Egg demand and supply forecasting system

Abstract

To provide a system that enables anyone, even without experience, to easily predict egg production and shipment. [Solution] The egg supply and demand prediction system has an egg supply and demand prediction device (10) connected to it so that it can communicate with it via a network, and the egg prediction device acquires daily production information that can determine the survival rate, egg laying rate, average egg weight of eggs according to the age of egg-laying hens, and the egg laying volume for each size of egg produced, and creates a standard performance model that correlates and determines the survival rate, egg laying rate and average egg weight according to the age of egg-laying hens, and an egg weight table that determines the egg laying rate for each size according to the average egg weight, and can predict the production quantity by size according to the age of egg-laying hens using the standard performance model and the egg weight table, and creates an index category that specifies a calculation method for predicting the shipping quantity according to the size of eggs based on shipping information for a specified period in the past, and can predict the shipping quantity by size according to the scheduled shipping date using the shipping information for the specified period and the index category.

Description

[Technical field]

[0001] The present invention relates to a system for predicting supply and demand of eggs that is expected to be produced and shipped in the future. [Background technology]

[0002] Traditionally, egg production predictions have been based on producers' many years of experience, and egg production performance varies depending on the age, environment, and breed of the layer. For example, in the summer, chickens eat less feed, which leads to a decrease in production volume and size (from large to medium, etc.). Furthermore, egg-laying performance differs depending on the rearing environment of each producer, so egg production predictions are usually handled by experts with many years of experience. In recent years, production farms have become larger, and as a result, there are larger fluctuations, making it difficult to predict egg production based on experience.

[0003] On the other hand, egg shipment forecasts are made by producers who compare sales information for each sales outlet, such as retailers and restaurants, and calculate the necessary quantities based on their many years of experience. Producers often adjust supply and demand to avoid stockouts, which results in excess inventory. When there is a surplus, producers must sell it at a lower price than usual, and in some cases they may be forced to sell it below the production cost.

[0004] As such, currently, egg production and shipping forecasts are made manually by producers, but it is necessary to train experienced people to make long-term predictions, and there is concern that in recent years it is becoming increasingly difficult to comprehensively forecast supply and demand through experience alone. Therefore, if the current situation continues, there is a risk that surplus or shortages will occur, leading to the decline of egg production areas and a drop in demand, so there has been a need to create a system to efficiently forecast egg supply and demand.

[0005] Incidentally, several mechanisms for systematizing product demand and supply management have been proposed (see, for example, Patent Documents 1 to 4). Patent Document 1 makes it possible to adjust supply and demand by determining the planting quantity based on the predicted sales quantity of agricultural products and calculating the predicted harvest quantity based on this planting quantity. Patent Document 2 predicts the demand for similar products based on sales history (sales performance) information of products sold in the past. Patent Document 3 claims that it is possible to grasp demand by having the total amount of agricultural produce to be purchased reserved before the sowing of the produce, and to grasp supply by receiving an order for the desired shipping amount on a daily basis before harvest and shipping, thereby managing the production and distribution of agricultural produce and achieving efficient shipping adjustments. Patent Document 4 identifies the planting period so that the crop to be cultivated can be harvested at the target sales time, and also identifies an index related to the planting volume that will enable the harvest of the crop to reach the target sales value, thereby assisting in the planning of crop cultivation plans.

[0006] However, none of the conventional mechanisms or systems described above are designed to manage supply and demand that involve uncertainties, such as egg production, the size and quantity of which may vary depending on the age of the eggs or the season, or egg shipment, the quantity of which may vary depending on whether or not a sales destination has a sale or event. It is therefore difficult to apply these mechanisms or systems to supply and demand management, such as egg production and shipment forecasts. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Patent No. 6509278 [Patent Document 2] Patent No. 2955081 [Patent Document 3] Japanese Patent Application Publication No. 11-175609 [Patent Document 4] International Publication No. 2015 / 173875 Brochure Summary of the Invention [Problem to be solved by the invention]

[0008] The present invention was made in consideration of the above-mentioned conventional circumstances, and aims to provide a system that allows anyone, even without experience, to easily predict egg production and shipment. [Means for solving the problem]

[0009] In order to achieve the above-mentioned object, a first aspect of the present invention is a system for predicting supply and demand for eggs, comprising: production performance information acquisition means for acquiring daily production information that enables the determination of the survival rate, egg-laying rate, average egg weight of eggs, and egg volume for each size of egg produced according to the age of the egg-laying hens; model creation means for creating a standard performance model that correlates and specifies the survival rate, egg-laying rate, and average egg weight according to the age of the egg-laying hens based on the acquired production information; table creation means for creating an egg weight table that specifies the egg-laying rate for each size according to the average egg weight based on the acquired production information; and production prediction means for outputting supply prediction information that predicts the production quantity by size according to the age of the egg-laying hens based on the standard performance model and the egg weight table.

