JP4930152B2 - Steel product production planning method, manufacturing method and program thereof - Google Patents

Description

  The present invention relates to a production plan method for a steel bar product, a plurality of orders having different dimensions on a billet, a plurality of billets required for the order are designed, and a production plan for the plurality of billets is created, a production method thereof, and Regarding the program.

As a conventional method for manufacturing a steel bar product, for example, in order to handle inconsistent evaluation indices of yield and workability, two independent algorithms are executed in parallel, and either one is adopted based on a predetermined evaluation index. Has been proposed (see, for example, Patent Document 1).
Japanese Patent Application No. 2001-333092

  In the conventional production planning method, two independent algorithms are executed in parallel and either one is adopted based on a predetermined evaluation index, which is called yield and workability. The purpose was to make flexible judgments according to the characteristics and production status of the target product when handling contradictory evaluation indices. However, there is a problem that it is difficult to obtain a solution that satisfies both the yield and workability because it is an alternative.

  The present invention solves the above-mentioned problems, and provides a production planning method for steel products, a method for producing the same, and a program capable of producing the products satisfying the production constraints and improving both yield and workability. The purpose is to do.

The steel product production planning method according to the present invention includes a billet product production plan including a billet design process in which a plurality of orders with different dimensions are combined on a billet and a plurality of billets required for all orders are designed. A method,
The billet design process includes:
A data input process for capturing a plurality of orders stored in a storage device;
A data classification process for classifying each order into a plurality of groups that can be processed in parallel based on the operating conditions of the finishing equipment and the order length ;
Based on the identification of the data classification process, the combination of the orders selected one by one from the plurality of groups is put together on the virtual billet, and after the order of one kind in the group is cut off, the next different kinds of orders Repeat the procedure to start taking out all orders and calculate the evaluation index, repeating the series of operations multiple times while replacing the remaining number of orders with the initial number of orders , and the results obtained from the multiple operations And adopting a result having the largest evaluation index as a solution and storing it in a storage device.

The steel product production planning method according to the present invention includes a billet product production plan including a billet design process in which a plurality of orders with different dimensions are combined on a billet and a plurality of billets required for all orders are designed. A method,
The billet design process includes:
A data input process for capturing a plurality of orders stored in a storage device;
A data classification process for classifying each order into a plurality of groups that can be processed in parallel based on the operating conditions of the finishing equipment and the order length ;
Based on the identification of the data classification process, the combination of the orders selected one by one from the plurality of groups is put together on the virtual billet, and after the order of one kind in the group is cut off, the next different kinds of orders Repeat the procedure to start taking out all the orders and repeat the series of operations to calculate the evaluation index multiple times when executing, and the result of the multiple times of the number of billets When the small solution is temporarily stored in the storage device as the best solution, the total length of the order is divided by the maximum slab length and the fractional part is rounded up, and the difference between the number of slabs of the best solution is large. Temporarily and partially alleviating the restriction of taking off one order in the group, recalculating the arrangement on the virtual billet, adopting the best solution obtained, and storing it in storage. And a step of.

Moreover, the manufacturing method of the bar product which concerns on this invention manufactures a several steel piece according to the design result of the steel piece obtained by said production planning method, The manufacturing method of the bar product characterized by the above-mentioned.
Further, the program according to the present invention causes a computer to execute each step of the production plan for the above-mentioned long steel product.

According to the present invention, since orders are sequentially arranged so as to guarantee the order of input to the finishing equipment, improvement in workability can be ensured. Under this condition, the initial solution was changed several times, and multiple evaluation indicators including yield were adopted as the best results, so the yield and other evaluation indicators were also used simultaneously. It can be improved.
In addition, according to the present invention, a method for searching for the best solution for a plurality of evaluation indexes including yields under the conditions is applied, with the order of input to the finishing equipment being constrained to ensure workability. In doing so, the case where only a solution with a deteriorated yield index can be obtained is determined from the result, and the restriction is relaxed partially or temporarily, so that production satisfying the production restriction is possible, and Thus, both the yield and workability are improved, and it becomes possible to design a steel bar product that matches the attributes of the order group to be designed.

