Information processing apparatus

Abstract

To provide an information processor for improving the efficiency of an ordering task while optimizing stock.SOLUTION: In the information processing system 1, the information processing device receives an input of receipt and payment data including inventory data related to an inventory of a material, sales achievement data related to a sales achievement of the material, and contract remaining quantity data related to a contract remaining quantity of the material, acquires setting data including lead time data related to a lead time of the material, calculates a safety inventory quantity based on the sales achievement data and the lead time data, and predicts a demand quantity of the material based on the sales achievement data using a statistical prediction method. Whether or not to place an order for a material is determined on the basis of reception / payment data, lead time data, a safety stock quantity, and a demand quantity predicted by a demand quantity prediction part, and when it is determined to place the order for the material, an order quantity of the material is calculated, an order plan of the material is generated on the basis of the order quantity, order data related to the order of the material is generated on the basis of the order plan, and the order data is output.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] In the past, users who performed ordering tasks had to estimate future demand based on inventory data, etc. We will forecast and ensure that there are no shortages or out-of-stock situations and that sufficient stock is maintained. However, in the materials distribution industry, especially in the steel distribution industry, In the commercial industry, users import various data such as inventory data and shipping data, and create order slips. Manually creating and determining order quantities for each of the many line items. In addition, it is difficult to accurately measure the demand for each of the many items handled. Because it is difficult to predict, there is a possibility of excess inventory or shortages depending on the item being handled. Furthermore, only the person in charge of ordering has the know-how regarding the order quantity, and the person in charge of ordering cannot be replaced. In this case, it is necessary to pass on the know-how.

[0003] In recent years, in order to support such ordering operations, the amount of safety stock has been calculated and the amount of demand has been predicted. However, such technology is not suitable for the material distribution industry. Since it does not correspond to the business flow of ordering, users are required to calculate the safety stock amount and the demand amount. Ordering work needs to be carried out while forecasting using different services, and efficient ordering is required. Therefore, it is difficult to calculate the amount of safety stock and forecast the amount of demand. It is hoped that this will enable the optimization of inventory while improving the efficiency of ordering operations. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2003-242432 Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention provides an information processing system that can optimize inventory while improving the efficiency of ordering operations. The present invention aims to provide a processing device. [Means for solving the problem]

[0006] According to one aspect of the present invention, an information processing device stores inventory data relating to an inventory of a material, and Sales performance data regarding the sales performance of the material, and contract remaining amount data regarding the contract remaining amount of the material. a receiving unit for receiving input of receipt and payment data including the lead time of the material; an acquisition unit that acquires setting data including time data; Based on the data, a safety stock amount indicating the minimum inventory amount of the material to be held is determined. a reference months calculation unit for calculating a reference months' worth of inventory amount for a certain number of months; a demand quantity forecasting unit that forecasts the demand quantity of the material using a statistical forecasting method; the lead time data, the reference number of months, and the demand amount predicted by the demand amount prediction unit. an order determination unit that determines whether to order the material based on the demand amount obtained; an order quantity calculation unit that calculates the order quantity of the material when the determination unit determines that the material should be ordered; an order plan generating unit that generates an order plan for the material based on the order quantity; an order data generating unit that generates order data related to the ordering of the material based on the plan; and an order data output unit that outputs the order data. [Effects of the Invention]

[0007] According to the present invention, it is possible to optimize inventory while improving the efficiency of ordering operations. . [Brief explanation 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. [Figure 2] 1 is a diagram illustrating an example of a configuration of an information processing system according to a first embodiment. [Figure 3] 1 is a diagram illustrating an example of a configuration of an information processing device according to a first embodiment. [Figure 4] FIG. 10 is a diagram showing an example of an item data screen displayed on a display of a terminal device. [Figure 5] FIG. 10 is a diagram showing an example of an order category data screen displayed on a display of a terminal device. [Figure 6] FIG. 10 is a diagram showing an example of a receipt / payment data input screen displayed on the display of the terminal device. [Figure 7] FIG. 10 is a diagram showing an example of values ​​of safety coefficients set for each allowable stockout frequency. [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. 10 is a diagram illustrating a method for selecting one statistical prediction method based on the prediction errors of each of a plurality of statistical prediction methods. [Figure 12] 10 is a flowchart of an order output process executed in the information processing device according to the first embodiment. [Figure 13]10 is a flowchart of an order output process executed in the information processing device according to the first embodiment. [Figure 14] FIG. 10 is a diagram showing an example of a receipt and payment table screen displayed on the display of the terminal device. [Figure 15] FIG. 10 is a diagram showing an example of an order planning screen displayed on a display of a terminal device. [Figure 16] FIG. 10 is a diagram showing an example of an order data output screen displayed on a display of a terminal device. [Figure 17] FIG. 10 is a diagram illustrating an example of a configuration of an information processing device according to a second embodiment. [Figure 18] 10 is a flowchart of an order output process executed in an information processing device according to a second embodiment. [Figure 19] FIG. 10 is a diagram showing an example of a contract remaining amount adjustment screen displayed on a display of a terminal device. [Figure 20] FIG. 10 is a diagram illustrating an example of the configuration of an information processing device according to a third embodiment. [Figure 21] 10 is a flowchart of an order output process executed in an information processing device according to a third embodiment. [Figure 22] FIG. 10 is a diagram illustrating an example of the configuration of an information processing device according to a fourth embodiment. [Figure 23] FIG. 10 is a diagram illustrating an example of a reference number of months setting screen displayed on a display of a terminal device. [Figure 24] FIG. 10 is a diagram showing an example of a first demand forecast screen displayed on a display of a terminal device. [Figure 25] FIG. 10 is a diagram showing an example of a second demand forecast screen displayed on the display of the terminal device. [Figure 26] FIG. 10 is a diagram illustrating an example of a past performance screen displayed on a display of the terminal device. [Figure 27] FIG. 10 is a diagram showing an example of an inventory search screen displayed on a display of a terminal device. [Figure 28] FIG. 10 is a diagram illustrating an example of a Pareto analysis screen displayed on a display of a terminal device. [Figure 29]FIG. 10 is a diagram showing an example of a retained inventory screen displayed on a display of a terminal device. [Figure 30] FIG. 10 is a diagram showing an example of a third demand forecast screen displayed on a display of the terminal device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. It is not something to do.

