Information processing device

Abstract

The goal is to optimize inventory while improving the efficiency of ordering operations. [Solution] The information processing device accepts input of receipt and payment data including inventory data on material inventory, sales performance data on material sales performance, and contract remaining quantity data on contract remaining quantity of material, obtains setting data including lead time data on material lead times, calculates safety stock amounts based on the sales performance data and lead time data, predicts the demand for materials using a statistical prediction method based on the sales performance data, determines whether to order materials based on the receipt and payment data, lead time data, safety stock amounts, and the demand predicted by the demand prediction unit, and if the order determination unit determines to order materials, calculates the order quantity of materials, generates a material ordering plan based on the order quantity, generates ordering data for ordering materials based on the ordering plan, and outputs the ordering data.

Description

[Technical field]

[0001] The embodiments disclosed in the present specification and drawings relate to an information processing device. [Background technology]

[0002] Conventionally, users who perform ordering operations perform accurate and appropriate ordering operations while predicting future demand in consideration of inventory status based on inventory data, etc., so as to avoid out-of-stocks and shortages, and to ensure sufficient inventory. However, in the material distribution industry, particularly in the steel distribution industry, users manually import various data such as inventory data and shipping data, create order slips, and determine order quantities for each of the many items handled, resulting in a huge amount of work. In addition, since it is difficult to accurately predict the demand for each of the many items handled, there is a possibility of excess inventory or shortages for some items handled. Furthermore, only the ordering personnel is familiar with know-how regarding order quantities, and when the ordering personnel is replaced, the know-how must be inherited.

[0003] In recent years, technologies have been proposed to support such ordering operations, such as calculating safety stock amounts and predicting demand amounts. However, such technologies do not correspond to the ordering workflow for the material distribution industry, so users must perform ordering operations while calculating safety stock amounts and predicting demand amounts using different services, making it difficult to perform ordering operations efficiently. Therefore, it is desirable to realize the efficiency of ordering operations while optimizing inventory by calculating safety stock amounts and predicting demand amounts. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2003-242432 A Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention has an object to provide an information processing device that can realize efficient ordering operations while optimizing inventory. [Means for solving the problem]

[0006] According to one aspect of the present invention, an information processing device includes: a receiving unit that receives input of receipt and payment data including inventory data on an inventory of a material, sales performance data on a sales performance of the material, and contract remaining quantity data on a contract remaining quantity of the material; an acquisition unit that acquires setting data including lead time data on a lead time of the material; a reference month number calculation unit that calculates a reference number of months indicating an inventory amount for a number of months that should be held based on a safety stock amount indicating a minimum inventory amount of the material, based on the sales performance data and the lead time data; a demand quantity prediction unit that predicts a demand quantity of the material using a statistical prediction method, based on the sales performance data; an order determination unit that determines whether to order the material, based on the receipt and payment data, the lead time data, the reference number of months, and the demand amount predicted by the demand quantity prediction unit; an order quantity calculation unit that calculates an order quantity of the material when the order determination unit determines to order the material; an order plan generation unit that generates an order plan for the material based on the order quantity; an order data generation unit that generates order data for the order of the material based on the order plan; and an order data output unit that outputs the order data. Effect of the Invention

[0007] According to the present invention, it is possible to optimize inventory while improving the efficiency of ordering operations. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a diagram showing a business flow of ordering materials using the information processing system according to the first embodiment. [Diagram 2] 1 is a diagram illustrating an example of a configuration of an information processing system according to a first embodiment. [Diagram 3] 1 is a diagram illustrating an example of a configuration of an information processing device according to a first embodiment. [Figure 4] FIG. 13 is a diagram showing an example of an item data screen displayed on a display of a terminal device. [Diagram 5] FIG. 13 is a diagram showing an example of an order category data screen displayed on a display of a terminal device. [Figure 6] FIG. 13 is a diagram showing an example of a receipt / payment data input screen displayed on a display of a terminal device. [Figure 7] FIG. 13 is a diagram showing an example of values ​​of safety coefficients set for each allowable frequency of stockout. [Figure 8] FIG. 1 is a diagram illustrating a method for calculating a prediction error in the statistical prediction method of No. 1. [Figure 9] FIG. 9 is a diagram for explaining an outline of the learning method shown in FIG. 8. [Figure 10] FIG. 9 is a diagram for explaining an outline of the verification method shown in FIG. 8. [Figure 11] FIG. 13 is a diagram illustrating a method for selecting one statistical prediction method based on prediction errors in each of a plurality of statistical prediction methods. [Figure 12] 11 is a flowchart of an order output process executed in the information processing device according to the first embodiment. [Figure 13] 11 is a flowchart of an order output process executed in the information processing device according to the first embodiment. [Figure 14] FIG. 13 is a diagram showing an example of a receipt and payment table screen displayed on the display of the terminal device. [Figure 15] FIG. 13 is a diagram showing an example of an ordering plan screen displayed on a display of a terminal device. [Figure 16] FIG. 13 is a diagram showing an example of an order data output screen displayed on a display of a terminal device. [Figure 17] FIG. 11 is a diagram illustrating an example of a configuration of an information processing device according to a second embodiment. [Figure 18] 13 is a flowchart of an order output process executed in an information processing device according to a second embodiment. [Figure 19]FIG. 13 is a diagram showing an example of a contract remaining amount adjustment screen displayed on a display of a terminal device. [Figure 20] FIG. 11 is a diagram illustrating an example of a configuration of an information processing device according to a third embodiment. [Figure 21] 13 is a flowchart of an order output process executed in an information processing device according to a third embodiment. [Figure 22] FIG. 13 is a diagram illustrating an example of a configuration of an information processing device according to a fourth embodiment. [Figure 23] FIG. 13 is a diagram showing an example of a reference number of months setting screen displayed on a display of a terminal device. [Figure 24] FIG. 11 is a diagram showing an example of a first demand forecast screen displayed on a display of the terminal device. [Diagram 25] FIG. 13 is a diagram showing an example of a second demand forecast screen displayed on a display of the terminal device. [Figure 26] FIG. 13 is a diagram showing an example of a past performance screen displayed on a display of the terminal device. [Figure 27] FIG. 13 is a diagram showing an example of an inventory search screen displayed on a display of a terminal device. [Figure 28] FIG. 13 is a diagram illustrating an example of a Pareto analysis screen displayed on a display of a terminal device. [Figure 29] FIG. 13 is a diagram showing an example of a retained inventory screen displayed on a display of a terminal device. [Diagram 30] FIG. 13 is a diagram showing an example of a third demand forecast screen displayed on a display of the terminal device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The present invention is not limited to the embodiment.

