Information process system, information processing method, information processing program, and demolition policy creation system

Abstract

To support the planning of a component demolition policy meeting the current demand when demolishing a vehicle such as a car and recycling components, etc.SOLUTION: An information process system comprises a storage device which stores a prescribed index calculation model on each component provided in a vehicle, and an arithmetic device which calculates the current priority of each component taken out after a specified vehicle has been demolished by inputting a time-series change of the past demand of each component provided in a specified vehicle into the index calculation model.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing method, an information processing program, and a disassembly guideline creation system. [Background technology]

[0002] As environmental considerations grow, businesses that dismantle vehicles such as automobiles and recycle their parts are gaining attention. The demand for recycled parts from dismantled automobiles varies greatly depending on the change in the market value of the parts, the degree of damage to the parts, or the detailed model number. On the other hand, the supply side, i.e., the number of vehicles to be dismantled, the model of each vehicle, the degree of damage, etc., is not constant, and the stock situation of parts in the inventory of automobile dismantler companies changes from moment to moment, so the balance between demand and supply tends to be unstable. Therefore, there is a tendency for dismantling policies, such as which parts of dismantled vehicles are given priority for dismantling and produced as used parts, to vary.

[0003] In response to such issues, Patent Document 1 discloses a technology for identifying vehicle models for which the number of parts for which there is provisional reservation data for dismantled vehicle parts is a certain percentage or more compared to the total number of dismantled vehicle parts, as priority dismantling vehicle models. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2005-208909 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the technology described in Patent Document 1 identifies only temporary demand on a spot basis from provisional reservation data, and is unable to grasp ever-changing demand. Furthermore, it does not take into account the supply side, for example, the inventory status of vehicles or parts to be dismantled at automobile dismantling companies. Therefore, the technology described in Patent Document 1 has an issue in that it is difficult to formulate a dismantling policy for used parts that matches demand in the used vehicle parts industry, where the balance between supply and demand is unstable as described above.

[0006] The present invention has been made in consideration of the above circumstances, and an object of the present invention is to provide an information processing system, an information processing method, an information processing program, and a dismantling policy creation system that are capable of supporting the formulation of a part dismantling policy that matches demand. [Means for solving the problem]

[0007] One aspect of the present invention for solving the above problem is an information processing system including a storage device that stores a predetermined index calculation model for each part installed in a vehicle, and a calculation device that calculates a priority of each part to be removed by dismantling the specified vehicle by inputting a time series change in past demand for each part installed in a specified vehicle into the index calculation model. Effect of the Invention

[0008] According to the present invention, it is possible to support the formulation of a part dismantling policy that meets demand. Configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a dismantling policy creation system according to a first embodiment. [Diagram 2] FIG. 13 is a diagram illustrating an example of a demand amount management table. [Diagram 3] FIG. 11 is a process flow diagram illustrating an overview of a first priority calculation process. [Figure 4]FIG. 13 is a diagram showing an example of a priority display screen. [Diagram 5] FIG. 11 is a diagram illustrating an example of a configuration of a dismantling policy creation system according to a second embodiment. [Figure 6] FIG. 13 illustrates an example of a parts management table. [Figure 7] FIG. 11 is a process flow diagram illustrating an overview of a second priority calculation process. [Figure 8] FIG. 13 is a diagram illustrating an example of the configuration of a dismantling policy creation system according to a third embodiment. [Figure 9] FIG. 13 illustrates an example of a part state management table. [Figure 10] FIG. 11 is a process flow diagram illustrating an overview of a third priority calculation process. [Figure 11] FIG. 13 is a diagram illustrating an example of the configuration of a dismantling policy creation system according to a fourth embodiment. [Figure 12] FIG. 13 illustrates an example of a KPI management table. [Figure 13] FIG. 11 is a process flow diagram illustrating an outline of a weighting process. [Figure 14] FIG. 2 is a diagram illustrating a vehicle model. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. The following description and drawings are examples for explaining the present invention, and appropriate omissions and simplifications are made for clarity of explanation. The present invention can be implemented in various other forms. Unless otherwise specified, each component may be singular or plural. In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings. In the following explanation, various information may be explained using expressions such as "table," "list," and "queue," but the various information may be expressed in other data structures. To indicate independence of data structure, "XX table," "XX list," and the like may be referred to as "XX information." When explaining identification information, expressions such as "identification information," "identifier," "name," "ID," and "number" are used, but these are interchangeable. When there are multiple components having the same or similar functions, they may be described by using the same reference numerals with different subscripts. However, when there is no need to distinguish between these multiple components, the subscripts may be omitted. In addition, in the following description, the processing performed by executing a program may be described, but the program is executed by a processor (e.g., CPU, GPU) to perform a defined process using storage resources (e.g., memory) and / or interface devices (e.g., communication ports) as appropriate, so the subject of the processing may be the processor. Similarly, the subject of the processing performed by executing a program may be a controller, device, system, computer, or node having a processor. The subject of the processing performed by executing a program may be a calculation unit, and may include a dedicated circuit (e.g., FPGA or ASIC) that performs a specific process. A program may be installed in a device such as a computer from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and a storage resource for storing a program to be distributed, and the processor of the program distribution server may distribute the program to be distributed to other computers. In the following description, two or more programs may be realized as one program, and one program may be realized as two or more programs.