[0010] [First embodiment] First, an overview of an information processing system 1 according to the first embodiment will be described with reference to FIG. FIG. 1 shows a workflow for ordering materials using the information processing system 1 according to the first embodiment. This information processing system 1 is used in the material distribution industry, including the steel distribution industry. This is a system that supports a series of ordering tasks, including the user's ordering process. The information processing system 1 supports, for example, a user's work when ordering materials such as steel. In the following description, the present invention will be described using a case where the material is steel. The material used is not limited to steel, but can also be other materials. The information processing system 1 includes a user company system 10 and an information processing device 30. The user company system 10 and the information processing device 30 are communicably connected via a network. It continues.

[0011] When a user of the user company system 10 starts an application, information processing The management device 30 extracts data from the backbone system of the user company system 10 and stores it in the backbone system. Next, the information processing device 30 acquires the system data by using a processing tool (step S1). The core system data is processed into sales performance data and inventory data, and this sales performance data and inventory data are input as receipt and payment data (step S2). When receipt and payment data is entered, sales performance data and setup data including lead time data are generated. Based on the data, safety stock theory is used to calculate the minimum amount of safety stock. Based on the safety stock amount, calculate the base number of months that indicates the inventory amount that should be held for the number of months (step Next, the information processing device 30 uses a statistical prediction method based on the sales performance data. Next, the information processing device 30 predicts the demand amount based on the receipt and payment data (step S4). Based on the lead time data, the number of reference months, and the demand volume predicted in step S4, It determines whether or not steel needs to be ordered, calculates the amount of steel that needs to be ordered, and calculates the inventory amount and base month. A receipt and payment table listing the number, order amount, etc. is generated (step S5). Next, the information processing device 30 generates an ordering plan based on the order quantity (step S6). generates order data based on the order plan and outputs the generated order data (step Next, the information processing device 30 performs the following processing based on the order output data output as the order data. Based on this, the purchase order data is generated by the purchase order generation tool (step S8).

[0012] Next, a detailed configuration of the information processing system 1 according to this embodiment will be described with reference to FIG. FIG. 2 is a diagram showing an example of the configuration of the information processing system 1 according to the first embodiment. As shown, the information processing system 1 includes a user company system 10A of a user company A and a user company A user company system 10B of user company B, a user company system 10C of user company C, and an information processing device 30. The user company system 10A of the user company A and the user company system 30 of the user company B are The user company system 10B, the user company system 10C of the user company C, and the information processing device 30 are connected to each other via a network NW so that they can communicate with each other. , a user company system 10A of user company A, a user company system 10B of user company B, and When expressing without distinguishing between User Company C's User Company System 10C, it is simply referred to as "User Company System 10C." It is written as "System 10".

[0013] The user company system 10 is a system owned by the user company. For example, we purchase steel materials from steel manufacturers and steel trading companies, store them in warehouses, and then sell them to end users and wholesalers. This type of business is also called store sales. As shown, the user company system 10 is configured with a terminal device 11 and a core system 12. are.

[0014] The terminal device 11 is a terminal device owned by a user who uses the information processing device 30. For example, For example, mobile devices, tablets, smartphones, wearable devices, personal computers, Computers, etc.

[0015] The core system 12 stores various information of the user company. As shown in FIG. 2, the core system 12 is configured by a server device, etc. The core system 12 stores the data of the core system. Then, the core system data is transmitted to the information processing device 30.

[0016] In the example of FIG. 2 in this embodiment, the user company system 10A of the user company A and the user company system 10B of the user company B are The user company system 10B of user company B and the user company system 10C of user company C are three systems. The system is connected to the network NW, but the usage The number of company systems 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. It may be connected to a network NW.

[0017] The information processing device 30 is a device that supports the user's ordering operations. is, for example, a cloud-based information processing device 30, for example, The following functions and processes are provided in the form of SaaS (Software as a Service) The information processing device 30 is a cloud-based information processing device 30. The above functions and processes may be provided in the form of information processing equipment. The device 30 may be an on-premise device.

[0018] Network NW refers to the entire information and communication network that uses telecommunications technology. The network is, for example, a wireless network such as a hospital backbone LAN (Local Area Network). / In addition to wired LANs and Internet networks, telecommunications circuits and optical fiber communication networks , cable communication networks and satellite communication networks.

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

[0020] The communication unit 31 implements various information communication protocols according to the form of the network NW. The communication unit 31 communicates with other devices via the network NW in accordance with these various protocols. In particular, in this embodiment, the information processing device 30 realizes the following communication via the communication unit 31: By connecting to the network NW, 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 various data for each user company. This setting data is related to the lead time of the steel material. This lead time data includes, for example, the period from procurement to delivery. The setting data includes a delivery period and an order interval, which is the interval between the previous order and the next order. For example, product information including the name of the item, weight, unit price, minimum order quantity, supplier for each item, etc. Data on the rolling lines (hereafter referred to as "mills") of steel manufacturers assigned to each item It includes order category data, etc.

[0022] FIG. 4 is a diagram showing an example of an item data screen displayed on the display of the terminal device 11. As shown in Figure 4, the item data screen SC1 displays the name of the item as the item data. The item name includes the unit weight, which indicates the weight per unit, the purchase price, the standard supplier, and the minimum order quantity. The user operates the input device of the terminal device 11 to The item data can be edited via the terminal device 11. This corresponds to the display unit in the embodiment.

[0023] FIG. 5 shows 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, As data, a mill is assigned to each item. The order category data can be edited via the

[0024] The control unit 33 performs various processes. For example, the control unit 33 receives input of receipt and payment data. The system acquires the setting data, calculates the number of base months, predicts the demand, determines whether or not to order, and issues the The order amount is calculated, an order plan is generated, order data is generated, and the order data is output.

[0025] For this reason, as shown in FIG. 3, the control unit 33 includes a receiving unit 331, an acquiring unit 332, and a reference A months calculation unit 333, a demand amount prediction unit 334, an order determination unit 335, and an order amount calculation unit 336 a first display control unit 337, an ordering plan generation unit 338, a second display control unit 339, and an ordering It includes a data generation unit 3310 and an order data output unit 3311 .