[0010] [First embodiment] First, an overview of the information processing system 1 according to the first embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram showing a workflow of ordering materials using the information processing system 1 according to the first embodiment. This information processing system 1 is a system for supporting a series of ordering tasks, including the ordering tasks of users, in the material distribution industry, including the steel distribution industry. For example, this information processing system 1 supports tasks when a user orders materials such as steel. In the following description, the present invention will be described using a case where the material is steel as an example, but the material in the present invention is not limited to steel and can be applied to other materials. As shown in FIG. 1, the information processing system 1 has a user company system 10 and an information processing device 30. This user company system 10 and the information processing device 30 are connected to each other so as to be able to communicate with each other via a network.

[0011] When a user who uses the user company system 10 launches an application, the information processing device 30 extracts data from the backbone system of the user company system 10 to obtain backbone system data (step S1). Next, the information processing device 30 processes the backbone system data into sales performance data and inventory data using a processing tool, and inputs the sales performance data and inventory data as receipt and payment data (step S2). Next, when the receipt and payment data is input, the information processing device 30 calculates a safety stock amount indicating a minimum inventory amount using safety stock theory based on the sales performance data and setting data including lead time data, and calculates a reference month number indicating the inventory amount for the number of months that should be held based on the calculated safety stock amount (step S3). Next, the information processing device 30 predicts the demand amount using a statistical prediction method based on the sales performance data (step S4). Next, the information processing device 30 determines whether or not to order steel based on the receipt and payment data, lead time data, reference number of months, and the demand volume predicted in step S4, calculates the order volume of steel that needs to be ordered, and generates a receipt and payment table that lists inventory volume, reference number of months, order volume, etc. (step S5). Next, the information processing device 30 generates an ordering plan based on the order volume (step S6). Next, the information processing device 30 generates ordering data based on the ordering plan and outputs the generated ordering data (step S7). Next, the information processing device 30 generates order data using an order generation tool based on the order output data output as ordering data (step S8).

[0012] Next, a detailed configuration of the information processing system 1 according to the present embodiment will be described with reference to FIG. 2. FIG. 2 is a diagram showing an example of the configuration of the information processing system 1 according to the first embodiment. As shown in FIG. 2, the information processing system 1 is configured to include a user company system 10A of a user company A, a user company system 10B of a user company B, a user company system 10C of a user company C, and an information processing device 30. The user company system 10A of the user company A, the user company system 10B of the user company B, the user company system 10C of the user company C, and the information processing device 30 are connected to each other so as to be able to communicate with each other via a network NW. In the following, when the user company system 10A of the user company A, the user company system 10B of the user company B, and the user company system 10C of the user company C are expressed without distinction, they are simply referred to as "user company system 10".

[0013] The user company system 10 is a system owned by a user company. Here, the user company is, for example, a company that purchases steel materials from steel manufacturers or steel trading companies, stores them in a warehouse, and sells them to end users or wholesalers. This type of business is also called retail sales. As shown in FIG. 2, the user company system 10 is configured to include a terminal device 11 and a core system 12.

[0014] The terminal device 11 is a terminal device owned by a user who uses the information processing device 30, and is, for example, a mobile terminal, a tablet terminal, a smartphone, a wearable terminal, a personal computer, or the like.

[0015] The core system 12 stores various information of the user companies. This core system 12 is composed of, for example, a server device. As shown in Fig. 2, the core system 12 stores core system data. Then, the core system 12 transmits the core system data to the information processing device 30 via the network NW.

[0016] 2 in this embodiment, three systems, a user company system 10A of a user company A, a user company system 10B of a user company B, and a user company system 10C of a user company C, are connected to the network NW, but the number of user company systems connected to the network NW is not limited to this. For example, one or two user company systems 10 may be connected to the network NW, or four or more user company systems 10 may be connected to the network NW.

[0017] The information processing device 30 is a device that supports the ordering operation of a user. The information processing device 30 is, for example, in a cloud form, and as the cloud-type information processing device 30, for example, the functions and processes described below are provided in the form of SaaS (Software as a Service). Note that the information processing device 30 may provide the above functions and processes in the form of cloud computing as the cloud-type information processing device 30. The information processing device 30 may also be in an on-premise form.

[0018] The network NW refers to a general information and communication network that uses electric communication technology. The network NW includes, for example, wireless / wired LANs such as hospital backbone LANs (Local Area Networks) and the Internet, as well as electric communication circuit networks, optical fiber communication networks, cable communication networks, and satellite communication networks.

[0019] 3 is a diagram showing an example of the configuration of the information processing device 30 according to the first embodiment. As shown in FIG. 3, the information processing device 30 includes a communication unit 31, a storage unit 32, and a control unit 33.

[0020] The communication unit 31 implements various information communication protocols according to the form of the network NW. The communication unit 31 realizes communication with other devices via the network NW according to the various protocols. In particular, in this embodiment, the information processing device 30 is connected to the network NW via the communication unit 31, and communication with the user company system 10 is realized.

[0021] The storage unit 32 stores various data for each user company. For example, the storage unit 32 stores setting data for each user company. This setting data includes lead time data related to the lead time of steel materials. This lead time data includes, for example, a procurement period, which is the period from procurement to arrival, and an order interval, which is the interval from the previous order to the next order. The setting data also includes, for example, item data including data such as the name, weight, unit price, minimum order quantity, and supplier for each item, and order category data including data that assigns a steel manufacturer's rolling line (hereinafter referred to as a mill) to each item.

[0022] Fig. 4 is a diagram showing an example of an item data screen displayed on the display of terminal device 11. As shown in Fig. 4, on item data screen SC1, item names, which are the names of items, are associated with unit weights indicating weight per unit quantity, purchase prices, standard suppliers, minimum order lots indicating minimum order quantity data, and the like, as item data. A user can edit the item data via an input device of terminal device 11. The display of terminal device 11 corresponds to the display unit in this embodiment.

[0023] Fig. 5 is a diagram showing an example of an order category data screen displayed on the display of the terminal device 11. As shown in Fig. 5, on the order category data screen SC2, mills are assigned to each item as order category data. A user can edit the order category data via the input device of the terminal device 11.

[0024] The control unit 33 performs various processes. For example, the control unit 33 accepts input of receipt and payment data, acquires setting data, calculates the number of reference months, predicts the amount of demand, determines whether or not an order is required, calculates the amount of order, generates an order plan, generates order data, and outputs the order data.

[0025] For this reason, as shown in FIG. 3, the control unit 33 has a reception unit 331, an acquisition unit 332, a reference month number calculation unit 333, a demand quantity prediction unit 334, an order determination unit 335, an order quantity calculation unit 336, a first display control unit 337, an order plan generation unit 338, a second display control unit 339, an order data generation unit 3310, and an order data output unit 3311.

[0026] The reception unit 331 receives input (import) of receipt and payment data including inventory data related to the inventory of materials, sales performance data related to the sales performance of materials, and contract remaining amount data related to the contract remaining amount of materials.