[0011] [First embodiment] First, an information processing system, an information processing method, and an information processing program according to a first embodiment of the present invention will be described.

[0012] <System configuration> 1 is a diagram showing an example of the configuration of a dismantling policy creation system 1 in this embodiment. The dismantling policy creation system 1 (information processing system) is an information processing device that supports the formulation of a dismantling policy for each part by outputting the priority of parts to be taken out by dismantling a vehicle, for example, in an automobile recycling process.

[0013] The dismantling policy creation system 1 includes a storage device 11 such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive), a memory 12 such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a calculation device 13 consisting of a CPU (Central Processing Unit) or the like, an input device 14 such as a keyboard, a mouse, or a touch panel, an output device 15 such as a display or a printer, and a communication device 16 consisting of a NIC (Network Interface Card), a wireless communication module, a USB (Universal Serial Interface) module, a serial communication module, or the like.

[0014] The storage device 11 stores a demand quantity management table 200 for each part provided in the vehicle, a predetermined index calculation model 300 for each part, and a priority calculation program 1000.

[0015] (Demand management table) 2 is a diagram showing an example of a demand quantity management table 200. The demand quantity management table 200 is a database that stores time-series changes in the past demand quantity of each part provided in a vehicle. The demand quantity management table 200 includes a search count 201 in which the number of parts searched for is set, a request count 202, a price 203 in which the selling price of the part (for example, the average price for the relevant month) is set, a sales result count 204 in which the actual sales quantity of the part is set, a first sales forecast count 205 in which the sales quantity predicted by the index calculation model 300 based on the search count 201 is set, a first deviation 206 in which the deviation between the sales result count 204 and the first sales forecast count 203 is set, and a request count 207 in which the sales result count 207 is set. The data items include a second sales forecast number 207 in which the sales number predicted by the index calculation model 300 based on the sales forecast number 202 is set, a second deviation 208 in which the deviation between the actual sales number 204 and the second sales forecast number 207 is set, an inventory number 209 in which the inventory number is set, a first sales forecast number - inventory number 210 in which the value obtained by subtracting the inventory number 209 from the first sales forecast number 205 is set, and a second sales forecast number - inventory number 211 in which the value obtained by subtracting the inventory number 209 from the second sales forecast number 207 is set.

[0016] The number of searches for parts by users is set in the search count 201. That is, for example, the disassembly policy creation system 1 receives a search request using a keyword for identifying a part from a terminal (not shown) used by a user considering purchasing a part, and returns search results corresponding to the received search request to the terminal. The number of searches 201 is set to the number of times this search request has been received.

[0017] The number of requests for parts is set in the number of requests 202. A request is a request to purchase a part, or a tentative reservation to order a part, etc. That is, for example, the disassembly policy creation system 1 receives requests from a terminal (not shown) used by a user requesting the purchase of each part, and stores information on the received requests. The number of requests 202 is set to the number of times this request has been received.

[0018] The demand quantity management table 200 stores time-series data for each data item (in the illustrated example, values ​​for each month (January to September)). The storage device 11 also stores a demand quantity management table 200 for each part provided in the vehicle. That is, a demand quantity management table 200 exists for each part provided in the vehicle.

[0019] The index calculation model 300 predicts the value of an index related to future sales of each part by regression based on the time-series change of the past demand. The demand in this embodiment is the number of searches or the number of requests. The index related to sales in this embodiment is the sales volume. The index calculation model 300 may be a trained model that inputs the time-series change of the past demand and outputs the value of an index related to future sales, or may be an equation (such as an equation for performing regression prediction) or a database that calculates the value of an index related to future sales from the time-series change of the past demand by a predetermined calculation formula or the like. The trained model is constructed, for example, by machine learning using the past demand and actual sales numbers stored in the demand management table 200 as training data. In this case, the trained model is constructed, for example, based on the algorithms of a neural network, a decision tree, a random forest, and a support vector machine (SVM). The neural network is a neural network having an input layer that receives input data, one or more intermediate layers (hidden layers) that extract and output features from the input data, and an output layer that outputs output data, and is, for example, a CNN (Convolution Neural Network).

[0020] The priority calculation program 1000 inputs the time series change in the past demand amount of each part into the index calculation model 300, and performs a calculation process to calculate the priority of each part to be taken out when the vehicle is dismantled.

[0021] The programs of the disassembly policy creation system 1 described above are executed by the computing device 13 reading them from the memory 12 or the storage device 11. Furthermore, each program can be recorded on, for example, a portable or fixed recording medium and distributed. Next, the processing performed by the disassembly policy creation system 1 will be described.

[0022] <First priority calculation process> 3 is a process flow diagram for explaining an outline of the first priority calculation process performed in the dismantling policy creation system 1. The process shown in the figure is executed, for example, when a predetermined input is made from a user to the dismantling policy creation system 1. For example, a user (for example, a dismantling worker) makes a predetermined input to the dismantling policy creation system 1 before starting the work of dismantling a vehicle and extracting parts.