[0026] The reception unit 331 receives inventory data relating to the stock of materials, sales performance data relating to the sales performance of materials, and the like. and input of receipt and payment data including contract remaining data on the remaining contract quantity of materials (import Accepts (port).

[0027] FIG. 6 is a diagram showing an example of a receipt / payment data input screen displayed on the display of the terminal device. As shown in Figure 6, on the receipt and payment data input screen SC3, the receipt and payment data is Inventory data for each month includes the previous month's inventory results and the current month's inventory results, and sales results for each steel item The data includes the previous month's shipping volume, which is the previous month's shipping results, and the remaining contract quantity data for each steel item. As shown in Figure 6, the current month's steel inventory data includes the remaining contract amount. The inventory results are the inventory amount of steel materials for each item at the user company's own base where the user company system 10 is located. , the inventory of steel materials at other bases different from the own base, and the inventory of steel materials at relay points between the own base and other bases. In addition, the receipt and payment data displayed on the receipt and payment data input screen SC3 includes the inventory amount of materials. Sales performance data for the current month may be used in addition to or instead of the previous month's shipment performance. It may also include the shipping volume for the current month, which is the shipping volume for the month, and the shipping volume for the previous month and earlier. The shipping records for the previous month and the month before are also called past shipping records. By checking the receipt and payment data input screen SC3 displayed on the display of the terminal device 11, This allows you to check receipt and payment data before it is entered.

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

[0029] The reference number of months calculation unit 333 calculates the reference number of months. The reference month number calculation unit 333 calculates the reference month number by calculating the minimum inventory amount of steel materials. That is, the reference month number calculation unit 333 calculates the safety stock amount indicating the Calculate the number of base months. The formula for calculating this safety stock amount is expressed as formula (1).

number

[0030] The safety coefficient k in this formula (1) is a value set for each allowable stockout frequency. The coefficient k is set for each item as setting data and stored in the storage unit 32. 7 is a diagram showing an example of the value of the safety coefficient k set for each allowable stockout frequency. For example, if the stockout tolerance frequency is 3 months / quarter, that is, stockouts are allowed once every 3 months, In this case, the safety factor k is 0.43. As shown in Figure 7 and formula (1), the allowable stockout frequency is The larger the demand, the larger the safety stock. It is calculated based on the past shipments of the product.

[0031] The demand forecasting unit 334 forecasts the demand for steel products using a statistical forecasting method based on sales performance data. The demand quantity forecasting unit 334 forecasts the demand quantity of steel materials using a statistical forecasting method. By using this method, transactions are only conducted once a month, such as in the steel distribution industry. There are cases where data accumulation takes time due to the low frequency of transactions, such as when transactions are made online. If the types of data to be collected are limited to shipment volume, inventory volume, etc., the number of items handled is large and It is possible to predict the demand amount even when the demand fluctuations differ from one day to the next.

[0032] In addition, the demand quantity prediction unit 334 according to this embodiment selects one of a plurality of statistical prediction methods for each item. The demand is predicted by selecting a forecasting method. Examples of multiple statistical forecasting methods include: 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 methods ( Winters additive method), seasonal smoothing method (Winters multiplicative method), seasonally adjusted regression analysis (additive method) solution), seasonally adjusted regression analysis (multiplicative decomposition), seasonally adjusted power function (multiplicative decomposition), seasonal Adjusted exponential function (multiplicative decomposition), seasonally adjusted logarithmic function (multiplicative decomposition), Croston method, cumulative method, marketing EOL, null method, naive method, year-on-year comparison, previous year, and linear approximation method, etc. These multiple statistical forecasting methods are stored in the storage unit 32. The demand forecasting unit 33 4 calculates the forecast error for each of several statistical forecasting methods based on sales performance data. Therefore, the forecast error that is the smallest among the forecast errors of multiple statistical forecasting methods is selected. The method is used to forecast the demand for steel.

[0033] The method for selecting a statistical forecasting method will be explained in detail using Figures 8 to 11. FIG. 9 is a diagram showing a method for calculating a prediction error in the learning method shown in FIG. 10 is a diagram for explaining an outline of the verification method shown in FIG. Figure 11 shows the statistical forecast of 1 based on the forecast error for each of several statistical forecasting methods. FIG. 10 is a diagram illustrating a method for selecting a technique.

[0034] As shown in FIG. 8, the demand forecasting unit 334 generates a plurality of statistical forecasts based on sales performance data. We used cross-validation for each measurement method, sliding the learning and validation periods. However, the prediction errors of the multiple statistical forecasting methods are The mean absolute percentage error (MAPE) for each For example, in the first learning and verification period shown in Figure 8, the demand As shown in FIG. 9, the quantity prediction unit 334 calculates the learning data from the learning start month to the N+1 month and the Using the statistical prediction method, each model corresponding to each statistical prediction method is trained. During the verification period in the first learning and verification shown in FIG. As shown in the figure, we used the sales performance data from the validation period and the predicted values ​​output from the trained model. Specifically, the demand forecasting unit 334 calculates the MAPE for the first learning and validation round. APE = absolute value of (total value of validation period - total value of forecast value) ÷ total value of validation period Then, the demand forecasting unit 334 repeats the learning and verification X times. .

[0035] Next, as shown in FIG. 11, the demand forecasting unit 334 calculates the demand for each model corresponding to each statistical forecasting method. Calculate the average MAPE value for each of the training and validation rounds from the 1st to Xth rounds. Then, the demand forecasting unit 334 selects the statistical forecasting method that minimizes MAPE. The demand for steel products is predicted using a statistical forecasting method such as

[0036] The order determination unit 335 determines whether to order the steel material. 5 is a diagram showing the data for receipt and payment, lead time data, the number of reference months, and the forecast by the demand forecasting unit 334. Based on the measured demand, it is determined whether to order steel materials.

[0037] When the order determination unit 335 determines that the steel material is to be ordered, the order quantity calculation unit 336 Specifically, in the steel distribution industry, orders are placed on a monthly basis as a business practice. Therefore, the order quantity calculation unit 336 calculates the order quantity based on the periodic ordering method. The periodic ordering method is a method of placing orders at predetermined times, and each order is Delivery period T + Order interval O) × Planned amount of use (Monthly requirement) + Safety stock amount A = Current inventory amount (Current month inventory amount) This is a method of determining the order amount so that the balance of "stock amount + contract remaining amount + order amount" is achieved. In this embodiment, the order quantity calculation unit 336 calculates the reference number of months and the The order quantity is calculated using the number of months of holding, etc., which will be described later.