Embodiment 1. FIG.
FIG. 1 is a system configuration diagram for carrying out the first embodiment of the present invention. This system includes a billet design and production instruction computer (hereinafter referred to as a computer) 10, a database 11, a terminal 12, and a production facility 13. Various order information from the terminal 12 is input to the computer 10, and is temporarily stored in the database 11. The database 11 includes an order file 21, a billet assembling file 22, and a billet production plan file 23. The order file 21 stores various kinds of order information from the terminal 12.

The computer 10 performs the following processing.
(A) First, design conditions and facility operation conditions are input / referenced / changed at the terminal 12 and stored in an order file. The computer 10 reads the information in the order file 21, decides the billet assembling while referring to the design condition and the equipment operation condition, and stores it in the billet assembling file 22.
(B) Next, the computer 10 creates a production plan based on the information of the billet assembling file 22 and stores it in the billet production plan file 23.
(C) The computer 10 supplies the manufacturing plan information stored in the billet manufacturing plan file 23 to the manufacturing equipment 13, and the manufacturing equipment 13 operates the equipment based on the manufacturing plan information, and the steel is produced according to the production plan. Manufacture pieces.

Table 1 shows an example of an order group stored in the order file 21 (here, a simple case is shown for convenience of explanation). In the first embodiment, six types of order groups are set, and the total length is 616 m. In the first embodiment, when the assembling length of the steel slab is set to, for example, Max 70 m, an order group with a total length of 613 m is created with a maximum steel slab length of 70 m,
616m ÷ 70m = 8.8 (book)
It can be seen that it can be manufactured with a minimum of 9 steel pieces.

  Table 2 is an example of the refinement processing group classification. In this example, classification is made into three types of A (small), B (medium), and C (large) according to the order length. Here, the finishing equipment refers to a piling device. The piling apparatus creates a transport lot (pile) by stacking a plurality of products of the same length received one by one from the upstream. The transport lot is a unit that can be handled collectively by a crane or the like, and it is preferable to reduce the number in order to improve workability.

  FIG. 2 is a flowchart showing details of the above-described billet design process, and the computer 10 performs various arithmetic processes according to the flowchart.

(S11) The order data (see Table 1) is fetched from the order file 21.
(S12) The order data (see Table 1) is classified according to the groups (A to C) in Table 2. That is, the group to which each order belongs is classified.
(S13) An assembling pattern for the order data classified as described above is created.
(S14) The assembling length range is read from the order file 21. In this example, the assembling length range is set to 70 m as described above.
(S15) Next, the following processing is performed to create the first pattern (first type). A combination of all orders of the group (A to C) is tried. In other words, orders are appropriately extracted from each group and combined. In that case, the number from each group includes 0, 1 or 2 or more. Then, an evaluation index is calculated for the combination.

Here, the evaluation index is based on the following (1) to (3).
(1) Assortment length The closer to the MAX assembling length, the better. In the billet design problem, there is a restriction that the entire order group can be taken out. Therefore, it is highly possible that the billet number can be reduced as the assembling length increases. Since a rounded part is always generated for each steel slab and the yield decreases, the number of steel slabs and the yield are inversely proportional.
(2) Number of pieces of steel that can be collected in the same pattern. When combined with the above (1), it is convenient in terms of yield and the number of types of steel slabs in that many steel slabs can be designed as long as possible. Although the number of types of billet length will be described later, it is a limitation when casting a billet in the upstream process of strip production, and it is better to have a smaller number of types, so it matches this evaluation index.
(3) Use up of orders It is desirable to use up the contained orders by adopting this pattern. If the order cannot be used up, there is a restriction that it can be used continuously when creating the next pattern.