[0023] First, the priority calculation program 1000 selects one of the parts installed in the specified vehicle, inputs time series data of the past search count and actual sales count of the selected part into the index calculation model 300, thereby predicting a first sales forecast number of the part (S101), and writes the predicted first sales forecast number into the demand quantity management table 200. The specified vehicle is one or more vehicles that are candidates for dismantling (for example, vehicles owned by an automobile dismantler or the like). Information identifying the specified vehicle and information identifying each part installed in the vehicle are set and registered in advance in the dismantling policy creation system 1.

[0024] Next, the priority calculation program 1000 predicts a second sales forecast number for the part by inputting time series data on the number of past requests and actual sales numbers for the part into the index calculation model 300 (S102), and writes the predicted second sales forecast number into the demand management table 200.

[0025] Next, the priority calculation program 1000 selects the sales forecast number that matches the actual sales number highly (closest to the actual sales number) from the first sales forecast number or the second sales forecast number (S103). For example, the priority calculation program 1000 selects the sales forecast number with the smaller absolute value from the first deviation 206 or the second deviation 208 (e.g., the average value of the nearest period) in the demand amount management table 200.

[0026] Next, the priority calculation program 1000 judges whether the past sales figures of the part have a time-series characteristic (S104). For example, the priority calculation program 1000 judges whether the sales figures vary depending on the season (for example, whether the sales figures in a given month are higher or lower than those in other months). If the past sales figures do not have a time-series characteristic (S104: No), the program proceeds to the process of S106.

[0027] On the other hand, if the actual sales figures have a time-series characteristic (S104: Yes), the priority calculation program 1000 corrects the forecast sales figures by multiplying them by a coefficient based on the characteristic (S105). For example, if the month for which the sales figures were predicted is September and there is a time-series characteristic that the sales figures increase in September, the priority calculation program 1000 multiplies the forecast sales figures by a coefficient based on the increase.

[0028] Next, the priority calculation program 1000 judges whether the sales forecast numbers have been calculated for all parts installed in the specified vehicle (S106). If the sales forecast numbers have not been calculated for all parts (S106: No), the process returns to S101.

[0029] On the other hand, when the sales forecast number is calculated for all parts (S106: Yes), the priority calculation program 1000 calculates the priority of each part to be taken out by dismantling the vehicle based on the calculated sales forecast number, the current stock number, and the price (for example, the average price for the nearest period, etc.) (S107). For example, the priority calculation program 1000 assigns a higher priority to a part with a larger sales forecast number, and a lower priority to a part with a smaller sales forecast number. Furthermore, when the stock number is greater than the sales forecast number (when the value obtained by subtracting the stock number from the sales forecast number is negative), the priority calculation program 1000 determines that the part is in excess stock, and assigns a lower priority to the excess stock part. At this time, the priority calculation program 1000 may multiply the priority of each part calculated based on the sales forecast number by a coefficient based on the amount of excess stock to correct (recalculate) the priority. Furthermore, the priority calculation program 1000 assigns a higher priority to a part with a higher price, and assigns a lower priority to a part with a lower price. At this time, the priority calculation program 1000 may correct (recalculate) the priority of each part by multiplying the priority of each part calculated based on the sales forecast number and the stock number by a coefficient based on the price of each part. The priority calculation program 1000 may also calculate the priority by weighting each parameter (sales forecast number, stock number, or price).

[0030] Next, the priority calculation program 1000 outputs the calculated priority of each component by displaying a priority display screen 2000, which will be described later (S108). After that, the priority calculation program 1000 ends this first priority calculation process.

[0031] (Priority display screen) FIG. 4 is a diagram showing an example of a priority display screen 2000. The priority display screen 2000 includes an area 2010 that displays the priority of each part to be taken out by dismantling a vehicle. For example, the priority calculation program 1000 displays the dismantling priority (priority of taking out by dismantling a vehicle), part ID, part name, number of searches, number of requests, number of sales, sales amount, average price, and inventory number of each part in the area 2010 in descending order of priority. The part ID is identification information for identifying each part, and is, for example, a part number or a manufacturer part number described in a parts catalog or the like. The part name is the name of the part. The priority calculation program 1000 may calculate the priority of each part to be taken out by dismantling a vehicle as a rank (number) or may calculate it as a level such as "high", "medium", or "low". The priority calculation program 1000 may display the parts in descending order of priority, or may highlight the parts with high priority. "Highlighting" includes changing the display color, changing the font size, changing the background color, or adding a mark or the like.

[0032] The priority calculation program 1000 may display the priority display screen 2000 on the output device 15, or may cause the priority display screen 2000 to be displayed on a terminal used by an automobile dismantling company (e.g., a dismantling worker) via the communication device 16. The terminal used by the automobile dismantling company is, for example, an information processing device such as a personal computer, a tablet terminal, or a smartphone.

[0033] In the present embodiment, the index calculated by the index calculation model 300 is the sales volume, but the index is not limited to this and may be other indexes related to each part, such as the inventory turnover or the sales amount. For example, when the index calculated by the index calculation model 300 is the sales amount, the priority calculation program 1000 corrects the sales amount based on the sales record number and price in the processes of S104 and S105.