[0038] The first display control unit 337 controls the terminal 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. Then, as an order quantity management screen, a receipt and payment table screen including a receipt and payment table is displayed on the display of the terminal device 11. Display it.

[0039] The ordering plan generation unit 338 generates an ordering plan for steel materials based on the order quantity. The order plan is a plan for allocating the order quantity of each item. displays an ordering plan screen for managing the ordering plan generated by the ordering plan generating unit 338. The display of the terminal device 11 is controlled as shown in the figure. This corresponds to the order plan management screen in the current state.

[0040] The order data generation unit 3310 generates order data related to the ordering of steel materials based on the order plan. The order data output unit 3311 outputs the order data.

[0041] 12 and 13 show an order placement process executed by the information processing device 30 according to the first embodiment. 10 is a flowchart of the order output process. In this order output process, the information processing device 30 It accepts input data, acquires setting data, calculates the number of base months, and forecasts demand. It measures the quantity of goods, determines whether an order is necessary, calculates the order amount, generates a receipt and payment table, and calculates the order amount. Generates an image, generates order data, displays receipt and payment tables, and displays the order planning screen. For example, this issue The output process is performed when the user executes a dedicated application on the terminal device 11. This is the process to be performed.

[0042] First, as shown in FIG. 12, the reception unit 331 in the control unit 33 of the information processing device 30 The receiving unit 331 receives input of receipt and payment data (step S11). The core system data acquired from the core system 12 of the user company system 10 via the unit 31 Inventory data, sales performance data, and contract remaining data generated by processing the data More specifically, the receiving unit 331 receives input (import) of receipt and payment data including the data. The terminal device 11 is configured to collect inventory data, sales data, and other data based on the user's input operation via the input device of the terminal device 11. The system accepts input of sales performance data and receipt / payment data including contract remaining amount data.

[0043] Next, as shown in FIG. 12, the acquisition unit 332 in the control unit 33 of the information processing device 30 The acquisition unit 332 acquires the setting data (step S13). In this embodiment, the setting data is , including minimum order quantity data regarding minimum order quantities of steel products.

[0044] Next, as shown in FIG. 12, the reference month number calculation unit 3 in the control unit 33 of the information processing device 30 The reference number of months calculation unit 333 calculates the reference number of months (step S15). The base number of months is calculated based on the sales performance data and the lead time data. The base month number calculation unit 333 calculates the base month number based on the sales performance data and the lead time data. Calculate the number of base months using the number of base months = safety stock amount ÷ average monthly shipping amount + supply period T + order interval O do.

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

[0046] Next, in step S15, the reference month number calculation unit 333 calculates the reference month number based on the sales performance data. Specifically, the reference month number calculation unit 333 calculates the average monthly shipping volume based on the sales performance data. The average monthly shipment volume is calculated by averaging the past shipment records. The period of past shipments in the sales performance data used to calculate the average shipment volume is In the sales performance data used to calculate the standard deviation σ of the demand quantity in the above formula (1), For example, the standard deviation σ of the demand volume is calculated based on the The past shipping data in the sales performance data available is shipping data for the past 60 months. In the case of data of the sales performance data used to calculate the average of past shipment performance, The data on past shipment performance also covers the past 60 months.

[0047] Then, in step S15, the reference month number calculation unit 333 calculates the calculated safety stock amount and Based on the calculated average monthly shipment volume and lead time data including procurement period and order interval, , the number of base months = safety stock amount ÷ average monthly shipment amount + procurement period T + order interval O, Calculate.

[0048] Next, as shown in FIG. 12, the demand amount prediction unit 33 in the control unit 33 of the information processing device 30 4 predicts the demand (step S17). Specifically, the demand prediction unit 334 predicts the sales Based on actual data, the demand volume is predicted using statistical forecasting methods. The required quantity prediction unit 334 selects one statistical prediction method from a plurality of statistical prediction methods based on the sales performance data. Based on the sales performance data, the selected statistical forecasting method is used to predict the demand. The demand amount prediction unit 334 predicts the demand amount, for example, The predicted value of the shipping volume up to the future is derived.

[0049] Next, as shown in FIG. 12, the order determination unit 335 determines whether an order is necessary (step Specifically, the order determination unit 335 uses the receipt and payment data, the lead time data, and , and orders steel materials based on the reference number of months and the demand amount predicted by the demand amount prediction unit 334. More specifically, the order determination unit 335 determines whether or not the shortage amount is equal to the reference number of months. Calculate the shortage amount using (number of months) x monthly requirement amount and determine whether the shortage amount is greater than 0. This determines whether or not to order steel.

[0050] The method for determining whether to order steel materials will be described in detail below. First, step S1 In step 9, the order determination unit 335 calculates the monthly required amount. 5 is a single-month forecast based on lead time data and the forecast value of shipping volume up to the lead time destination. Required quantity = predicted shipping quantity up to the lead time destination ÷ (supply period T + order interval O) Calculate the monthly required amount.

[0051] Next, in step S19, the order determination unit 335 calculates the inventory amount for the current month. In this case, the order determination unit 335 determines the inventory data, sales performance data, and Based on the contract remaining quantity data and lead time data, current month's inventory quantity = previous month's inventory quantity - shipment quantity The current month's inventory amount is calculated using (current month's shipment amount) + (current month's arrival amount).

[0052] Next, in step S19, the order determination unit 335 calculates the number of months of retention. The number of months of stock is the amount of stock currently held for the number of months. , the calculated monthly requirement, the calculated inventory amount for the current month, and the contract remaining amount data in the receipt and payment data. Based on this, the number of months to hold is calculated using the following formula: Number of months to hold = (current month inventory + remaining contract amount) / monthly requirement. Put out.

[0053] Next, in step S19, the order determination unit 335 calculates the shortage amount. The order determination unit 335 compares the reference number of months calculated in step S15 with the reference number of months calculated in step S1 Based on the number of holding months calculated in 9 and the monthly required amount, the shortage amount = (base number of months - holding month The shortage amount is calculated using the number of units multiplied by the monthly required amount.