[0027] FIG. 6 is a diagram showing an example of a receipt and payment data input screen displayed on the display of a terminal device. As shown in FIG. 6, in the receipt and payment data input screen SC3, the receipt and payment data includes the previous month's inventory results and the current month's inventory results as inventory data for each steel item, the previous month's shipping results as sales performance data for each steel item, and the contract remaining amount data for each steel item. Also, as shown in FIG. 6, the current month's inventory results in the steel inventory data include, for each item, the inventory amount of steel at the own base where the user company system 10 exists, the inventory amount of steel at other bases different from the own base, and the inventory amount of steel at relay points between the own base and other bases. Note that the sales performance data in the receipt and payment data displayed on the receipt and payment data input screen SC3 may include the current month's shipping results, which are the shipping amount of the current month, and the shipping results from the previous month or the previous month, in addition to the previous month's shipping results, or instead of the previous month's shipping results. In the following, the previous month's shipping results and the shipping results from the previous month or the previous month are also called past shipping results. The user can check the receipt and payment data before it is input by checking the receipt and payment data input screen SC3 displayed on the display of the terminal device 11.

[0028] The acquisition unit 332 acquires various data. Specifically, the acquisition unit 332 acquires core system data. The acquisition unit 332 also acquires setting data. The setting data acquired by the acquisition unit 332 includes lead time data related to the lead time of steel materials.

[0029] The base month number calculation unit 333 calculates the base month number. The base month number indicates the amount of inventory for the number of months that should be held. To calculate the base month number, the base month number calculation unit 333 calculates the amount of safety stock that indicates the minimum inventory amount of steel products. In other words, the base month number calculation unit 333 calculates the base month number based on the amount of safety stock. The formula for calculating this amount of safety stock is expressed as shown in formula (1).

number

[0030] The safety coefficient k in this formula (1) is a value set for each allowable stockout frequency. This safety coefficient k is set for each item as setting data and stored in the storage unit 32. FIG. 7 is a diagram showing an example of the value of the safety coefficient k set for each allowable stockout frequency. In the example shown in FIG. 7, for example, when the allowable stockout frequency is 3 months / quarter, that is, when a stockout is allowed once every 3 months, the safety coefficient k is 0.43. As shown in FIG. 7 and formula (1), the safety stock amount increases as the allowable stockout frequency increases. In addition, the standard deviation σ of the demand amount is calculated based on the past shipment records in the sales record data.

[0031] The demand forecasting unit 334 forecasts the demand for steel materials using a statistical forecasting method based on the sales performance data. By using a statistical forecasting method to forecast the demand for steel materials in the demand forecasting unit 334, it is possible to forecast the demand even in cases where data accumulation takes time due to infrequent transactions, such as in the steel distribution industry where transactions are conducted only once a month, where the types of accumulated data are limited to shipment volume and inventory volume, where a large number of items are handled and demand fluctuations vary for each item, etc.

[0032] The demand forecasting unit 334 according to the present embodiment predicts the demand by selecting one forecasting method from a plurality of statistical forecasting methods for each item. The plurality of statistical forecasting methods are, for example, linear regression, logarithmic regression, exponential regression, power regression, moving average, double moving average, simple exponential smoothing, double exponential smoothing, triple exponential smoothing, Holt linear trend, seasonal smoothing method (Winter additive method), seasonal smoothing method (Winter multiplicative method), seasonal adjustment regression analysis (additive type decomposition), seasonal adjustment regression analysis (multiplicative type decomposition), seasonal adjustment power function (multiplicative type decomposition), seasonal adjustment exponential function (multiplicative type decomposition), seasonal adjustment logarithmic function (multiplicative type decomposition), Croston method, cumulative method, marketing EOL, zero-value method, naive method, year-on-year comparison, previous year, and linear approximation method. These plurality of statistical forecasting methods are stored in the storage unit 32. The demand forecasting unit 334 calculates the forecast error for each of a plurality of statistical forecasting methods based on sales performance data, and forecasts the demand for steel using the forecasting method that produces the smallest forecast error among the plurality of statistical forecasting methods.

[0033] A method for selecting a statistical prediction method will be described in detail with reference to Figs. 8 to 11. Fig. 8 is a diagram showing a method for calculating a prediction error in one statistical prediction method. Fig. 9 is a diagram for explaining an outline of the learning method shown in Fig. 8. Fig. 10 is a diagram for explaining an outline of the verification method shown in Fig. 8. Fig. 11 is a diagram for explaining a method for selecting one statistical prediction method based on prediction errors in each of a plurality of statistical prediction methods.

[0034] As shown in FIG. 8, the demand prediction unit 334 calculates a mean absolute percentage error (MAPE) for each of a plurality of statistical prediction methods as a prediction error for each of the plurality of statistical prediction methods while sliding a learning period and a validation period, using a cross-validation method for each of the plurality of statistical prediction methods based on sales performance data. For example, in the learning period of the first learning and validation shown in FIG. 8, the demand prediction unit 334 trains each model corresponding to each statistical prediction method using learning data from the learning start month to N+1 month and each statistical prediction method, as shown in FIG. 9. Also, in the validation period of the first learning and validation shown in FIG. 8, the demand prediction unit 334 calculates the MAPE for the first learning and validation using the sales performance data for the validation period and the predicted value output from the trained model, as shown in FIG. 10. Specifically, the demand prediction unit 334 calculates the MAPE using the absolute value of MAPE=(total value of values ​​for validation period-total value of predicted values)÷total value for the validation period. Then, the demand prediction unit 334 repeats the learning and verification X times.

[0035] 11, the demand prediction unit 334 calculates the average value of the MAPE in the first to Xth rounds of training and validation for each model corresponding to each statistical prediction method, and selects the statistical prediction method with the smallest MAPE. Then, the demand prediction unit 334 predicts the demand for steel using the statistical prediction method with the smallest MAPE.

[0036] The order determination unit 335 determines whether to order the steel material. Specifically, the order determination unit 335 determines whether to order the steel material based on receipt and payment data, lead time data, the number of reference months, and the demand amount predicted by the demand amount prediction unit 334.

[0037] The order quantity calculation unit 336 calculates the order quantity of steel when the order determination unit 335 determines that steel should be ordered. Specifically, in the steel distribution industry, orders are placed on a monthly basis according to commercial practice, so the order quantity calculation unit 336 calculates the order quantity based on a periodic ordering method. Here, the periodic ordering method is a method of placing orders at a predetermined timing, and is a method of determining the order quantity for each order so as to balance "(procurement period T + order interval O) × planned amount of use (required amount for a single month) + safety stock amount A = current inventory amount (inventory amount for the current month) + contract remaining amount + order amount." In this embodiment, the order quantity calculation unit 336 calculates the order quantity based on the periodic ordering method by using the base number of months and the number of holding months, which will be described in detail later, etc.

[0038] The first display control unit 337 controls the display of the terminal device 11 to display an order quantity management screen for managing the order quantity. For example, the first display control unit 337 generates a receipt and payment table, and displays a receipt and payment table screen including the receipt and payment table on the display of the terminal device 11 as the order quantity management screen.