[0034] As described above, the dismantling policy creation system 1 of this embodiment stores a predetermined index calculation model 300 for each part installed in a vehicle, and inputs the time-series changes in the past demand amount of each part installed in a specified vehicle into the index calculation model 300, thereby calculating the priority of each part to be removed when the specified vehicle is dismantled.

[0035] That is, the dismantling policy creation system 1 of the present embodiment can calculate the priority according to the time-series demand of each part to be taken out by dismantling a vehicle. This can support the formulation of a dismantling policy for parts that matches the demand.

[0036] In addition, the dismantling policy creation system 1 of this embodiment stores an index calculation model 300 that predicts the future sales volume (sales number) of each part installed in a vehicle based on a time-series change in the past demand for the part, and an index calculation model 300 that predicts the future sales volume of each part by inputting the time-series change in the past demand for each part installed in a specified vehicle into the index calculation model 300, and calculates the priority of each part to be removed when the specified vehicle is dismantled based on the predicted sales volume and inventory volume of each part.

[0037] For example, parts with a greater inventory than the predicted sales volume are likely to become excess inventory. Therefore, by predicting parts that will become excess inventory based on sales and inventory volumes and lowering the priority of those parts, it is possible to support the formulation of a dismantling policy that reduces inventory and improves inventory turnover.

[0038] In addition, the dismantling policy creation system 1 of this embodiment includes an index calculation model 300 that predicts the value of an index related to future sales of each part installed in a vehicle based on time-series changes in the past demand for the part, and stores the time-series changes in sales of each part, and for parts whose sales have time-series characteristics, corrects the index value predicted by the index calculation model 300 based on the stored time-series changes in sales of the part, and calculates the priority of each part to be removed when a specified vehicle is dismantled based on the corrected index value.

[0039] For example, depending on the part, the sales volume or price may vary depending on the season, etc. Therefore, for parts whose sales have time-series characteristics, the index value related to sales can be calculated more accurately by correcting the index value based on the characteristics. This makes it possible to calculate the priority of picking up each part in accordance with the demand.

[0040] In addition, the dismantling policy creation system 1 of this embodiment stores an index calculation model 300 that predicts the value of an index related to future sales of each part installed in a vehicle based on time-series changes in the past demand for the part, and the demand is the number of requests for each part for purchase or the number of searches for each part, and the time-series changes in the demand that are closest to the actual value (actual sales number) among the values ​​predicted by the index calculation model 300 based on the number of requests (first sales forecast number) or the values ​​predicted by the index calculation model 300 based on the number of searches (second sales forecast number) are input to the index calculation model 300, thereby calculating the priority of each part to be removed when the specified vehicle is dismantled.

[0041] That is, the dismantling policy creation system 1 of this embodiment predicts the value of an index related to future sales based on the demand amount for which the value predicted by the index calculation model 300 based on the number of searches for parts by users or the number of requests made by users to purchase parts is closer to the actual value (higher agreement with the actual value), so that it can predict the value of an index related to future sales with higher accuracy. This makes it possible to calculate the priority of taking out each part that is more suited to demand.

[0042] [Second embodiment] Next, an information processing system, an information processing method, and an information processing program according to a second embodiment of the present invention will be described.

[0043] 5 is a diagram showing an example of the configuration of the dismantling policy creation system 1 in this embodiment. The storage device 11 of the dismantling policy creation system 1 in this embodiment is different from the dismantling policy creation system 1 in the first embodiment in that it further stores a parts management table 400. In this embodiment, the same components as those in the dismantling policy creation system 1 in the first embodiment are denoted by the same reference numerals, and the description thereof will be omitted.

[0044] (Parts management table) FIG. 6 is a diagram showing an example of a parts management table 400. The parts management table 400 is a database that stores information about each part of a vehicle. The parts management table 400 has data items of a parts ID 401 in which a parts ID that identifies each part is set, and detailed information 402. In the detailed information 402, information for classifying each part in more detail is set. For example, the same part may be classified in more detail based on the model number or year. In the example shown in the figure, the part ID "X1" may be further classified into "X11", "X12", or "X13".

[0045] <Second priority calculation process> 7 is a process flow diagram for explaining an outline of the second priority calculation process performed by the dismantling policy creation system 1. The process shown in the figure is executed, for example, when a predetermined input is made from a user to the dismantling policy creation system 1. For example, a user (for example, a dismantling worker) makes a predetermined input to the dismantling policy creation system 1 before starting the work of dismantling a vehicle and extracting parts.

[0046] First, the priority calculation program 1000 selects one part from among the parts installed in the specified vehicle, and calculates the ratio of the number of requests to the number of searches for the selected part (S201).

[0047] Next, the priority calculation program 1000 calculates the level of need for the part by subtracting the sales amount from the number of requests (S202). At this time, the priority calculation program 1000 may calculate the level of need by subtracting the actual sales amount from the number of past requests, or may calculate the level of need by subtracting the forecast sales amount from the current number of requests.

[0048] Next, the priority calculation program 1000 judges whether the part is requested despite being in stock (S203). Specifically, the priority calculation program 1000 judges that the part is requested despite being in stock if the value obtained by subtracting the number of requests from the number of stock of the part is equal to or greater than a predetermined threshold. If the value obtained by subtracting the number of requests from the number of stock is less than the predetermined threshold (S203: No), the priority calculation program 1000 proceeds to the process of S205.