[0054] Then, in step S19, the order determination unit 335 determines whether the calculated shortage amount is greater than 0. In other words, by determining whether the shortage amount is greater than 0, it is possible to decide whether to order steel. Make a judgment.

[0055] Then, in step S19, it is determined that an order is necessary, that is, that steel materials are to be ordered. If it is determined that the order has been made (step S19: Yes), the control unit 33 of the information processing device 30 The quantity calculation unit 336 calculates the order quantity (step S21). 36 calculates the order quantity so that it exceeds the minimum order quantity of steel included in the setting data. More specifically, for example, the order quantity calculation unit 336 calculates the minimum order quantity of steel material included in the setting data. The order quantity is calculated so that the shortage amount exceeds the minimum order quantity. In step S19, if the shortage amount exceeds the minimum order amount, the order amount calculation unit 336 Alternatively, the shortage amount calculated in step S19 may be calculated as the order amount.

[0056] On the other hand, in step S19, it is determined that an order is not necessary, that is, that steel materials will not be ordered. If it is determined that the information processing is performed correctly (step S19: No), or after the process of step S27, The first display control unit 337 in the control unit 33 of the device 30 generates a receipt and payment table (step S twenty three).

[0057] Next, as shown in FIG. 13, the ordering plan generating unit 3 in the control unit 33 of the information processing device 30 The ordering plan generating unit 338 generates an ordering plan (step S25). Specifically, the ordering plan generating unit 338 An ordering plan is generated based on the order quantity calculated in step S21.

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

[0059] Next, as shown in FIG. 13, the first display control unit 3 in the control unit 33 of the information processing device 30 37 determines whether or not to display the receipt and payment table (step S29). The control unit 337 receives and displays a receipt and payment table from the user via the input device of the terminal device 11. By determining whether or not the input operation of the user has been accepted, it is determined whether or not to display the receipt and payment table. Here, the input operation for displaying the receipt and payment table screen including the receipt and payment table is, for example, This is an input operation to select this receipt and payment table screen in a pull-down menu including:

[0060] If it is determined in step S29 that the receipt and payment table is to be displayed (step S2 9: 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 Figure 14, the receipt and payment table in the receipt and payment table screen SC4 displays the item data and the location data for each item. The inventory of steel materials at the point, the inventory of steel materials at other bases, and the inventory of steel materials at relay points the recommended quantity indicating the order quantity calculated by the order quantity calculation unit 336, the monthly required quantity, and the The receipt and payment table includes the number of months and the number of base months, etc. In addition, the receipt and payment table includes the adjustment staff so that the order quantity can be adjusted. The first display control unit 337 allows the user to select a desired item via the input device of the terminal device 11. The input operation to adjust the order quantity from the user, that is, the order quantity for this adjustment number item The order amount is adjusted by receiving the adjustment amount. When the order quantity is adjusted via this receipt and payment table screen SC4, The order plan is regenerated based on the adjusted order quantity via If so, the order data generation unit generates the order data based on the regenerated order plan. Generate again.

[0062] On the other hand, if it is determined in step S29 that the receipt and payment table is not to be displayed (step S2 9: No), or after the processing of step S31, The second display control unit 339 determines whether or not to display the order planning screen (step S33 Specifically, the second display control unit 339 receives an input from the user via the input device of the terminal device 11. By determining whether or not an input operation for displaying the order planning screen from the It is determined whether or not to display the order planning screen. Here, the input for displaying the order planning screen is For example, the operation is to select this order planning screen from the pull-down menu containing each screen name. This is an input operation to select.

[0063] Then, in step S33, if it is determined that the order planning screen is to be displayed (step Step S33: Yes), the second display control unit 339 in the control unit 33 of the information processing device 30 The order planning screen is displayed (step S35). 15 is a diagram showing an example of a displayed order planning screen. In the ordering plan on the ordering plan screen SC5, enter the standard supplier, order quantity, and number of orderers for each item. The order planning screen SC5 also includes information IF1 about the order quantity for each mill. Specifically, the information IF1 on the order quantity for each mill is the possible order quantity for each mill and the number of orders already placed. The second display control unit 339 displays the quantity already ordered, the quantity currently ordered, and the excess quantity. If the sum of the amount and the current order amount exceeds the possible order amount, the color of the excess amount column will change to alert you. The display of the order planning screen SC5 is controlled so that the order planning screen SC5 changes. In this case, the second display control unit 339 checks the check box of the mill that is the timing for placing an order. The timing of ordering is determined based on the user's input operations related to sorting, such as entering a check. The display of the terminal 11 is controlled so that the mill can sort only the items assigned to it. For example, manufacturer A uses Mill 1 for items with large outer diameters. The order timing for the items handled by Mill 1 is early every month, while the order timing for the outer diameter The smaller size items are handled by Mill 2, and the order timing of the items handled by Mill 2 is The timing of user orders varies from mill to mill, with mills ordering at the end of each month. For example, the period when the order quantity is calculated for each item is divided into the first, middle and last quarter of the month. Therefore, the timing for ordering is in the early part of the month and the middle of the month. Only items that are available at mills that are scheduled for the first half of the month and items that are available at mills that are scheduled for the second half of the month are sorted. In addition, the order plan screen SC5 has a function that allows you to adjust the order plan. In this way, an item for the number of orderers is provided, and the input of the terminal device 11 for this item for the number of orderers is By receiving an input operation for adjusting the ordering plan from the user via the input device, The order plan is adjusted. Then, the order data generation unit 3310 displays this order plan screen SC When the purchase order plan is adjusted via the purchase order plan screen SC5, the total purchase order adjusted via the purchase order plan screen SC5 Based on the image, the order data is regenerated.

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

[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 33 in the control unit 33 of the information processing device 30 The terminal device 11 displays the order data output screen (step S39). 10 is a diagram showing an example of an order data output screen displayed on the second display control unit 33. 9, in the order data in the order data output screen SC6 shown in FIG. 16, for each item, the supplier, The order form, quantity, weight, unit price, etc. are displayed. Also, on the order data output screen SC6, The order details output button is displayed.

[0066] Next, as shown in FIG. 13, the second display control unit 3 in the control unit 33 of the information processing device 30 39 determines whether to output the order data (step S41). The display control unit 339 controls the order details output button B displayed on the order data output screen SC6. By determining whether or not 1 has been pressed, it is determined whether or not to output the order data. Then, in step S41, if it is determined that the order data is not to be output (step S41: No), or in step S37, the order data output screen is not displayed. If it is determined that the step S37 is not completed (No), the process returns to step S29. Repeat the process from step 9.