[0039] The ordering plan generating unit 338 generates an ordering plan for steel products based on the order quantity. Here, the ordering plan refers to a plan for allocating the order quantity of each item. The second display control unit 339 controls the display of the terminal device 11 to display an ordering plan screen for managing the ordering plan generated by the ordering plan generating unit 338. The ordering plan screen corresponds to the ordering plan management screen in this embodiment.

[0040] The order data generating unit 3310 generates order data for ordering steel materials based on the order plan. The order data output unit 3311 outputs the order data.

[0041] 12 and 13 are flowcharts of an order output process executed by the information processing device 30 according to the first embodiment. In this order output process, the information processing device 30 accepts input of receipt and payment data, acquires setting data, calculates the number of reference months, predicts demand, determines whether or not an order is required, calculates the order amount, generates a receipt and payment table, generates an ordering plan, generates order data, displays a receipt and payment table, displays an ordering plan screen, displays an order data output screen, and outputs order data. For example, this order output process is a process that is executed when a user executes a dedicated application on the terminal device 11.

[0042] 12, the reception unit 331 in the control unit 33 of the information processing device 30 receives input of receipt and payment data (step S11). Specifically, the reception unit 331 receives input (import) of receipt and payment data including inventory data, sales performance data, and contract remaining amount data generated by processing core system data acquired from the core system 12 of the user company system 10 via the communication unit 31. More specifically, the reception unit 331 receives input of receipt and payment data including inventory data, sales performance data, and contract remaining amount data based on an input operation from a user via an input device of the terminal device 11.

[0043] 12, the acquisition unit 332 in the control unit 33 of the information processing device 30 acquires setting data (step S13). Specifically, the acquisition unit 332 acquires setting data including lead time data from the storage unit 32. In this embodiment, the setting data includes minimum order quantity data regarding the minimum order quantity of steel materials.

[0044] 12, the reference number of months calculation unit 333 in the control unit 33 of the information processing device 30 calculates the reference number of months (step S15). Specifically, the reference number of months calculation unit 333 calculates the reference number of months based on the sales performance data and the lead time data. More specifically, the reference number of months calculation unit 333 calculates the reference number of months based on the sales performance data and the lead time data using the following equation: Reference number of months = safety stock amount / average monthly shipping amount + procurement period T + order interval O.

[0045] A method for calculating the reference number of months will be described below. First, in step S15, the reference number of months calculation unit 333 calculates the safety stock amount using the above-mentioned formula (1). Specifically, the reference number of months calculation unit 333 calculates the standard deviation σ of the demand amount indicating the variation in the shipping amount based on the sales performance data, and calculates the safety stock amount A using the above-mentioned formula (1) based on the safety coefficient k for each item included in the setting data, the supply period T and the order interval O in the lead time data included in the setting data, and the standard deviation σ of the demand amount indicating the variation in the calculated shipping amount.

[0046] Next, in step S15, the reference number of months calculation unit 333 calculates the monthly average shipping volume based on the sales performance data. Specifically, the reference number of months calculation unit 333 calculates the monthly average shipping volume by calculating the average of past shipping volumes in the sales performance data. The period of past shipping volumes in the sales performance data used to calculate the average of the past shipping volumes is the same as the period of past shipping volumes in the sales performance data used to calculate the standard deviation σ of the demand volume in the above-mentioned formula (1). For example, if the past shipping volume data in the sales performance data used to calculate the standard deviation σ of the demand volume is shipping volume data for the past 60 months, the past shipping volume data in the sales performance data used to calculate the average of the past shipping volumes is also shipping volume data for the past 60 months.

[0047] Then, in step S15, the reference month number calculation unit 333 calculates the reference month number based on the calculated safety stock amount, the calculated monthly average shipping amount, and the lead time data including the procurement period and the order interval, using Reference Month Number=Safety Stock Amount÷Monthly Average Shipping Amount+Procurement Period T+Order Interval O.

[0048] Next, as shown in Fig. 12, the demand prediction unit 334 in the control unit 33 of the information processing device 30 predicts the demand (step S17). Specifically, the demand prediction unit 334 predicts the demand using a statistical prediction method based on the sales performance data. More specifically, the demand prediction unit 334 selects one statistical prediction method from a plurality of statistical prediction methods based on the sales performance data, and predicts the demand using the selected one statistical prediction method based on the sales performance data. The demand prediction unit 334 derives a predicted value of the shipping volume up to the lead time by predicting the demand, for example.

[0049] 12, the order determination unit 335 determines whether or not an order is required (step S19). Specifically, the order determination unit 335 determines whether or not to order steel materials based on receipt and payment data, lead time data, the reference number of months, and the demand amount predicted by the demand amount prediction unit 334. More specifically, the order determination unit 335 calculates the shortage amount using Shortage amount=(Reference number of months-Number of holding months)×Monthly requirement amount, and determines whether or not to order steel materials by determining whether the shortage amount is greater than 0.

[0050] A method for determining whether to order steel materials will be described in detail below. First, in step S19, the order determination unit 335 calculates the monthly requirement. Specifically, the order determination unit 335 calculates the monthly requirement based on the lead time data and the predicted value of the shipping volume up to the lead time, using the formula: monthly requirement = predicted value of shipping volume up to the lead time ÷ (procurement period T + order interval O).

[0051] Next, in step S19, the order determination unit 335 calculates the current month's inventory amount. Specifically, the order determination unit 335 calculates the current month's inventory amount based on the inventory data, sales performance data, contract remaining amount data, and lead time data in the receipt and payment data, using the following equation: Current month's inventory amount = Previous month's inventory amount - Shipment amount (Current month's shipment amount) + Arrival amount (Current month's arrival amount).

[0052] Next, in step S19, the order determination unit 335 calculates the number of holding months. Here, the number of holding months is the amount of inventory currently held for the number of months. Specifically, the order determination unit 335 calculates the number of holding months using the number of holding months = (current month inventory amount + contract remaining amount) ÷ single month requirement based on the calculated single month requirement amount, the calculated current month inventory amount, and the contract remaining amount data in the receipt and payment data.

[0053] Next, in step S19, the order determination unit 335 calculates the shortage amount. Specifically, the order determination unit 335 calculates the shortage amount based on the reference number of months calculated in step S15, the holding number of months calculated in this step S19, and the single-month requirement amount, using Shortage Amount = (Reference Number of Months - Holding Number of Months) x Single-Month Requirement Amount.

[0054] Then, in step S19, the order determination unit 335 determines whether or not to order the steel material by determining whether the calculated shortage amount is greater than 0, that is, whether or not shortage amount>0 is satisfied.

[0055] Then, in step S19, if it is determined that an order is necessary, that is, that the steel material is to be ordered (step S19: Yes), the order quantity calculation unit 336 in the control unit 33 of the information processing device 30 calculates the order quantity (step S21). Specifically, the order quantity calculation unit 336 calculates the order quantity so that it exceeds the minimum order quantity of the steel material included in the setting data. More specifically, for example, the order quantity calculation unit 336 compares the minimum order quantity of the steel material included in the setting data with the shortage quantity, and calculates the order quantity so that the shortage quantity exceeds the minimum order quantity. Note that in step S19, if the shortage quantity exceeds the minimum order quantity, the order quantity calculation unit 336 may calculate the shortage quantity calculated in step S19 as the order quantity.