(S16) The evaluation indexes are sorted in descending order of the evaluation indexes. Specifically, first, sorting is performed according to the “(1) assembling length”, and then the sorted one is sorted according to the “(2) number of steel pieces that can be collected in the same pattern”. Finally, the sorted items are sorted in three stages, ie, sorted according to the above-mentioned “(3) Order use up”. Of course, the sorting method is not limited to the above-mentioned example, and it goes without saying that it can be appropriately changed as necessary. For example, the above (1) to (3) are assigned evaluation points. You may make it sort by it. Table 3 shows the result of sorting as described above. In Table 3, the top of the sorted combinations is shown. Table 3 shows a state after sorting the results of the total length of 70 m on the basis of the above three evaluation indexes, and adopts a pattern having the maximum number of steel pieces that can be collected in the same pattern.

(S17) A plurality of patterns in Table 3 are stored in the steel piece assembling file 22. In this example, for example, an example of the top three combinations is stored. These three patterns are respectively adopted as one pattern (first type) as described later.
(S18) The top two items in Table 3 are extracted and determined as the first pattern (first type). Here, 1 × 2 (2) 18m, 3 × 2 (6), 15m, and 1 × 2 (2) 7m are adopted. FIG. 3A shows a state where the first pattern thus formed is adopted.
(S19) When the top second item in Table 4 is extracted as the first pattern, as shown in “Remaining” in FIG. 3B, the remaining orders are 8 for 21m and 5 for 18m. -2 = 3, 15m is 0, 13m is 7, 9m is 9, and 7m is 15-2 = 13. Based on the remaining order data, it is determined whether there is an in-group continuous order after the second pattern (second type). In this example, since there is an in-group continuation order (see “continuation” in FIG. 3B), it is determined that there is an in-group continuation order.

(S20) Then, all combinations of continuous orders within the group are tried.
(S21) If it is determined that there is no in-group continuous order, all combinations of all remaining orders in the group and other group continuous orders are tried.
(S22) Next, it is determined whether or not there is an order cancellation and an in-group remaining order for the tried combination, and if the determination is YES, the process proceeds to processing (S21), and if NO, The process proceeds to processing (S23).
(S23) The following one type is added from the group and the arrangement is tried (see FIG. 3C).
(S24) It is determined whether or not the combination is within the assembling length range. If it is not within the assembling length range, the process returns to the above-described process (S23) and the process is repeated.
(S25) When it is determined in the above determination (S24) that it is the assembling length range and when it is determined NO in the above determination (S22), the result of the combination so far is used as the above evaluation index. Sort in descending order. FIG. 3D shows what is sorted in this way.

(S26) Of the sorted combinations, the highest one is stored in the steel piece assembling file 22 as a solution candidate. Thus, for example, the combination of the second pattern (second type) in Table 4 described later is determined.
(S27) Next, it is determined whether there is a remaining order.
(S28) If the remaining order still remains, the remaining order number is updated. The remaining order number at this time is as shown in FIG. Thereafter, similarly to the above example, the processes (S18) to (S28) are repeated, and when there is no remaining order, the process proceeds to the process (S29).
(S29) Here, it is determined whether or not the predetermined number of times (three times in this example) has been completed.
(S30) If it is determined that the process has not been completed, the remaining number of orders is initialized, and the process proceeds to the above process (S18). Here, the second pattern in Table 3 above is adopted as the first pattern (first type), and the above processing (S18) to (S39) is repeated in the same manner. The first, second, and third are the first pattern (first type), respectively, and three assortment patterns are created. If three are created, the process proceeds to the next process (S31). . Table 4 shows an example of the assembling pattern created as described above. In the first embodiment, three such tables as shown in Table 4 are created. Of course, this number is arbitrary.

  Up to the fifth steel slab in Table 4, assembling is performed in one order from each processing group for each steel slab. However, in the case of the sixth type of steel bill, when one 13m order and four 7m orders are combined, all orders that have continued from the previous pattern have been used. Therefore, a steel piece with a total length of 68 m is designed by assembling three 9 m pieces from the same A group as the 7 m order. Since the 7m order and the 9m order are processed by the same piling apparatus with fine adjustment, it is not desirable to put them into the apparatus while both are mixed. When saving the slab design results, the order of arrangement in the slabs should be 7m x 4 first, then 9m x 3 and satisfy the preceding and following relationship, and the result will be Output to.