[0067] On the other hand, if it is determined in step S41 that the order data is to be output (step S4 1: Yes), the order data output unit 3311 in the control unit 33 of the information processing device 30 The order data is output (step S43). By executing this step S43, The order output process ends. After this order data is output, the order data is treated as order output data. The data is then converted into purchase order data by a purchase order generation tool.

[0068] As described above, in the information processing device 30 according to this embodiment, the input of receipt and payment data is received. It receives the data, retrieves the setting data, calculates the number of base months, predicts the demand, and orders the steel. If it is determined that an order should be placed, the order quantity is calculated and an order plan is made based on the order quantity. generating order data based on the order plan; and outputting the generated order data. This makes it possible to optimize inventory while improving the efficiency of 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 remaining contract 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. The configuration of the information processing system according to the second embodiment is the same as that according to the first embodiment. Since it is the same as the information processing system 1, the explanation will be omitted.

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

[0071] The contract remaining amount adjustment unit 3312 adjusts the contract remaining amount in the contract remaining amount data included in the receipt and payment data. Accepts input operations from the user regarding adjustments, and adjusts the remaining contract amount according to the accepted input operations. Adjust.

[0072] FIG. 18 is a flowchart of an order output process executed in the information processing device 30 according to the second embodiment. 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, and sets setting data It can obtain the data, calculate the number of base months, forecast the demand, and determine whether or not to place an order. For example, this order output process can be performed by the user on the terminal device 11. This is the process that is executed when a dedicated application is executed. The process of step S11 is the same as that in FIG. 12, and therefore a description thereof will be omitted.

[0073] Next, as shown in FIG. 18, the contract remaining amount adjusting unit 3 in the control unit 33 of the information processing device 30 312 determines whether to adjust the remaining contract amount (step S51). The remaining amount adjustment unit 3312 receives a contract remaining amount adjustment screen from the user via the input device of the terminal device 11. The contract remaining amount is adjusted by determining whether an input operation related to the generation of Here, the input operation related to the generation of the contract remaining amount adjustment screen is, for example, In the pull-down menu containing the screen name, select this contract remaining charge adjustment screen by input operation. be.

[0074] Then, in step S51, if it is determined that the remaining contract amount is to be adjusted (step S 53: Yes), the contract remaining amount adjusting unit 3312 in the control unit 33 of the information processing device 30 Specifically, the contract remaining amount adjusting unit 3312 generates a contract remaining amount adjustment screen (step S53). A contract remaining amount adjustment screen is generated based on the contract remaining amount data.

[0075] Next, as shown in FIG. 18, the contract remaining amount adjusting unit 3 in the control unit 33 of the information processing device 30 312 displays the contract remaining amount adjustment screen (step S55). The unit 3312 controls the display unit 3313 to display the contract remaining amount adjustment screen generated in step S53. Controls the display of the terminal device 11.

[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 display of the terminal device 11 displays a contract remaining amount adjustment screen SC 7 is displayed. This contract remaining amount adjustment screen SC7 displays the order number and the contract remaining amount for each item. The contract balance adjustment unit 3312 adjusts the contract balance. While the remaining amount adjustment screen SC7 is displayed, the following is input via the input device of the terminal device 11: Accepts input operations from the user regarding adjustment of the remaining contract amount in the remaining contract amount data, and In the example shown in FIG. 19, the remaining contract amount is adjusted according to the input operation received. The adjustment unit 3312 receives input operations from the user regarding adjustment of the remaining contract amount for each steel material item. Accepts the input operation of entering a check mark in the completion flag set in The remaining contract amount of the material that has been checked in the set completion flag is set to 0, that is, the contract is It is assumed to be completed.

[0077] On the other hand, in step S51, if the contract remaining amount is not adjusted (step S51: No), Alternatively, after the process of step S55, the acquisition unit 33 in the control unit 33 of the information processing device 30 2 acquires the setting data (step S13). The process from step S13 onward is the same as that shown in FIG. 12 and 13, so the explanation will be omitted. Then, step S43 is executed. This completes the order output process according to this embodiment.

[0078] As described above, in the information processing device 30 in the information processing system 1 according to the second embodiment, In this case, when adjusting the remaining contract amount, the contract remaining amount adjustment screen is displayed and the contract remaining amount adjustment section 3312 receives input operations from the user regarding adjustment of the contract remaining amount in the contract remaining amount data. The remaining contract amount will be adjusted according to the input operation received. Due to business practices in the material distribution industry, the amount of inventory received may not necessarily match the amount of orders. In particular, when the amount of inventory received is less than the amount of orders, it is necessary to adjust the remaining contract amount. This prevents the remaining contract amount from becoming noise when calculating order quantities and generating order plans. This will prevent inventory issues and improve the efficiency of ordering operations. can be done.

[0079] Third Embodiment In the information processing device 30 according to the first and second embodiments described above, the demand for steel is intermittent. In this case, it is possible to predict the demand. The third embodiment is a case where the present invention is applied to the first embodiment, and the differences from the first embodiment will be described. The case where this modification is applied to the first embodiment will be described. The configuration of the information processing system according to the third embodiment is also applicable to the second embodiment. is the same as that of the information processing system 1 according to the first embodiment described above, and therefore the 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. 20 is a diagram corresponding to FIG. 3. As shown in FIG. 20, the control unit 33 is The control unit 33 is configured by adding an intermittent determination unit 3313 to the control unit 33. In the information processing device 30 in the information processing system 1 according to this embodiment, the control unit 3 The demand amount prediction unit 334a is different from that of the first embodiment. The configuration other than the demand amount prediction unit 334a and the intermittent operation determination unit 3313 is the same as that in FIG. Therefore, the explanation will be omitted.

[0081] The intermittent supply determining unit 3313 determines whether the demand for steel is intermittent based on the sales performance data. Here, the demand is intermittent when the shipment volume of the sales performance data is This is the case when the weight is 0 kg for N consecutive months. N can be set arbitrarily by the user. Cut.