[0056] On the other hand, in step S19, if it is determined that ordering is not necessary, i.e., that steel will not be ordered (step S19: No), or after the processing of step S27, the first display control unit 337 in the control unit 33 of the information processing device 30 generates a receipt and payment table (step S23).

[0057] 13, the ordering plan generating unit 338 in the control unit 33 of the information processing device 30 generates an ordering plan (step S25). Specifically, the ordering plan generating unit 338 generates the ordering plan based on the order amount calculated in step S21.

[0058] 13, the order data generating unit 3310 in the control unit 33 of the information processing device 30 generates order data (step S27). Specifically, the order data generating unit 3310 generates the order data based on the order plan generated in step S25.

[0059] 13, the first display control unit 337 in the control unit 33 of the information processing device 30 determines whether or not to display the receipt and payment table (step S29). Specifically, the first display control unit 337 determines whether or not to display the receipt and payment table by determining whether or not an input operation for displaying the receipt and payment table has been accepted from the user via the input device of the terminal device 11. Here, the input operation for displaying the receipt and payment table screen including the receipt and payment table is, for example, an input operation for selecting this receipt and payment table screen in a pull-down menu including the names of each screen.

[0060] Then, if it is determined in step S29 that the receipt and payment table is to be displayed (step S29: Yes), the first display control unit 337 displays the receipt and payment table (step S31).

[0061] FIG. 14 is a diagram showing an example of a receipt and payment table screen displayed on the display of the terminal device 11. As shown in FIG. 14, the receipt and payment table in the receipt and payment table screen SC4 includes, for each item, item data, the inventory amount of steel at the own base, the inventory amount of steel at the other base, the inventory amount of steel at the relay point, the recommended quantity indicating the order amount calculated by the order amount calculation unit 336, the single-month required quantity, the number of holding months, the reference number of months, and the like. In addition, the receipt and payment table is provided with an item for the number of adjustment staff so that the order amount can be adjusted, and the first display control unit 337 adjusts the order amount by receiving an input operation for adjusting the order amount from the user via the input device of the terminal device 11, that is, an adjustment amount of the order amount for the item for the number of adjustment staff. Then, when the order amount is adjusted via this receipt and payment table screen SC4, the ordering plan generation unit 338 regenerates an ordering plan based on the order amount adjusted via this receipt and payment table screen SC4. Furthermore, when the ordering plan is regenerated, the ordering data generating unit regenerates the ordering data based on the regenerated ordering plan.

[0062] On the other hand, in step S29, if it is determined that the receipt and payment table is not to be displayed (step S29: No), or after the processing of step S31, the second display control unit 339 in the control unit 33 of the information processing device 30 determines whether or not to display the order plan screen (step S33). Specifically, the second display control unit 339 determines whether or not to display the order plan screen by determining whether or not an input operation for displaying the order plan screen has been accepted from the user via the input device of the terminal device 11. Here, the input operation for displaying the order plan screen is, for example, an input operation for selecting this order plan screen from a pull-down menu including the names of each screen.

[0063] Then, in step S33, if it is determined that the ordering plan screen is to be displayed (step S33: Yes), the second display control unit 339 in the control unit 33 of the information processing device 30 displays the ordering plan screen (step S35). FIG. 15 is a diagram showing an example of the ordering plan screen displayed on the display of the terminal device 11. The second display control unit 339 displays the standard supplier, the order amount, and the number of orderers for each item in the ordering plan in the ordering plan screen SC5 shown in FIG. 15. In addition, the ordering plan screen SC5 includes information IF1 on the order amount for each mill. Specifically, the information IF1 on the order amount for each mill includes the possible ordering amount, the already ordered amount, the current ordering amount, and the excess amount for each mill. The second display control unit 339 controls the display of the ordering plan screen SC5 so that the color of the excess amount column changes as an alert when the sum of the already ordered amount and the current ordering amount exceeds the possible ordering amount. In addition, on the order planning screen SC5, the second display control unit 339 controls the display of the terminal device 11 so that only items to which the mills that are the order timing are assigned can be sorted based on the user's input operation for sorting, such as inputting a check in the checkbox of the mill that is the order timing. This is because, for example, at a certain manufacturer A, items with a large outer diameter are handled by mill 1, and the order timing for items corresponding to mill 1 is the beginning of each month, while items with a small outer diameter are handled by mill 2, and the order timing for items corresponding to mill 2 is the end of each month. Since the user's order timing differs for each mill, the period when the work of calculating the order quantity for each item is performed is divided into, for example, the beginning, middle, and end of the month, so that only items corresponding to mills with an order timing in the beginning of the month, items corresponding to mills with an order timing in the middle of the month, and items corresponding to mills with an order timing in the end of the month can be sorted. In addition, the ordering plan screen SC5 has a field for the number of ordering personnel so that the ordering plan can be adjusted, and the ordering plan is adjusted by accepting input operations for adjusting the ordering plan from the user via the input device of the terminal device 11 into this field for the number of ordering personnel.Then, when the ordering plan is adjusted via this ordering plan screen SC5, the ordering data generating unit 3310 generates the ordering data again based on the ordering plan adjusted via the ordering plan screen SC5.

[0064] On the other hand, in step S33, if it is determined that the order plan screen SC5 is not to be displayed (step S33: No), or after the processing of step S35, the second display control unit 339 in the control unit 33 of the information processing device 30 determines whether or not to display the order data output screen (step S37). Specifically, the second display control unit 339 determines whether or not to display the order data output screen by determining whether or not an input operation for displaying the order data output screen has been accepted from the user via the input device of the terminal device 11. Here, the input operation for displaying the order data output screen is, for example, an input operation for selecting this order data output screen in a pull-down menu including each screen name.

[0065] Then, in step S37, if it is determined that the order data output screen is to be displayed (step S37: Yes), the second display control unit 339 in the control unit 33 of the information processing device 30 displays the order data output screen (step S39). Fig. 16 is a diagram showing an example of the order data output screen displayed on the display of the terminal device 11. The second display control unit 339 displays the supplier, purchase order, quantity, weight, unit price, etc. for each item in the order data in the order data output screen SC6 shown in Fig. 16. In addition, an order details output button is displayed on the order data output screen SC6.

[0066] 13, the second display control unit 339 in the control unit 33 of the information processing device 30 determines whether or not to output the order data (step S41). Specifically, the second display control unit 339 determines whether or not to output the order data by determining whether or not the order details output button B1 displayed on the order data output screen SC6 has been pressed. Then, if it is determined in step S41 that the order data is not to be output (step S41: No), or if it is determined in step S37 that the order data output screen is not to be displayed (step S37: No), the process returns to the above-mentioned step S29 and repeats the process from step S29.