  In Table 4, a surplus length of 2 m (= steel piece combination length MAX−pattern combination length) is generated in the sixth steel piece. This is due to the refinement processing group constraints. Table 5 shows the results when the restrictions are removed by the above processing. In the sixth steel slab, only 3 pieces are used without taking a 7m order, and 4 pieces of 9m orders of the same group are used, thereby realizing an assembling length of 70m. However, in this case, the same order is not continuously put into the piling apparatus, and there is a possibility that the conveyance lot is enlarged and workability is lowered.

(S31) All results obtained by processing as described above are sorted in descending order of evaluation index. For example, this evaluation index is as follows.
(1) Number of steel pieces It is better that the number of steel pieces is small. As described above, a rounded part is always generated for each steel slab and the yield is lowered, so the number of steel slabs and the yield are inversely proportional. Therefore, a solution with a small number of steel pieces has a good yield.
(2) Number of steel slab length types The number of steel slab length types is better. As described above, as a restriction when casting a steel slab in the upstream process of strip manufacturing, a steel slab handling property is improved when the number of types of steel slabs is small, and distribution costs can be reduced.

(S32) Among the solutions sorted according to the above evaluation indexes, the solution having the best evaluation index is adopted and stored as the optimal solution. This is reflected in the manufacturing order output to the manufacturing facility.

  The reason why only the top one of a plurality of pattern candidates is adopted in the second and subsequent patterns is an example of a plurality of means considering the processing time and the accuracy of the solution, and limits the present invention. is not. However, in this problem that keeps organizing the same order, the choice of the first pattern has the most influence on the quality of the solution, and holding multiple solutions after the second pattern tends to increase the calculation time. You need to be careful.

  As described above, according to the first embodiment, the orders are sequentially arranged so as to guarantee the order of loading into the finishing equipment, so that the workability can be improved. Under this condition, the initial solution was changed several times, and multiple evaluation indicators including yield were adopted as the best results, so the yield and other evaluation indicators were also used simultaneously. It can be improved.

Embodiment 2. FIG.
Next, a production planning method according to Embodiment 2 of the present invention will be described. The system configuration of the second embodiment is the same as that shown in FIG. Further, an example of the order data described here is as shown in Table 6, and the refinement generation processing group classification is as shown in Table 2 above.

  4 and 5 are flowcharts showing the process of the production planning method according to the second embodiment. The processes S11 to S32 in FIG. 4 are the same as the processes S11 to S32 in FIG. 2 and the details thereof are omitted, but the process S33 is added in FIG. This process S33 determines whether or not the process so far is a process from (A) after storing the highest rank as a solution candidate in process S26 (see FIG. 5), and is not a process from (A). In the case, the process proceeds to the process (S27), and in the case of the process from (A), the process proceeds to the process S52 in FIG. In the first process, since the process so far is not (A), the process proceeds to process (27). Accordingly, in the first processing stage, the same processing as the processing of FIG. 2 is performed. In the second embodiment, after the best solution is stored in the process S32, the process proceeds to the process of FIG. 5 to verify the solution. In the process of FIG. 4, it is assumed that the solution shown in Table 7 is obtained next.

(S41) First, the theoretical number of order groups is calculated. The theoretical number is a numerical value obtained by dividing the total order length by the combined length Max and rounding up the decimal number, and means the minimum number that can be realized. In the second embodiment, the total order length is 554 m, and the assembling length Max is 70 m.
554m ÷ 70m = 7.91 → 8 Therefore, the theoretical number is 8.

  On the other hand, the number of steel slabs in Table 7 is 9, which is one difference from the theoretical number. As already described, an increase in the number of steel slabs is directly linked to an increase in cut-off portions, that is, a decrease in yield, so it is desired to suppress as much as possible. In Table 7, a surplus length (= steel piece combination length MAX−pattern combination length) occurs in the third and subsequent steel pieces. This is due to the refinement processing group constraints. Since the order group in Table 7 has a smaller number of Group A than other groups, there are often cases where only two types can be combined in the same billet, but the remaining length is frequently accumulated. As a result, the number of steel pieces increased.