[0082] When it is determined that the demand for steel is intermittent, the demand amount prediction unit 334a according to this embodiment In this case, the moving average method is used as a statistical forecasting method to predict the demand for steel products. When it is determined that the demand for steel is not intermittent, the quantity prediction unit 334a performs a plurality of statistical prediction methods. Among the prediction errors in each method, the statistical prediction method that minimizes the prediction error is used. , and forecast the demand for steel products.

[0083] FIG. 21 is a flowchart of an order output process executed in the information processing device 30 according to the third embodiment. 12. In this order output process, the information processing device 30 accepts input of receipt and payment data, acquires setting data, calculates the base number of months, Determine whether demand is intermittent, forecast demand, and determine whether an order needs to be placed. For example, this order output process may be performed by a user on the terminal device 11. This is the process that is executed when a dedicated application is executed in the The processes from step S11 to step S15 shown in FIG. 12 are the same as those in FIG. 12, so the explanation will be omitted. is omitted.

[0084] Next, as shown in FIG. 21, the intermittent determination unit 331 in the control unit 33 of the information processing device 30 3 determines whether the demand is intermittent (step S61). The unit 3313 determines whether the demand for steel materials is intermittent based on the sales performance data. .

[0085] Then, in step S61, if it is determined that the demand is intermittent (step S 61: Yes), the demand forecasting unit 334a in the control unit 33 of the information processing device 30 The demand amount is predicted using the averaging method (step S63). 4a predicts the demand volume using the moving average method based on the sales performance data. The moving average method is a method of using the average value of shipment volume (demand volume) over the last N months as the forecast value.

[0086] On the other hand, if it is determined in step S61 that the demand is not intermittent (step S6 1: No.), the demand forecasting unit 334 in the control unit 33 of the information processing device 30 performs statistical forecasting of 1. The demand is predicted using a measurement method (step S17). 12 and 13, so the explanation will be omitted. By performing this, the order output process according to this embodiment is completed.

[0087] As described above, in the information processing device 30 according to this embodiment, whether the demand is intermittent or not If the demand is determined to be intermittent, the moving average method is used to calculate the demand. Therefore, it is possible to predict the demand even when the demand is intermittent. Therefore, even when demand is intermittent, we can optimize inventory and streamline ordering operations. Efficiency can be achieved.

[0088] [Fourth embodiment] In the information processing device 30 according to the first to third embodiments described above, the order determination and the order quantity are The reference number of months used in the calculation is a value calculated by the reference number of months calculation unit 333. In the fourth embodiment, the information processing device 30 receives a message from a user. The user selects between the inputted reference number of months and the reference number of months calculated by the reference number of months calculation unit 333. The selected base number of months is accepted from the user and set as the base number of months used to calculate the order quantity. The case where this modification is applied to the first embodiment is referred to as the fourth embodiment. First, differences from the first embodiment will be described. The configuration of the information processing system is the same as that of the information processing system 1 according to the first embodiment described above. 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 the fourth embodiment. 22 is a diagram corresponding to FIG. 3. As shown in FIG. 22, the control unit 33 is The control unit 33 includes a reference number of months setting unit 3314 added thereto. The configuration other than the reference number of months setting unit 3314 is the same as that in FIG. 3, and therefore a description thereof will be omitted.

[0090] The reference number of months setting unit 3314 calculates the reference number of months input by the user and the reference number of months calculation unit 33 3. Accept the user's selection of the base number of months calculated by 3. and issue the selected base number of months. This is set as the reference number of months used to calculate the order amount. When the reference number of months to be used for calculating the order date is set, the order determination unit 335 calculates the order date by the set reference number of months. The order quantity calculation unit 336 determines again whether to place an order using the set reference number of months. The order quantity is calculated again using the above.

[0091] FIG. 23 shows 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 number of base months can be input for each item. The user is asked to select either the calculated or the calculated base number of months for each material. The 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, In this case, 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 are used. The user selects the number of base months and the number of quasi-months, and the selected number of base months is used to calculate the order quantity. Since it is set as a quasi-month number, the value of the base month number can be adjusted, so inventory This will enable us to streamline ordering operations while optimizing the system.

[0093] [Other Modifications] In the information processing device 30 according to the first to fourth embodiments described above, the demand amount prediction unit 33 4, 334a are the forecast errors of the moving average method and multiple statistical forecasting methods. , and the statistical forecasting method that minimizes the forecast error is selected from the user. The demand may be predicted using a prediction method. 24 is a diagram showing an example of a first demand forecast screen displayed on a display. 1 On the demand forecast screen SC9, there is a check box for selecting the moving average method for each item. , a checkbox to select the statistical forecasting method that minimizes the forecast error as the system recommendation. This allows the user to input the product information via the input device of the terminal device 11. For each item, choose either the moving average method or the statistical forecasting method that minimizes the forecast error. is possible.

[0094] Furthermore, in the information processing device 30 according to the first to fourth embodiments described above, the user For steel products for which the moving average method is used as a statistical forecasting method, monthly requirements can be confirmed. 25 shows the display of the terminal device 11. 25 is a diagram showing an example of a second demand forecast screen. As shown in FIG. 25, the second demand forecast screen SC1 0 shows the monthly requirement for each steel item, for which the moving average method is used as a statistical forecasting method. This allows users to easily use moving averages, which are likely to be used as statistical forecasting methods. The monthly required quantity of steel products whose demand has been predicted using this method can be easily confirmed.

[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 volume and inventory volume. 26 is a diagram showing an example of a past performance screen displayed on the display. The actual result screen SC11 displays inventory data in the receipt and payment data that the reception unit 331 receives as input. Based on the past sales data, the past shipment and inventory volume of the selected steel item is displayed. By displaying this past performance screen, the user can check the shipping volume and Past inventory levels can be easily referenced.

[0096] In addition, in the information processing device 30 according to the first to fourth embodiments described above, The inventory quantity may be searched. 27 is a diagram showing an example of an inventory search screen. As shown in FIG. 27, the inventory search screen SC12 There is an input box for entering specifications, dimensions, etc., a search button, and a search function for the items entered in the input box. The current inventory of items that match the content you have entered is displayed. This allows users to save time by searching for the stock amount of a specific steel item and The inventory of the item can be easily checked.