[0067] On the other hand, if it is determined in step S41 that the order data is to be output (step S41: Yes), the order data output unit 3311 in the control unit 33 of the information processing device 30 outputs the order data (step S43). By executing this step S43, the order output process is terminated. After this order data is output, the order data is converted into order data by the order generation tool as order output data.

[0068] As described above, the information processing device 30 of this embodiment accepts input of receipt and payment data, acquires setting data, calculates the reference number of months, predicts demand, determines whether or not to order steel, calculates the order quantity if it is determined to order, generates an ordering plan based on the order quantity, generates ordering data based on the ordering plan, and outputs the generated ordering data, thereby making it possible to optimize inventory while achieving efficient ordering operations.

[0069] Second Embodiment In the information processing device 30 in the information processing system 1 according to the first embodiment described above, it is also possible to adjust the contract remaining amount in the contract remaining amount data included in the receipt and payment data. In the second embodiment, an information processing device 30 capable of adjusting the contract remaining amount will be described. Note that the configuration of the information processing system according to the second embodiment is the same as that of the information processing system 1 according to the first embodiment described above, and therefore a description thereof will be omitted.

[0070] Fig. 17 is a diagram showing an example of the configuration of the information processing device 30 according to the second embodiment, and corresponds to Fig. 3 described above. As shown in Fig. 17, the control unit 33 is configured by adding a contract remaining amount adjustment unit 3312 to the control unit 33 according to the first embodiment. The configuration other than the contract remaining amount adjustment unit 3312 is the same as that in Fig. 3, and therefore description thereof will be omitted.

[0071] The contract remaining amount adjustment unit 3312 receives an input operation from the user regarding adjustment of the contract remaining amount in the contract remaining amount data included in the receipt and payment data, and adjusts the contract remaining amount in accordance with the received input operation.

[0072] FIG. 18 is a flowchart of an order output process executed in the information processing device 30 according to the second embodiment, and corresponds to FIG. 12. In this order output process, the information processing device 30 accepts input of receipt and payment data, generates a contract remaining amount adjustment screen, acquires setting data, calculates the number of reference months, predicts demand, determines whether or not an order is required, and calculates the order amount. For example, this order output process is a process that is executed when the user executes a dedicated application on the terminal device 11. Note that the process of step S11 shown in FIG. 18 is the same as that in FIG. 12, and therefore will not be described.

[0073] 18, the contract remaining amount adjusting unit 3312 in the control unit 33 of the information processing device 30 determines whether to adjust the contract remaining amount (step S51). Specifically, the contract remaining amount adjusting unit 3312 determines whether to adjust the contract remaining amount by determining whether an input operation related to the generation of a contract remaining amount adjustment screen has been received from the user via the input device of the terminal device 11. Here, the input operation related to the generation of the contract remaining amount adjustment screen is, for example, an input operation of selecting this contract remaining amount adjustment screen from a pull-down menu including the names of each screen.

[0074] Then, in step S51, if it is determined that the contract remaining amount is to be adjusted (step S53: Yes), the contract remaining amount adjusting unit 3312 in the control unit 33 of the information processing device 30 generates a contract remaining amount adjustment screen (step S53). Specifically, the contract remaining amount adjusting unit 3312 generates the contract remaining amount adjustment screen based on the contract remaining amount data.

[0075] 18, the contract remaining amount adjusting unit 3312 in the control unit 33 of the information processing device 30 displays a contract remaining amount adjustment screen (step S55). Specifically, the contract remaining amount adjusting unit 3312 controls the display of the terminal device 11 so as to display the contract remaining amount adjustment screen generated in step S53.

[0076] FIG. 19 is a diagram showing an example of a contract remaining amount adjustment screen displayed on the display of the terminal device 11. As shown in FIG. 19, the contract remaining amount adjustment screen SC7 is displayed on the display of the terminal device 11. The contract remaining amount adjustment screen SC7 displays the order number, the contract remaining amount, the planned purchase date, and the adjusted contract remaining amount for each item. In a state in which the contract remaining amount adjustment screen SC7 is displayed, the contract remaining amount adjustment unit 3312 accepts an input operation from the user regarding the adjustment of the contract remaining amount in the contract remaining amount data via the input device of the terminal device 11, and adjusts the contract remaining amount according to the accepted input operation. In the example shown in FIG. 19, the contract remaining amount adjustment unit 3312 accepts an input operation of inputting a check in the completion flag set for each steel item as an input operation from the user regarding the adjustment of the contract remaining amount, and sets the contract remaining amount of the material for which a check is entered in the completion flag set for each steel item to 0, that is, the contract is completed.

[0077] On the other hand, in step S51, if the contract remaining amount is not adjusted (step S51: No) or after the processing of step S55, the acquisition unit 332 in the control unit 33 of the information processing device 30 acquires the setting data (step S13). The processing from step S13 onwards is the same as in Fig. 12 and Fig. 13, and therefore the description will be omitted. Then, by executing step S43, the order output processing according to this embodiment is terminated.

[0078] As described above, in the information processing device 30 in the information processing system 1 of the second embodiment, when adjusting the contract remaining quantity, a contract remaining quantity adjustment screen is displayed, and the contract remaining quantity adjustment unit 3312 accepts input operations from the user regarding the adjustment of the contract remaining quantity in the contract remaining quantity data, and adjusts the contract remaining quantity according to the accepted input operations. Therefore, in cases where the inventory quantity does not necessarily match the order quantity due to business practices in material distribution industries such as the steel distribution industry, particularly when the inventory quantity is small compared to the order quantity, it is possible to adjust the contract remaining quantity, thereby preventing the contract remaining quantity from becoming noise in the calculation of the order quantity and the generation of the ordering plan, and thereby achieving the efficiency of ordering operations while optimizing inventory.

[0079] Third Embodiment In the information processing device 30 according to the first and second embodiments described above, it is possible to predict demand when the demand for steel is intermittent. Below, a case where this modified example is applied to the first embodiment will be referred to as a third embodiment, and differences from the first embodiment described above will be described. Note that although a case where this modified example is applied to the first embodiment will be described, this modified example can also be applied to the second embodiment described above. Note that the configuration of the information processing system according to the third embodiment is the same as that of the information processing system 1 according to the first embodiment described above, and therefore description thereof will be omitted.

[0080] Fig. 20 is a diagram showing an example of the configuration of an information processing device 30 according to the third embodiment, and corresponds to Fig. 3 described above. As shown in Fig. 20, the control unit 33 is configured by adding an intermittent determination unit 3313 to the control unit 33 according to the first embodiment. In addition, in the information processing device 30 in the information processing system 1 according to this embodiment, the demand prediction unit of the control unit 33 is different from that in the first embodiment described above, and is therefore represented as a demand prediction unit 334a. The configuration other than the demand prediction unit 334a and the intermittent determination unit 3313 is the same as that in Fig. 3, and therefore description thereof will be omitted.