[0049] On the other hand, if the value obtained by subtracting the number of requests from the number of stock is equal to or greater than a predetermined threshold (S203: Yes), the priority calculation program 1000 classifies the part in more detail based on the detailed information of the part, and calculates the ratio of the number of requests to the number of searches and the level of need for each classified part (S205).

[0050] Next, the priority calculation program 1000 judges whether or not the above-mentioned processes of S201 to S204 have been executed for all parts installed in the specified vehicle (S205). If the processes of S201 to S204 have not been executed for all parts (S205: No), the program returns to the process of S201.

[0051] On the other hand, when the priority calculation program 1000 has executed the processes of S201 to S204 for all parts (S205: Yes), it calculates the priority of each part to be taken out by dismantling the vehicle based on the ratio calculated in S201, the level of need calculated in S202, and the price (for example, the average value of the nearest neighboring regular intervals, etc.) (S206). For example, the priority calculation program 1000 relatively compares the ratio of the number of requests to the number of searches between each part, and as a result of the relative comparison, the priority of the part with a higher ratio is increased and the priority of the part with a lower ratio is decreased (the priority of the part with a higher ratio is increased higher than the priority of the part with a lower ratio). Furthermore, the priority calculation program 1000 increases the priority of the part with a higher need and decreases the priority of the part with a lower need (the priority of the part with a higher need is increased higher than the priority of the product with a lower need). At this time, the priority calculation program 1000 may correct (recalculate) the priority of each part calculated based on the ratio of the number of requests to the number of searches so that the priority of the product with a higher need is increased. Moreover, the priority calculation program 1000 assigns a higher priority to a higher-priced part and a lower priority to a lower-priced part. The priority calculation program 1000 may multiply the priority of each part calculated based on the ratio of the number of requests to the number of searches and the level of need by a coefficient based on the price of each part to correct (recalculate) the priority of each part. The priority calculation program 1000 may determine the priority of each part to be taken out by dismantling a vehicle based on the sales forecast number (or the predicted sales amount, the predicted inventory turnover rate, etc.) and the inventory number in addition to the ratio, the level of need, and the price. The priority calculation program 1000 may assign a weight to each parameter (ratio, level of need, sales forecast number, inventory number, or price) to determine the priority of each part to be taken out by dismantling a vehicle.

[0052] Next, the priority calculation program 1000 outputs the calculated priority of each component by displaying the priority display screen 2000 (S207). After that, the priority calculation program 1000 ends this second priority calculation process.

[0053] As described above, the disassembly policy creation system 1 of this embodiment calculates the ratio of the number of requests to the number of searches for each part, and gives a higher priority to parts with a higher calculated ratio than parts with a lower calculated ratio.

[0054] That is, the dismantling policy creation system 1 of this embodiment can give a higher priority to the parts to be taken out of the vehicle dismantled, as the parts are in high demand for the more requested parts by users to purchase them, as opposed to the number of parts searched for simply out of curiosity, etc. This can support the formulation of a dismantling policy for parts that meets demand.

[0055] Furthermore, the dismantling policy creation system 1 of this embodiment modifies the priority of each part so that the greater the value obtained by subtracting the sales amount from the demand amount, the higher the priority of the part.

[0056] That is, the dismantling policy creation system 1 of the present embodiment can give a higher priority to a part for dismantling a vehicle and taking it out, as the part with a larger value obtained by subtracting the sales amount from the demand amount is regarded as being in high demand. This can support the formulation of a dismantling policy for parts that meets the demand.

[0057] Furthermore, the disassembly policy creation system 1 of this embodiment modifies the priority of each part by multiplying the calculated priority by a coefficient based on the price of each part.

[0058] That is, the dismantling policy creation system 1 of the present embodiment can give a high priority to the removal of high-priced parts among parts in demand, thereby supporting the creation of a dismantling policy that increases sales.

[0059] In addition, the dismantling policy creation system 1 of this embodiment further classifies parts whose inventory amount is a predetermined amount or more greater than the demand amount, and calculates a priority for dismantling and removing a specified vehicle for each classified part.

[0060] For example, a part that is requested despite being in stock may be a part of a model or vintage that is not in stock. Therefore, by classifying such parts in more detail (for example, by model or vintage) and calculating the priority of each classified part, it is possible to calculate the priority of picking each part that is more in line with demand.

[0061] [Third embodiment] Next, an information processing system, an information processing method, and an information processing program according to a third embodiment of the present invention will be described.

[0062] 8 is a diagram showing an example of the configuration of a dismantling policy creation system 1 in this embodiment. The storage device 11 of the dismantling policy creation system 1 in this embodiment differs from the dismantling policy creation system 1 in the first embodiment in that it further stores a part state management table 500. In this embodiment, the same components as those in the dismantling policy creation system 1 in the first embodiment are denoted by the same reference numerals, and the description thereof will be omitted.