[0010] A second aspect of the present invention is that in the first aspect, the production performance information acquisition means acquires the production information including the start date of molting induction, and the table creation means further creates a molting induction table based on the acquired production information, specifying information for correcting the survival rate, egg laying rate, and average egg weight of the egg-laying hens according to the number of days after the start of molting induction of the egg-laying hens, and the production prediction means outputs supply prediction information predicting size-specific production quantities according to the age of the egg-laying hens based on the standard performance model, the egg weight table, and the molting induction table.

[0011] A third aspect of the present invention is a supply and demand forecasting system for eggs, comprising: a shipping performance information acquiring means for acquiring past shipping information that enables identification of shipping quantities according to shipping dates for each size of egg; a classification creating means for creating index categories that identify a calculation method for predicting shipping quantities according to egg sizes based on the acquired shipping information for a specified period of time; and a shipping forecasting means for outputting demand forecast information that predicts shipping quantities by size according to scheduled shipping dates based on the shipping information for the specified period of time and the index categories.

[0012] In a fourth aspect of the present invention, a producer terminal used by a producer who raises egg-laying hens to produce eggs, a seller terminal used by a seller who sells the eggs, and a supply and demand prediction device that predicts the production quantity of eggs by size and the shipping quantity of eggs by size are communicably connected via a network, and the producer terminal includes a means for inputting daily production information that can specify the survival rate, egg laying rate, average egg weight of the eggs according to the age of the egg-laying hens, and the egg laying amount by size of the eggs produced, a means for transmitting the input production information to the supply and demand prediction device, and The seller terminal is provided with a means for transmitting a production quantity forecast request for eggs to the supply and demand forecasting device, and a means for receiving supply forecast information from the supply and demand forecasting device, and the seller terminal is provided with a means for inputting past shipping information capable of identifying a shipping quantity according to a shipping date for each size of egg, a means for transmitting the inputted shipping information to the supply and demand forecasting device, a means for transmitting a shipping quantity forecast request for eggs to the supply and demand forecasting device, and a means for receiving demand forecast information from the supply and demand forecasting device, and the supply and demand forecasting device is provided with a production performance information acquisition unit for acquiring the production information from the producer terminal. a model creating means for creating a standard performance model which associates and specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hen based on the acquired production information; a table creating means for creating an egg weight table which specifies the egg laying amount for each size according to the average egg weight based on the production information; and a production prediction means for outputting supply prediction information which predicts the production quantity by size according to the age of the egg-laying hen based on the standard performance model and the egg weight table in response to a request for predicting the production quantity of eggs from the producer terminal, and further comprising: a shipping performance information acquiring means for acquiring the shipping information from the seller terminal; a classification creating means for creating an index classification which specifies a calculation method for predicting the shipping quantity according to the size of the eggs based on the acquired shipping information for a specified period; and a shipping prediction means for outputting demand prediction information which predicts the shipping quantity by size according to the scheduled shipping date based on the shipping information for the specified period and the index classification in response to a request for predicting the shipping quantity of eggs from the seller terminal.