[0081] The intermittent determination unit 3313 determines whether the demand for steel materials is intermittent based on the sales performance data. Here, the demand is intermittent when the shipping performance, which is the shipping amount of the sales performance data, is 0 kg for N consecutive months. This N can be set arbitrarily by the user.

[0082] When it is determined that the demand for steel is intermittent, the demand forecasting unit 334a according to this embodiment forecasts the demand for steel using the moving average method as a statistical forecasting method. When it is determined that the demand for steel is not intermittent, the demand forecasting unit 334a forecasts the demand for steel using the statistical forecasting method that has the smallest forecast error among the forecast errors in each of a plurality of statistical forecasting methods.

[0083] FIG. 21 is a flowchart of an order output process executed in the information processing device 30 according to the third embodiment, and corresponds to FIG. 12. In this order output process, the information processing device 30 accepts input of receipt and payment data, acquires setting data, calculates the number of reference months, determines whether demand is intermittent, predicts the demand amount, determines whether an order is required, and calculates the order amount. For example, this order output process is a process executed when the user executes a dedicated application on the terminal device 11. Note that the processes from step S11 to step S15 shown in FIG. 21 are the same as those in FIG. 12, and therefore will not be described.

[0084] 21, the intermittent determination unit 3313 in the control unit 33 of the information processing device 30 determines whether the demand is intermittent or not (step S61). Specifically, the intermittent determination unit 3313 determines whether the demand for steel materials is intermittent or not based on sales performance data.

[0085] Then, in step S61, if it is determined that the demand is intermittent (step S61: Yes), the demand prediction unit 334a in the control unit 33 of the information processing device 30 predicts the demand using the moving average method (step S63). Specifically, the demand prediction unit 334a predicts the demand using the moving average method based on the sales performance data. Here, the moving average method is a method in which the average value of the shipment amount (demand amount) for the most recent N months is used as the predicted value.

[0086] On the other hand, if it is determined in step S61 that the demand is not intermittent (step S61: No), the demand amount prediction unit 334 in the control unit 33 of the information processing device 30 predicts the demand amount using the statistical prediction method of 1 (step S17). The process from step S17 onwards is the same as in Fig. 12 and Fig. 13, and therefore the description will be omitted. Then, by executing step S45, the order output process according to this embodiment is terminated.

[0087] As described above, in the information processing device 30 of this embodiment, it is determined whether or not demand is intermittent, and if it is determined that the demand is intermittent, the demand amount is predicted using the moving average method. Therefore, even when the demand is intermittent, the demand amount can be predicted. Therefore, even when the demand is intermittent, it is possible to optimize inventory and achieve efficient ordering operations.

[0088] [Fourth embodiment] In the information processing device 30 according to the first to third embodiments described above, the reference number of months used for order determination and order amount calculation is a value calculated by the reference number of months calculation unit 333, but this is not limited thereto. In the fourth embodiment, the information processing device 30 may accept a selection from the user between the reference number of months input by the user and the reference number of months calculated by the reference number of months calculation unit 333, and set the selected reference number of months as the reference number of months used for calculating the order amount. The fourth embodiment is a case where this modification is applied to the first embodiment described above, and the differences from the first embodiment described above will be described. Note that the configuration of the information processing system according to the fourth embodiment is the same as that of the information processing system 1 according to the first embodiment described above, and therefore the description will be omitted.

[0089] Fig. 22 is a diagram showing an example of the configuration of an information processing device 30 according to a fourth embodiment, and corresponds to Fig. 3 described above. As shown in Fig. 22, the control unit 33 is configured by adding a reference number of months setting unit 3314 to the control unit 33 according to the first embodiment. The configuration other than this reference number of months setting unit 3314 is the same as that in Fig. 3, and therefore description thereof will be omitted.

[0090] The reference number of months setting unit 3314 accepts a selection from the user between the reference number of months input by the user and the reference number of months calculated by the reference number of months calculation unit 333, and sets the selected reference number of months as the reference number of months to be used for calculating the order amount. When the reference number of months to be used for calculating the order amount is set by this reference number of months setting unit 3314, the order determination unit 335 uses the set reference number of months to again determine whether or not to place an order, and the order amount calculation unit 336 recalculates the order amount using the set reference number of months.

[0091] Fig. 23 is a diagram showing an example of a reference number of months setting screen SC8 displayed on the display of the terminal device 11. As shown in Fig. 23, the reference number of months can be input for each item, and a selection between the inputted reference number of months and the calculated reference number of months can be accepted for each material from the user, and the selected reference number of months can be set as the reference number of months used to calculate the order amount.

[0092] As described above, in the information processing device 30 in the information processing system 1 according to the fourth embodiment, a selection is accepted from the user between the base number of months input by the user and the base number of months calculated by the base number of months calculation unit 333, and the selected base number of months is set as the base number of months to be used for calculating the order quantity. Since the value of the base number of months can be adjusted, it is possible to optimize inventory while improving the efficiency of ordering operations.

[0093] [Other Modifications] In the information processing device 30 according to the first to fourth embodiments described above, the demand forecasting unit 334, 334a may receive a selection from the user between the moving average method and a statistical forecasting method that has the smallest forecast error among the forecast errors in each of a plurality of statistical forecasting methods, and forecast the demand using the selected statistical forecasting method. FIG. 24 is a diagram showing an example of a first demand forecasting screen displayed on the display of the terminal device 11. As shown in FIG. 24, the first demand forecasting screen SC9 displays, for each item, a check box for selecting the moving average method and a check box for selecting the statistical forecasting method that has the smallest forecast error as a system recommendation. This allows the user to select, for each item, either the moving average method or the statistical forecasting method that has the smallest forecast error via the input device of the terminal device 11.

[0094] In addition, in the information processing device 30 according to the first to fourth embodiments described above, it is also possible to allow the user to check the monthly requirement for steel items for which the moving average method is used as the statistical forecasting method. FIG. 25 is a diagram showing an example of a second demand forecast screen displayed on the display of the terminal device 11. As shown in FIG. 25, the second demand forecast screen SC10 displays the monthly requirement for each steel item for which the moving average method is used as the statistical forecasting method. This allows the user to easily check the monthly requirement for steel items for which the demand is predicted using the moving average method, which is likely to be used as the statistical forecasting method.

[0095] In addition, in the information processing device 30 according to the first to fourth embodiments described above, it is also possible to check the past shipment and inventory amounts for each item. Fig. 26 is a diagram showing an example of a past performance screen displayed on the display of the terminal device 11. As shown in Fig. 26, the past performance screen SC11 displays the past shipment and inventory amounts of the selected steel product based on the inventory data and sales performance data in the receipt and payment data received by the reception unit 331. By displaying this past performance screen, the user can easily refer to the past shipment and inventory amounts for each item.

[0096] In addition, in the information processing device 30 according to the first to fourth embodiments described above, the user may be allowed to search for the stock amount. FIG. 27 is a diagram showing an example of a stock search screen displayed on the display of the terminal device 11. As shown in FIG. 27, the stock search screen SC12 displays an input box for inputting specifications, dimensions, etc., a search button, and the current stock of items that match the contents input in the input box. By making it possible to search for the stock amount in this way, the user can save the effort of searching for the stock amount of a specific steel item and can easily confirm the stock amount of a specific steel item.