(S42) It is determined whether the number of steel pieces> theoretical number + threshold value 1 is satisfied. Here, the threshold value 1 for determining the difference between the theoretical number and the design result (the number of steel pieces) is set to 0 in the second embodiment. That is, if even one difference occurs, the processing subsequent to the processing (S44) is performed.
(S43) If the theoretical number is equal to the design result (the number of steel pieces), the best solution is stored as the optimum solution and the process is terminated.
(S44) When the design result (the number of steel slabs) is larger than the theoretical number, the theoretical surplus length is obtained by the following equation.
Theoretical surplus length = theoretical number × arrangement length max−order total length This means the maximum value of the surplus length allowed to maintain the minimum feasible number. If this example is applied to the above equation, the theoretical excess length is
8 x 70m-554m = 6m
It becomes.
(S45) The steel pieces of the best solution are sequentially read out one by one.
(S46) Then, it is determined whether or not there is a remaining steel piece. If it is determined that there is a remaining steel piece, the process proceeds to processing (S47). If it is determined that there is no, the process proceeds to later-described processing (S56).
(S47) Here, the remaining theoretical length and the remaining theoretical number after selection are obtained by the following equations.
Theoretical remainder length = theoretical remainder length−the surplus length cumulative number after selection Theoretical number of theory = theoretical number−reading billet number cumulative sum (S48) Next, the average surplus length margin is obtained by the following equation.
Average excess length margin = theoretical remainder length ÷ theoretical remaining number after selection Theoretical remainder length is 0 and the theoretical number is just below the limit. If the theoretical remainder length is negative, the theoretical number cannot be realized and the number increases.
(S49) Next, it is determined whether or not the change in average surplus margin <-threshold value 2 is satisfied. If it is satisfied, the process proceeds to processing (S50). The process proceeds to S45). In this example, the threshold value 2 is set to 0, for example. For example, when the third steel slab is assembled, the average extra length margin change is -0.45 = 0.75-1.2.
Then, it is below the threshold value 2.
(S50) Next, it is determined whether there is a group in which a plurality of orders with the remaining number ≧ 2 remain. That is, returning to the time immediately before assembling the steel pieces, it is inspected whether there is a group in which two or more orders with a remaining number of two or more remain. In the case of the remaining order 1 or when only one kind of order remains in the group, it is not possible to expect the effect of relaxing the restriction on the completion of one kind of order in the group within the billet. Therefore, in order to give up the redesign of the steel slab and determine whether to reduce the threshold value 2 or adopt the best solution as it is, the process proceeds to the process (S56) described later.
(S51) If there is a group that satisfies the conditions in the above determination (S50), in order to redesign the steel piece, a group with the maximum remaining order number in the group is searched for and temporarily placed Remove the limit. In this example, in Group A, 21m is 7 remaining and 18m is 5 remaining, so the minimum number of remaining orders in the group is 5. Similarly, since the B group is 1 and the C group is 1, the A group is selected. This is to maximize the degree of freedom in setting the assembling length by relaxing the constraints.

After the above processing (S51), the processing after processing (S19) in FIG. 4 is processed in the same manner as in the first embodiment, and in processing (S33), the processing from (A) above is performed. It is determined whether or not there is, but here, since the process is from (A), the process returns to the flowchart of FIG. 5 again and proceeds to the process (S52).
(S52) The remaining order number is updated here.
(S53) Then, it is determined whether there is a remaining order.
(S54) When it is determined that there is an order remaining number, the order cancellation restriction is added again. And the process after the process (S19) of FIG. 4 will be repeated.
(S55) If it is determined in the above process (S53) that there is no remaining order, the solution at that time is stored as the best solution and the process is terminated.
(S56) Here, it is determined whether or not there is room for lowering the threshold value 2.
(S57) If it is determined that there is no room for lowering the threshold value 2, the previous solution is stored as the best solution and the processing is terminated.
(S58) If it is determined that there is room for lowering the threshold 2, the value of the threshold 2 (0> 0) is appropriately reduced, and the process proceeds to the processing (S45). Repeat the process.