[0013] In a fifth aspect of the present invention, a producer terminal used by a producer who raises egg-laying hens to produce eggs, a seller terminal used by a seller who sells the eggs, and a supply and demand prediction device that predicts the production quantity of eggs by size and the shipping quantity of eggs by size are connected to each other via a network in a manner that allows communication therebetween, and the producer terminal has a means for inputting daily production information that can specify the survival rate, egg laying rate, average egg weight of eggs, and egg laying amount by size of the produced eggs according to the age of the egg-laying hens, a means for transmitting the input production information to the supply and demand prediction device, and a means for transmitting a request for prediction of the production quantity of eggs to the supply and demand prediction device. The seller terminal comprises a means for inputting past shipping information capable of specifying a shipping quantity according to a shipping date for each size of egg, a means for transmitting the inputted shipping information to the supply and demand prediction device, a means for transmitting a request for predicting an egg shipping quantity to the supply and demand prediction device, and a means for receiving demand prediction information from the supply and demand prediction device. The supply and demand prediction device comprises a production record information acquisition means for acquiring the production information from the producer terminal, and a means for receiving a demand forecast information according to the age of the egg-laying hens based on the acquired production information. a model creating means for creating a standard performance model that correlates and specifies survival rate, egg laying rate, and average egg weight; a table creating means for creating an egg weight table that specifies the amount of eggs laid by size according to the average egg weight based on the production information, and a molting induction table that specifies information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens; and a table creating means for creating a standard performance model that correlates and specifies the amount of eggs laid by size according to the average egg weight based on the production information, and a molting induction table that specifies information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens. The system comprises a production forecasting means for outputting supply forecast information that forecasts production quantities by size according to the age of egg-laying hens, a shipping performance information acquiring means for acquiring the shipping information from the seller terminal, a classification creating means for creating an index classification that specifies a calculation method for predicting shipping quantities according to egg sizes based on the acquired shipping information for a specified period, and a shipping forecasting means for outputting demand forecast information that predicts shipping quantities by size according to a scheduled shipping date based on the shipping information for the specified period and the index classification in response to an egg shipping quantity forecast request from the seller terminal.The egg supply and demand forecasting system is characterized by comprising:

[0014] In the first, second, fourth, or fifth aspect, the production performance information acquisition means may acquire the production information by production area, by farm, or by chicken house.

[0015] In addition, when the production performance information acquisition means acquires the production information divided by production area, farm or chicken house, the model creation means may create the standard performance model divided by production area, farm or chicken house, and when the production performance information acquisition means acquires the production information divided by production area, farm or chicken house, the table creation means may create the egg weight table divided by production area, farm or chicken house.

[0016] Furthermore, when the production performance information acquisition means acquires the production information divided by production area, farm, or chicken house, the production prediction means may predict the production quantity by size divided by production area, farm, or chicken house.

[0017] In the third, fourth or fifth aspect, the shipping performance information acquisition means may acquire the shipping information for each shipping destination. In addition, when the shipping record information acquiring means acquires the shipping information for each shipping destination, the category creating means may create the index category for each shipping destination. Furthermore, when the shipping record information acquisition means acquires the shipping information for each shipping destination, the shipping prediction means may predict the number of shipments by size for each shipping destination. Effect of the Invention

[0018] According to the present invention, a system can be provided that can predict egg production and shipment without relying on individual experience or skill. [Brief description of the drawings]

[0019] [Figure 1] 1 is a schematic diagram showing the configuration of an egg supply and demand prediction system according to an embodiment of the present invention. [Diagram 2] 1 is a block diagram showing the hardware configuration of a device constituting an egg supply and demand prediction system according to an embodiment of the present invention. FIG. [Diagram 3] FIG. 2 is a functional block diagram showing an example of a functional configuration of the device. [Figure 4] FIG. 2 is a sequence diagram illustrating the flow of a supply prediction process in the egg supply and demand prediction system according to one embodiment of the present invention. [Diagram 5] FIG. 11 is a sequence diagram illustrating the flow of another supply forecast process in the egg supply and demand forecast system according to an embodiment of the present invention. [Figure 6] FIG. 1 is a schematic diagram showing an example of the configuration of a standard performance model used in an egg supply and demand prediction system according to an embodiment of the present invention. [Figure 7] FIG. 2 is a schematic diagram showing an example of the configuration of an egg weight table used in the egg supply and demand prediction system according to one embodiment of the present invention. [Figure 8] Explaining the supply forecast results of an egg supply and demand forecasting system according to one embodiment of the present invention, (A) is a schematic diagram showing a first stage simulation result 1, and (B) is a schematic diagram showing a second stage simulation result 2. [Figure 9] FIG. 2 is a schematic diagram showing an example of the configuration of a molting induction table used in an egg supply and demand prediction system according to an embodiment of the present invention. [Figure 10] FIG. 3 is a schematic diagram showing a simulation result 3 after molting induction, explaining the supply prediction results in the egg supply and demand prediction system according to one embodiment of the present invention. [Figure 11] 11 is a flowchart showing the operation of a supply forecasting process in the supply and demand forecasting device. [Figure 12] FIG. 2 is a sequence diagram illustrating the flow of a demand forecast process in the egg supply and demand forecast system according to one embodiment of the present invention. [Figure 13]FIG. 2 is a schematic diagram showing an example of the configuration of index categories used in the egg supply and demand prediction system according to one embodiment of the present invention. [Figure 14] 1A is a schematic diagram showing a first shipment result, FIG. 1B is a schematic diagram showing a second shipment result, and FIG. 1C is a schematic diagram showing a third shipment result. [Figure 15] Explaining the results of shipment forecasting in an egg supply and demand forecasting system according to one embodiment of the present invention, (A) is a schematic diagram showing a shipment forecast based on index category 1, (B) is a schematic diagram showing a shipment forecast based on index category 2, and (C) is a schematic diagram showing a shipment forecast based on index category 3. [Figure 16] 4 is a flowchart showing the operation of a demand forecasting process in the supply and demand forecasting device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, an example of an embodiment of the egg demand and supply forecasting system according to the present invention will be described with reference to the drawings. In addition, the embodiments described below are preferred specific examples of the present invention, and therefore various technical limitations are imposed thereon. However, the scope of the present invention is not limited to these embodiments unless otherwise specified in the following description.