[0063] (Parts status management table) FIG. 9 is a diagram showing an example of the part status management table 500. The part status management table 500 is a database for managing the status of each part provided in a vehicle. The part status management table 500 has data items of a part ID 501 in which a part ID is set, a status 502, a travel distance 503, and a removal time 504. Information on damage to the part is set in the status 502. For example, information such as the depth or length of a scratch on the exterior of the part, or an image of the part (or a scratch on the part) is set in the status 502. The travel distance 503 is set to the travel distance of the vehicle to be dismantled in order to remove the part. The removal time 504 is set to the time required to dismantle the vehicle and remove the part. The removal time 504 is set to the time measured when the same part was actually removed from the vehicle in the past. The value of each data item of the part status management table 500 is set in advance by a user based on, for example, a vehicle currently to be dismantled.

[0064] <Third priority calculation process> 10 is a process flow diagram for explaining an overview of the third priority calculation process performed by the dismantling policy creation system 1. The process shown in the figure is executed, for example, when a predetermined input is made from a user to the dismantling policy creation system 1. For example, a user (for example, a dismantling worker) makes a predetermined input to the dismantling policy creation system 1 before starting the work of dismantling a vehicle and extracting parts.

[0065] The processing in S301 to S306 is similar to the processing in S101 to S106 in the first embodiment, and therefore the description thereof will be omitted.

[0066] When the priority calculation program 1000 has calculated the sales forecast numbers for all parts installed in the specified vehicle (S306: Yes), it determines the condition of each part installed in the specified vehicle (S307). For example, the priority calculation program 1000 determines the degree of damage of each part (for example, levels such as "high", "medium", "low", "no damage", etc.) based on the information set in the status 502 of the part status management table 500.

[0067] Next, the priority calculation program 1000 calculates the priority of each part to be taken out by dismantling the vehicle based on the calculated sales forecast number, current stock number, price, part condition, mileage, and removal time (S308). For example, the priority calculation program 1000 increases the priority of a part with a lower degree of damage (good condition), and decreases the priority of a part with a higher degree of damage (poor condition). The priority calculation program 1000 also increases the priority of a part with a shorter mileage, and decreases the priority of a part with a longer mileage. The priority calculation program 1000 also increases the priority of a part with a shorter removal time, and decreases the priority of a part with a longer removal time. At this time, the priority calculation program 1000 may correct (recalculate) the priority of each part by multiplying the priority of each part calculated based on the sales forecast number, stock number, and price by a coefficient related to the condition of each part, the vehicle mileage, or the removal time.

[0068] The priority calculation program 1000 may calculate the priority of removing each part based on the ratio of the number of requests to the number of searches for each part and the level of need instead of or in addition to the sales forecast number and the stock number of each part. The priority calculation program 1000 may also calculate the priority of each part by weighting each parameter (sales forecast number, stock number, price, ratio of the number of requests to the number of searches, level of need, condition, mileage, or removal time).

[0069] Next, the priority calculation program 1000 outputs the calculated priority of each component by displaying the priority display screen 2000 (S309). After that, the priority calculation program 1000 ends this third priority calculation process.

[0070] As described above, the dismantling policy creation system 1 of this embodiment further stores the time required for removing each part installed on the vehicle from the vehicle, and calculates the priority of each part to be removed when the specified vehicle is dismantled based on the stored time required for removing each part from the vehicle.

[0071] That is, the dismantling policy creation system 1 of the present embodiment can, for example, give higher priority to parts with short removal times (parts with few man-hours to dismantle). Therefore, it is possible to support the formulation of a part dismantling policy that improves the work efficiency on site.

[0072] In addition, the dismantling policy creation system 1 of this embodiment further stores information regarding the state of each part installed in the vehicle, and calculates the priority of each part to be removed when the specified vehicle is dismantled, based on the stored state of each part.

[0073] That is, the dismantling policy creation system 1 of this embodiment can, for example, give a higher priority to parts in good condition (for example, parts with no scratches on the exterior) than parts in bad condition (for example, parts with severe scratches on the exterior). This can support the creation of a dismantling policy that gives priority to parts that are more likely to be sold or parts that can be sold at a higher price.

[0074] In addition, the dismantling policy creation system 1 of this embodiment further stores the mileage of the specified vehicle, and calculates the priority of each part to be removed by dismantling the specified vehicle based on the stored mileage of the specified vehicle.

[0075] That is, the dismantling policy creation system 1 of this embodiment can, for example, give a higher priority to parts installed in vehicles with short mileage than to parts installed in vehicles with long mileage. This makes it possible to calculate the priority based on not only formal data such as the number of searches and part model numbers used in the first and second embodiments, but also data such as the deterioration state specific to each vehicle and part, and therefore can support the formulation of a dismantling policy that preferentially removes parts that are more likely to be sold or parts that can be sold at a higher price.

[0076] [Fourth embodiment] Next, an information processing system, an information processing method, and an information processing program according to a fourth embodiment of the present invention will be described.

[0077] 11 is a diagram showing an example of the configuration of a dismantling policy creation system 1 in this embodiment. The storage device 11 of the dismantling policy creation system 1 in this embodiment differs from the dismantling policy creation system 1 in the first embodiment in that it further stores a KPI management table 600. In this embodiment, the same components as those of the dismantling policy creation system 1 in the first embodiment are denoted by the same reference numerals, and the description thereof will be omitted.