  Table 8 shows the solutions obtained by the above processing. Table 8 shows the results of the steel slab design with partial relaxation of the precise ordering restrictions. As a result of restraint relaxation in the third steel slab, it is possible to suppress the occurrence of surplus length, and the design is finished with the theoretical number of eight. Then, the result is reflected in the manufacturing order output to the manufacturing facility.

  In the second embodiment, the allocation of the surplus material to the surplus length is not considered, but the surplus material (not included in the order to be designed this time but of a size that may be received in the future) In the case of assigning a pre-made), it is necessary to change the definition of the theoretical surplus length and further reduce the total surplus length from the above formula. When two or more types of steel slab length can be set, a plurality of assortment lengths are assigned to the temporarily stored best solution, and the theoretical number is calculated from the result.

  As described above, according to the second embodiment, in order to guarantee workability, the order of introduction into the finishing equipment is constrained, and a plurality of evaluation indexes including yields search for the best solution under the conditions. When applying this method, it was determined from the results that only yielded solutions with a degraded yield index were obtained, and partial or temporary relaxation of the constraints was performed. It is possible to design steel products that meet the requirements.

It is a system configuration diagram for carrying out Embodiment 1 of the present invention. It is a flowchart which shows the process of the said Embodiment 1. FIG. It is explanatory drawing of the process of FIG. It is a flowchart (the 1) which shows the process of Embodiment 2 of this invention. It is a flowchart (the 2) which shows the process of the said Embodiment 2. FIG.

Explanation of symbols

  10 computers, 11 databases, 12 terminals, 13 manufacturing equipment, 21 order files, 22 assortment files, 23 billet manufacturing plan files.

Claims (4)

A method for producing a steel bar product comprising a billet design process in which a plurality of orders having different dimensions are combined on a billet and a plurality of billets necessary for all orders are designed,
The billet design process includes:
A data input process for capturing a plurality of orders stored in a storage device;
A data classification process for classifying each order into a plurality of groups that can be processed in parallel based on the operating conditions of the finishing equipment and the order length ;
Based on the identification of the data classification process, the combination of the orders selected one by one from the plurality of groups is put together on the virtual billet, and after the order of one kind in the group is cut off, the next different kinds of orders Repeat the procedure to start taking out all orders and calculate the evaluation index, repeating the series of operations multiple times while replacing the remaining number of orders with the initial number of orders , and the results obtained from the multiple operations A method for planning the production of steel bar products, comprising the step of adopting a result having the largest evaluation index as a solution and storing the result in a storage device. A method for producing a steel bar product comprising a billet design process in which a plurality of orders having different dimensions are combined on a billet and a plurality of billets necessary for all orders are designed,
The billet design process includes:
A data input process for capturing a plurality of orders stored in a storage device;
A data classification process for classifying each order into a plurality of groups that can be processed in parallel based on the operating conditions of the finishing equipment and the order length ;
Based on the identification of the data classification process, the combination of the orders selected one by one from the plurality of groups is put together on the virtual billet, and after the order of one kind in the group is cut off, the next different kinds of orders Repeat the procedure to start taking out all the orders and repeat the series of operations to calculate the evaluation index multiple times when executing, and the result of the multiple times of the number of billets When the small solution is temporarily stored in the storage device as the best solution, the total length of the order is divided by the maximum billet length and the fractional part is rounded up, and the difference between the number of billets in the best solution is large. Temporarily and partially alleviating the restriction of taking off one order in the group, recalculating the arrangement on the virtual billet, adopting the best solution obtained, and storing it in storage. Long products production planning method characterized by comprising the step of.   A method for manufacturing a strip steel product, wherein a plurality of steel slabs are manufactured according to a design result of the steel slab obtained by the production planning method according to claim 1 or 2.   A program for causing a computer to execute each step of the production plan for the long steel product according to claim 1 or 2.

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