[0097] In addition, in the information processing device 30 according to the first to fourth embodiments described above, the Pareto distribution 28 is a diagram showing the analysis of the terminal device 11. 28 is a diagram showing an example of a Pareto analysis screen. As shown in FIG. 28, the Pareto analysis screen SC1 3 shows the Pareto chart, which is the result of the Pareto analysis. From the left, the Pareto chart shows The customers with the largest shipping weights are listed along with their shipping weights, and the cumulative shipping weight ratio is displayed overlaid. In this way, the user can see the results of this Pareto analysis. .

[0098] Furthermore, in the information processing device 30 according to the first to fourth embodiments described above, the user 29 is displayed on the display of the terminal device 11. 29 is a diagram showing an example of a slow-moving inventory screen displayed on the slow-moving inventory screen SC14. For example, the first display control unit 337 displays the inventory amount and the date of receipt for each item. If the difference between the date when this screen is displayed and the base month number is later than the stock entry date, If there are any items that are in a slow-moving inventory, the color of the receiving date of the corresponding item on the slow-moving inventory screen SC14 will be changed. By checking this slow inventory screen SC14, the user can easily check the slow inventory. You can manage the warehouse.

[0099] Furthermore, in the information processing device 30 according to the first to fourth embodiments described above, the user It may also be possible to check the actual monthly shipping volume and predicted demand volume for each item. 10 is a diagram showing an example of a third demand forecast screen displayed on the display of the terminal device 11. FIG. As shown in FIG. 30, the third demand forecast screen SC15 displays the actual monthly shipping volume for each item and In this way, the user can see the actual monthly shipment volume for each item. and forecasted demand values ​​can be referenced.

[0100] In addition, in the information processing apparatuses according to the first to fourth embodiments described above, the screens are displayed by As an input operation for the user, buttons for transitioning to other screens are displayed on each screen, and the user can Each screen can be displayed by pressing the button to transition to another screen. stomach.

[0101] Finally, although various embodiments of the present invention have been described, they are presented by way of example only. and are not intended to limit the scope of the invention. It is possible to carry out the invention in various forms, and various omissions and substitutions may be made without departing from the spirit of the invention. The embodiments and their modifications are within the scope and spirit of the invention. The present invention is also included in the scope of the inventions described in the claims and their equivalents. [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 month number calculation unit, 334, 334a...demand amount prediction unit, 334 a... demand quantity forecasting unit, 335... order determination unit, 336... order quantity calculation unit, 337... first display control unit, 338... ordering plan generation unit, 339... second display control unit, 3310... ordering data generation unit, 3311...Order data output unit, 3312...Contract remaining amount adjustment unit, 3313...Intermittent determination unit, 33 14...Base month number setting section

Claims

1. Inventory data on the inventory of materials, sales performance data on the sales performance of the materials, and a receiving unit for receiving input of receipt and payment data including contract remaining amount data relating to the contract remaining amount of the material; and, Obtaining configuration data including lead time data regarding the lead time of the material Department and Based on the sales performance data and lead time data, the minimum inventory amount of the material is determined. The number of months to calculate the number of months of inventory to be held based on the safety stock amount indicated. A calculation unit; Based on the sales performance data, a statistical forecasting method is used to forecast the demand for the material. a demand prediction unit; The receipt and payment data, the lead time data, the reference number of months, and the demand quantity forecasting unit an order determination unit that determines whether to order the material based on the demand amount predicted by the above; 、 When the order determination unit determines that the material is to be ordered, the order amount of the material is calculated. an order quantity calculation unit; an order plan generation unit that generates an order plan for the material based on the order quantity; An order data generator that generates order data regarding the ordering of the material based on the order plan. With Naribe, an order data output unit that outputs the order data; An information processing device comprising:

2. The information processing device according to claim 1 , wherein the material is steel.

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

4. Further, a storage unit that stores a plurality of the statistical prediction methods, The demand prediction unit Based on the sales performance data, a prediction error in each of the plurality of statistical prediction methods is calculated. Find the difference, Among the prediction errors in each of the plurality of statistical prediction methods, the one with the smallest prediction error is and predicting the demand for the material using a statistical prediction method comprising: The information processing device according to claim 1 .

5. The demand forecasting unit calculates the demand for a certain product from each of the plurality of statistical forecasting methods based on the sales performance data. The cross-validation method is used for each of the plurality of statistical prediction methods to compare the prediction errors of each of the plurality of statistical prediction methods. The mean absolute percentage error is calculated as the difference, and the mean absolute percentage error is the smallest. The information processing device according to claim 4 , wherein the demand amount of the material is predicted using a statistical prediction method. Place.

6. determining whether the demand for the material is intermittent based on the sales performance data; Further comprising a determination unit, When it is determined that the demand for the material is intermittent, the demand amount forecasting unit 2. The information processing method according to claim 1, wherein the demand amount of the material is predicted using a moving average method as a measurement method. Information processing device.

7. Accepting an input operation from a user regarding adjustment of the contract remaining amount in the contract remaining amount data and a contract remaining amount adjusting unit that adjusts the contract remaining amount in response to the received input operation. The information processing device according to claim 1 .

8. Table 1: Controlling the display unit to display an order quantity management screen for managing the order quantity The information processing device according to claim 1 , further comprising a display control unit.

9. When the order quantity is adjusted via the order quantity management screen, the order plan generation unit: The order plan is regenerated based on the order quantity adjusted via the order quantity management screen. The information processing device according to claim 8 .

10. The inventory data includes the amount of the material in stock at the home base and the amount of material in stock at other bases different from the home base. the inventory amount of the material at the location and the inventory amount of the material at the relay point between the location and the other location and the amount, The order quantity management screen displays the stock amount of the material at the home base and the stock amount at the other base. The method according to claim 8 , further comprising: determining an inventory amount of the material; and determining an inventory amount of the material at the relay point. Information processing device.

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

12. When the ordering plan is adjusted via the ordering plan management screen, the ordering data generation unit In this case, the order data is updated based on the order plan adjusted via the order plan management screen. The information processing apparatus according to claim 11 , wherein the information processing apparatus regenerates the image data.

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

14. The reference number of months input by the user and the reference number of months calculated by the reference number of months calculation unit The user selects the number of base months and the number of base months is used to calculate the order quantity. The information processing apparatus according to claim 1 , further comprising a reference number of months setting unit that sets the reference number of months as a reference number of months.

Images