[0078] (KPI management table) 12 is a diagram showing an example of a KPI management table 600. The KPI management table 600 is a database that manages KPIs (Key Performance Indicators) that are considered important for each user (for example, an automobile dismantler who dismantles vehicles). The KPIs that are considered important are, for example, indicators related to the policy of the dismantling work. The KPI management table 600 has data items of a user ID 601 that identifies each user, an important KPI 602 in which a KPI that the user considers important is set, and an important KPI-related parameter 603 in which a parameter related to the important KPI is set.

[0079] <Weighting process> 13 is a process flow diagram for explaining an outline of the weighting process performed by the dismantling policy creation system 1. The process shown in this diagram is executed, for example, when a predetermined input is made by a user to the dismantling policy creation system 1. For example, the dismantling policy creation system 1 executes the process shown in this diagram when the results of dismantling work actually performed on site (the parts taken out by dismantling a vehicle, the order in which they are taken out, etc.) are input.

[0080] First, the priority calculation program 1000 receives an input of the results of dismantling work actually performed on site, with respect to the dismantling policy based on the priority output in the priority calculation process. Then, the priority calculation program 1000 compares the dismantling policy with the results of the dismantling work (S401).

[0081] Next, the priority calculation program 1000 predicts the KPI that the user considers important based on the portion where the difference between the dismantling policy and the dismantling work result is relatively large (S402). For example, when part B is preferentially removed even though part A has a higher priority than part B in the dismantling policy, the priority calculation program 1000 predicts the KPI that the user considers important based on the differences between parts A and B or the characteristics of each parameter related to part B (e.g., inventory quantity, sales volume, price, removal time, etc.). Then, the priority calculation program 1000 writes the predicted KPI that the user considers important into the important KPI 802 of the KPI management table 600.

[0082] The priority calculation program 1000 may input the dismantling policy and the dismantling work results, and predict the KPIs that the user considers important using a trained model that outputs the KPIs that the user considers important.

[0083] Next, the priority calculation program 1000 weights the parameter related to the predicted important KPI more heavily than the other parameters, and updates the weight of each parameter (S403). For example, when the important KPI is inventory turnover, the priority calculation program 1000 weights the inventory quantity more heavily than the other parameters. When the important KPI is sales amount, the priority calculation program 1000 weights the sales quantity and price more heavily than the other parameters. When the important KPI is sales quantity, the priority calculation program 1000 weights the sales quantity more heavily than the other parameters.

[0084] Next, the priority calculation program 1000 assigns the updated weight to each parameter and executes a priority calculation process (for example, any one of the first to third priority calculation processes described above) (S404). After that, the priority calculation program 1000 ends this weighting process.

[0085] The priority calculation program 1000 is not limited to the above-mentioned flow, and may calculate the value of the important KPI of a designated user using the index calculation model 300, and calculate the priority of each part based on the calculated important KPI value. For example, the priority calculation program 1000 may calculate the inventory turnover rate using the index calculation model 300 for user "Company A", calculate the sales amount using the index calculation model 300 for user "Company B", and calculate the sales volume using the index calculation model 300 for user "Company C".

[0086] In addition, in this embodiment, the priority calculation program 1000 predicts the KPIs that each user considers important based on the dismantling policy and the dismantling work results, but this is not limited to the above, and the user may manually set and input the important KPIs into the KPI management table 600.

[0087] As described above, the dismantling policy creation system 1 of this embodiment further stores parameters (parameters related to KPIs) corresponding to each of the indicators related to the dismantling work policy, and indicators that each user considers important (important KPIs), weights the parameters corresponding to the indicators that the designated user considers important among the multiple parameters more heavily than the other parameters, and calculates the priority of each part to be removed when the designated vehicle of the designated user is dismantled based on the multiple weighted parameters.

[0088] The KPIs that each user considers important may differ depending on the user performing the dismantling work (such as an automobile dismantler). Therefore, by weighting the parameters related to the KPIs that each user considers important, it is possible to calculate the priority of removing each part that matches the KPIs that each user considers important. This makes it possible to support the formulation of dismantling policies that match the KPIs that each user considers important.

[0089] The present invention is not limited to the above-described embodiment, and can be implemented using any components without departing from the scope of the present invention. The above-described embodiments and modifications are merely examples, and the present invention is not limited to these contents as long as the features of the invention are not impaired. In addition, although various embodiments and modifications have been described above, the present invention is not limited to these contents. Other aspects conceivable within the scope of the technical idea of ​​the present invention are also included in the scope of the present invention.

[0090] For example, part of the hardware included in each device of this embodiment may be provided in another device.

[0091] Furthermore, each program of the dismantling policy creation system 1 may be provided in another device, a certain program may be made up of a plurality of programs, or a plurality of programs may be integrated into one program.

[0092] In the above-described embodiment, the dismantling policy creation system 1 calculates the priority of removing each part provided in the specified vehicle, but the present invention is not limited to this, and the dismantling priority of each vehicle may be calculated. When calculating the dismantling priority of a vehicle, the dismantling policy creation system 1 specifies each vehicle by its type, such as a classification type, a certification type, a classification type (type designation number-classification division number), or a full model number.