[0097] Moreover, in the information processing device 30 according to the first to fourth embodiments described above, a Pareto analysis may be displayed. Fig. 28 is a diagram showing an example of a Pareto analysis screen displayed on the display of the terminal device 11. As shown in Fig. 28, a Pareto chart, which is the result of the Pareto analysis, is displayed on the Pareto analysis screen SC13, and the customers with the largest shipping weights and their shipping weights are arranged in order from the left in the Pareto chart, with the shipping weight cumulative ratios being superimposed. In this way, the user can refer to the results of this Pareto analysis.

[0098] In addition, in the information processing device 30 according to the first to fourth embodiments described above, the user may be allowed to check the slow-moving stock. FIG. 29 is a diagram showing an example of a slow-moving stock screen displayed on the display of the terminal device 11. As shown in FIG. 29, the slow-moving stock screen SC14 displays the stock amount and the stocking date for each item. For example, when there is an item for which the difference between the date when this screen is displayed and the reference number of months is later than the stocking date, the first display control unit 337 may change the color of the stocking date of the corresponding item on the slow-moving stock screen SC14. The user can easily manage the slow-moving stock by checking this slow-moving stock screen SC14.

[0099] Furthermore, in the information processing device 30 according to the first to fourth embodiments described above, the user may be allowed to check the actual value of the single-month shipping volume and the predicted value of the demand volume for each item. FIG. 30 is a diagram showing an example of a third demand forecast screen displayed on the display of the terminal device 11. As shown in FIG. 30, the third demand forecast screen SC15 displays the actual value of the single-month shipping volume and the predicted value of the demand volume for each item. In this way, the user can refer to the actual value of the single-month shipping volume and the predicted value of the demand volume for each item.

[0100] Furthermore, in the information processing devices according to the first to fourth embodiments described above, as an input operation for displaying each screen, a button for transitioning to another screen may be displayed on each screen, and each screen may be displayed by pressing the button to transition to the other screen.

[0101] Finally, although various embodiments of the present invention have been described, these are presented as examples and are not intended to limit the scope of the invention. The new embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. The embodiments and their modifications are within the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0102] 1...information processing system, 10...user company system, 11...terminal device, 12...core system, 30...information processing device, 31...communication unit, 32...storage unit, 33...control unit, 331...reception unit, 332...acquisition unit, 333...reference number of months calculation unit, 334, 334a...demand amount forecasting unit, 334a...demand amount forecasting unit, 335...order determination unit, 336...order amount calculation unit, 337...first display control unit, 338...order plan generation unit, 339...second display control unit, 3310...order data generation unit, 3311...order data output unit, 3312...contract remaining amount adjustment unit, 3313...intermittent determination unit, 3314...reference number of months setting unit

Claims

1. A receiving unit that receives input of receipt and payment data including inventory data on steel inventory, sales performance data on sales performance of the steel, and contract remaining amount data on the contract remaining amount of the stocked amount of the steel against the order amount, An acquisition unit that acquires setting data including lead time data related to the lead time of the steel material; a reference months calculation unit that calculates a reference months number indicating an inventory amount for a number of months that should be held based on a safety stock amount indicating a minimum inventory amount of the steel material, based on the sales performance data and the lead time data; a demand forecasting unit that forecasts the demand for the steel material using a statistical forecasting method based on the sales performance data; an order determination unit that determines whether or not to order the steel material based on the receipt and payment data, the lead time data, the reference number of months, and the demand amount predicted by the demand amount prediction unit; an order quantity calculation unit that calculates an order quantity of the steel material when the order determination unit determines to order the steel material; an ordering plan generating unit that generates an ordering plan for the steel material based on the order amount; an order data generation unit that generates order data regarding the ordering of the steel material based on the order plan; an order data output unit that outputs the order data; a contract remaining quantity adjustment unit that receives an input operation from a user regarding adjustment of the contract remaining quantity in the contract remaining quantity data, in which the received quantity is less than the order quantity and the contract has been completed, and adjusts the contract remaining quantity in which the received quantity is less than the order quantity and the contract has been completed in accordance with the received input operation; An information processing device comprising:

2. The information processing device according to claim 1 , wherein the order amount calculation unit calculates the order amount based on a periodic ordering method.

3. A storage unit that stores a plurality of the statistical prediction methods, The demand prediction unit is determining a prediction error for each of the plurality of statistical prediction methods based on the sales performance data; predicting the demand for the steel material using a statistical forecasting method that produces a minimum prediction error among the prediction errors produced by each of the plurality of statistical forecasting methods; The information processing device according to claim 1 .

4. 4. The information processing device according to claim 3, wherein the demand forecasting unit calculates a mean absolute percentage error as a prediction error for each of the plurality of statistical forecasting methods by using a cross-validation method for each of the plurality of statistical forecasting methods based on the sales performance data, and forecasts the demand for the steel material by using the statistical forecasting method that minimizes the mean absolute percentage error.

5. An intermittent determination unit that determines whether or not the demand for the steel material is intermittent based on the sales performance data, The information processing device according to claim 1 , wherein the demand forecasting unit forecasts the demand for the steel material using a moving average method as the statistical forecasting method when it is determined that the demand for the steel material is intermittent.

6. The information processing device according to claim 1 , further comprising a first display control unit that controls the display unit to display an order quantity management screen for managing the order quantity.

7. 7. The information processing device according to claim 6, wherein when the order quantity is adjusted via the order quantity management screen, the ordering plan generation unit regenerates the ordering plan based on the order quantity adjusted via the order quantity management screen.

8. The inventory data includes an inventory amount of the steel material at a home base, an inventory amount of the steel material at another base different from the home base, and an inventory amount of the steel material at a relay point between the home base and the another base, The information processing device according to claim 6 , wherein the order quantity management screen includes an inventory amount of the steel material at the home base, an inventory amount of the steel material at the other base, and an inventory amount of the steel material at the relay point.

9. The information processing device according to claim 1 , further comprising a second display control unit that controls the display unit to display an ordering plan management screen for managing the ordering plan generated by the ordering plan generating unit.

10. 10. The information processing device according to claim 9, wherein, when the ordering plan is adjusted via the ordering plan management screen, the ordering data generation unit regenerates the ordering data based on the ordering plan adjusted via the ordering plan management screen.

11. The setting data includes minimum order quantity data regarding a minimum order quantity of the steel material, The information processing device according to claim 1 , wherein the order quantity calculation unit calculates the order quantity so as to exceed a minimum order quantity of the steel material.

12. 2. The information processing device according to claim 1, further comprising a reference number of months setting unit that accepts a selection from a user between a reference number of months input by the user and a reference number of months calculated by the reference number of months calculation unit, and sets the selected reference number of months as the reference number of months to be used in calculating the order quantity.

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