (11).

[0053]

number

[0054] Here, c represents the correction of the prediction error obtained from the difference between the predicted temperature and the measured temperature. t (minutes) is the lead time from the torch cutting time to the time of actual measurement of the charging temperature. α and β are parameters related to the regression equation for the prediction error obtained from each slab. These parameters can be determined using the least squares method, etc. In other words, equations (10) and (11) are regression equations based on the residence time of the slab from after casting or extraction from the heating furnace until it is charged into the heating furnace, and the difference between the predicted slab temperature in the simulation and the actual slab temperature at the time of charging into the heating furnace.

[0055] When the best solution shown in Figure 26 was executed, the actual charging temperature shown in Figure 27 was obtained. At this time, α = -0.0646 and β = 4.0096 were obtained. By correcting the charging temperature using equations (10) and (11), the error in the predicted temperature can be reduced. When the error between the predicted and actual charging temperatures was compared before and after applying this correction formula over a long period (November 15, 2021 to January 4, 2022), it was confirmed that the RMSE improved with the application of the correction formula, as shown in Figure 11. The horizontal axis of Figure 11 is t (minutes). The vertical axis of Figure 11 is the error (°C) between the predicted and actual charging temperatures. The left figure of Figure 11 shows the case without applying the correction formula, and the right figure shows the case with applying the correction formula.

[0056] As described above, the logistics plan creation method and logistics plan creation apparatus 10 according to this embodiment can create a logistics plan that contributes to energy saving while ensuring the feasibility of operations through the above-described process and configuration. By following a logistics plan whose feasibility of operations, including multi-stage processes, is ensured through verification by logistics simulation, it is possible to avoid execution adjustments due to logistics capacity bottlenecks during actual operations, and efficient steel product manufacturing becomes possible. Furthermore, since the logistics plan is selected from multiple candidates to provide an improved charging temperature to the heating furnace and a low-load heating pattern operation of the heating furnace, energy savings can be achieved.

[0057] 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]

[0058] 10 Logistics planning device 11 Acquisition Department 12 Arithmetic section 13 Output section 20 Higher-level systems

Claims

1. A method for creating a logistics plan for a slab yard that stores slabs extracted from a continuous casting machine and loaded into a heating furnace, or slabs that are extracted from the heating furnace and loaded back into the heating furnace without undergoing the hot rolling process, in a rolling process in which slabs are hot-rolled in a hot-rolling mill, The process involves acquiring input information including inventory information, which includes initial inventory information, which is information on the inventory in the slab yard at the start of the calculation for creating the logistics plan; casting information, which includes information on the dimensions and steel type of the cast slabs; casting information, which includes information on the surface temperature of the slabs at the time of torch cutting; heating information, which includes the actual temperature value of the slabs and the scheduled time for charging into the heating furnace, which constitutes part of the plan for charging into the heating furnace; rolling information, which includes rolling constraints, which also constitute part of the plan for charging into the heating furnace; and equipment information. The charging temperature is predicted using the slab surface temperature and slab atmosphere temperature extracted from the continuous casting machine included in the casting information, Based on the initial inventory information, the past performance of traverse trolley travel time included in the equipment information, the equipment specifications between the steelmaking process by the continuous casting machine and the rolling process, the heating information, and the heating furnace charging plan included in the rolling information, it is determined whether there will be insufficient crane operating capacity at the time when the slab, predicted to arrive in front of the slab yard based on the torch cutting time and reflecting past performance of traverse trolley travel time, arrives in front of the slab yard, and it is determined whether the charging time into the heating furnace, calculated by adding the lead time from the dispensing order to the arrival of the slab in front of the heating furnace based on past performance data, will be sufficient. By eliminating candidates for the charging plan that cannot be executed, a candidate for the logistics plan of the slab yard is created. This includes performing a simulation using a discrete event model on the candidate logistics plans, excluding logistics plans that cannot meet the scheduled loading time or have insufficient crane operating capacity, and then selecting a logistics plan while considering heating constraints. The consideration of the heating constraints is carried out by selecting a logistics plan using an evaluation formula that includes the sum of the charging temperatures, which is a term relating to improving the charging temperature of the slab into the heating furnace, and the sum of the differences, which is a term relating to reducing the difference in charging temperatures between adjacent slabs in the heating furnace. The method for creating the aforementioned logistics plan involves determining whether a shortage of crane capacity will occur by considering crane gripping constraints that limit the differences in width, length, weight, and thickness of slabs grasped by the crane to be less than or equal to the crane's maximum allowable value, and stacking constraints that limit the height of slabs piled up in the slab yard to be less than or equal to a predetermined maximum allowable height.

2. The method for creating a logistics plan according to Claim 1, wherein predicting the charging temperature involves performing a calculation to predict the charging temperature of the slabs into the heating furnace using a heat dissipation model equation for slabs that assumes there is no heat transfer between slabs in the slab yard.

3. A logistics planning device for creating a logistics plan for a slab yard that stores slabs extracted from a continuous casting machine and loaded into a heating furnace, or slabs that are extracted from the heating furnace and loaded back into the heating furnace without undergoing the hot rolling process, in a rolling process in which slabs are hot-rolled in a hot-rolling mill, An acquisition unit acquires input information including inventory information, which is initial inventory information, which is information on the inventory in the slab yard at the start of calculation for creating a logistics plan; casting information, which includes information on the dimensions and steel type of the cast slabs; casting information, which includes information on the surface temperature of the slabs at the time of torch cutting; heating information, which includes actual slab temperatures and the scheduled time for charging into the heating furnace, which constitutes part of the plan for charging into the heating furnace; rolling information, which includes rolling plans and rolling constraints, which constitute part of the plan for charging into the heating furnace; and equipment information. The charging temperature is predicted using the slab surface temperature and slab atmosphere temperature extracted from the continuous casting machine included in the casting information. Based on the initial inventory information, the past performance of travel time on the traverse trolley included in the equipment information, the equipment specifications between the steelmaking process by the continuous casting machine and the rolling process, the heating information, and the plan for charging the heating furnace included in the rolling information, it is determined whether there will be insufficient crane operating capacity at the time when the slab, predicted to arrive in front of the slab yard based on the torch cutting time and reflecting past performance of travel time on the traverse trolley, arrives in front of the slab yard, and it is determined whether the charging time into the heating furnace, calculated by adding the lead time from the dispensing order to the arrival of the slab in front of the heating furnace based on past performance data, will be sufficient. By eliminating candidates for the charging plan that cannot be executed, a candidate logistics plan for the slab yard is created. The system includes a calculation unit that performs a simulation using a discrete event model on the candidate logistics plans, excludes logistics plans that cannot meet the scheduled loading time or have insufficient crane operating capacity, and then selects a logistics plan considering heating constraints. The consideration of the heating constraints is carried out by selecting a logistics plan using an evaluation formula that includes the sum of the charging temperatures, which is a term relating to improving the charging temperature of the slab into the heating furnace, and the sum of the differences, which is a term relating to reducing the difference in charging temperatures between adjacent slabs in the heating furnace. A logistics planning device that creates candidate logistics plans by determining whether a crane operating capacity deficiency will occur, taking into account crane gripping constraints that limit the width, length, weight, and thickness of the slabs grasped by the crane to be less than or equal to the crane's maximum allowable value, and stacking constraints that limit the height of the slabs stacked in the slab yard to be less than or equal to a predetermined maximum allowable height.

4. The logistics planning device according to claim 3, wherein predicting the charging temperature involves performing a prediction calculation of the charging temperature of the slabs into the heating furnace using a heat dissipation model equation for slabs that assumes there is no heat transfer between slabs in the slab yard.

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