[0093] FIG. 14 is a diagram for explaining vehicle types. The classification type is a type that broadly classifies vehicles. The certification type is a type that classifies vehicles in more detail than the classification type. For example, the classification type can specify whether the vehicle is a two-wheel drive or a four-wheel drive. The classification type is a type that classifies vehicles in more detail than the certification type. For example, the classification type can specify the grade of the vehicle. The full model number is a type that classifies vehicles in more detail than the classification type. For example, the full model number can specify a finer grade that cannot be specified by the classification type. The part number or manufacturer part number can specify each part provided in each vehicle individually. [Explanation of symbols]

[0094] 1 Dismantling policy creation system, 11 Storage device, 12 Memory, 13 Calculation device, 14 Input device, 15 Output device, 16 Communication device, 200 Demand amount management table, 300 Index calculation model, 400 Parts management table, 500 Parts status management table, 600 KPI management table, 1000 Priority calculation program, 2000 Priority display screen

Claims

1. A storage device that stores a predetermined index calculation model for each part provided in the vehicle; a calculation device that calculates a priority of each part to be taken out by dismantling the specified vehicle by inputting a time series change in past demand amount of each part installed in the specified vehicle into the index calculation model; An information processing system comprising:

2. the storage device stores the index calculation model for predicting a future sales volume of each part installed in a vehicle based on a time-series change in a past demand volume of the part, and an inventory volume of each part of the vehicle; the computing device predicts future sales of each part by inputting a time series change in the demand amount of each part installed in the specified vehicle in the past into the index calculation model, and calculates a priority of each part to be removed by dismantling the specified vehicle based on the predicted sales amount of each part and the inventory amount of each part. The information processing system according to claim 1 .

3. the storage device stores the index calculation model for predicting a value of an index related to future sales of each part installed in a vehicle based on a time-series change in past demand for the part, and stores the time-series change in sales of each part; the calculation device corrects the index value predicted by the index calculation model for a part whose sales have time-series characteristics, based on the stored time-series change in sales of the part, and calculates a priority of each of the parts to be removed by dismantling the specified vehicle, based on the corrected index value. The information processing system according to claim 1 .

4. the storage device stores the index calculation model for predicting a value of an index related to future sales of each part provided in a vehicle based on a time-series change in past demand for the part; The demand amount may be a number of requests for each part that is requested for purchase or a number of searches for each part that is searched for, the calculation device calculates a priority of each of the parts to be taken out by dismantling the specified vehicle by inputting into the index calculation model a time series change in the demand amount that is a value predicted by the index calculation model based on the number of requests or a value that is close to an actual value among the values ​​predicted by the index calculation model based on the number of searches. The information processing system according to claim 1 .

5. The demand amount may be a number of requests for each part that is requested for purchase or a number of searches for each part that is searched for, the computing device calculates a ratio of the number of requests to the number of searches for each of the components, and gives a higher priority to a component having a higher calculated ratio than a component having a lower calculated ratio; The information processing system according to claim 1 .

6. the computing device modifies the priority of each part so that a part having a larger value obtained by subtracting sales volume from demand volume has a higher priority; 6. The information processing system according to claim 5.

7. the computing device modifies the priority of each part by multiplying the calculated priority by a coefficient based on the price of each part; The information processing system according to claim 1 .

8. the computing device further classifies the parts in detail for the parts whose inventory amount is greater than the demand amount by a predetermined amount or more, and calculates a priority for dismantling the specified vehicle and removing the parts for each of the classified parts; The information processing system according to claim 1 .

9. The storage device further stores a time required for removing each part provided on the vehicle from the vehicle, the computing device calculates a priority of each of the parts to be removed by dismantling the specified vehicle based on a time required for removing each of the stored parts from the vehicle. The information processing system according to claim 1 .

10. The storage device further stores information regarding a state of each component provided in the vehicle, the computing device calculates a priority of each of the parts to be removed by dismantling the specified vehicle based on the stored state of each of the parts. The information processing system according to claim 1 .

11. The storage device further stores a mileage of the specified vehicle; the computing device calculates a priority of each of the parts to be taken out by dismantling the specified vehicle based on the stored mileage of the specified vehicle. The information processing system according to claim 1 .

12. The storage device further stores a plurality of parameters corresponding to each index related to a policy of the dismantling work, and the index that each user considers important; the calculation device weights a parameter corresponding to the index that the designated user considers important among the plurality of parameters more heavily than other parameters, and calculates a priority of each part to be taken out by dismantling the designated vehicle of the designated user based on the weighted plurality of parameters; The information processing system according to claim 1 .

13. An information processing device, A calculation process is executed to calculate a priority of each part to be taken out by dismantling the specified vehicle by inputting a time series change in the past demand amount of each part installed in the specified vehicle into a predetermined index calculation model for each part installed in the vehicle. Information processing methods.

14. In the information processing device, A calculation process is executed to calculate the priority of each part to be taken out by dismantling the specified vehicle by inputting a time series change in the past demand amount of each part installed in the specified vehicle into a predetermined index calculation model for each part installed in the vehicle. Information processing program.

15. A storage device that stores a predetermined index calculation model for each part provided in the vehicle; a calculation device that calculates a priority of each part to be taken out by dismantling the specified vehicle by inputting a time series change in past demand amount of each part installed in the specified vehicle into the index calculation model; A dismantling policy creation system that includes:

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