[0021] <System configuration> FIG. 1 is a diagram showing an example of the configuration of a chicken egg supply and demand prediction system according to this embodiment. As shown in FIG. 1, the egg supply and demand prediction system in this embodiment is configured by an egg supply and demand prediction device 10, a producer terminal 20, and a seller terminal 30, which are connected via a network N so as to be able to communicate with each other.

[0022] In the following description, the supply and demand prediction device 10 may be referred to as a "server." Furthermore, the network N is not limited to the Internet, but may be a communication network such as a LAN (Local Area Network) or a WAN (Wide Area Network).

[0023] The supply and demand prediction device 10 shown in Figure 1 is a device that stores information received from producer terminal 20 and seller terminal 30, and is used for egg supply and demand prediction processing to predict egg production quantities by egg size and egg shipping quantities by egg size. The supply and demand prediction device 10 has a calculation function and a communication function, and functions as a server in the egg supply and demand prediction system. The supply and demand prediction device 10 of the present embodiment is realized by, for example, a server device or an electronic device such as a personal computer.

[0024] The producer terminal 20 is a computer operated by someone involved in a poultry farming facility that raises egg-laying hens on farms to produce eggs, and is a device with processing and communication functions, and is realized, for example, by a desktop computer, laptop computer, tablet computer, smartphone, etc.

[0025] This producer terminal 20 has at least a means for inputting daily production information that enables specification of, for example, the survival rate according to the age of the laying hens, the egg laying rate, the average egg weight, and the amount of eggs laid for each size of produced eggs, a means for transmitting the input production information to the supply and demand prediction device 10, a means for transmitting a request for predicting the egg production quantity to the supply and demand prediction device 10, and a means for receiving supply prediction information from the supply and demand prediction device 10. This production information may include the start date of molting induction. The production information may also be information that can identify the number of laying hens, their age, and the size, number, and weight of the eggs produced.

[0026] The seller terminal 30 is a computer operated by personnel at an automatic egg sorting and packaging facility such as a GP center (Grading and Packaging Center) where eggs produced on farms are washed, dried, inspected, weighed, and packed, or by personnel at a wholesale facility that sells eggs to customers such as supermarkets and retail stores, and is a device with processing and communication functions, and may be realized, for example, as a desktop computer, laptop computer, tablet computer, smartphone, etc.

[0027] This seller terminal 30 has at least a means for inputting past shipping information that enables identification of the shipping quantity according to the shipping date for each size of egg, a means for transmitting the input shipping information to the supply and demand prediction device 10, a means for transmitting a request for predicting the shipping quantity of eggs to the supply and demand prediction device 10, and a means for receiving demand prediction information from the supply and demand prediction device 10.

[0028] In the example of FIG. 1, only one producer terminal 20 and one seller terminal 30 are shown, but the number of each is not particularly limited and may be more than one.

[0029] <Hardware configuration> FIG. 2 is a block diagram showing a hardware configuration of the supply and demand prediction device 10 according to this embodiment. The supply and demand forecasting device 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a bus 14, an input / output interface 15, an output unit 16, an input unit 17, a memory unit 18, and a communication unit 19.

[0030] The CPU 11 executes various processes according to a program stored in the ROM 12 or a program loaded from the storage unit 18 to the RAM 13. That is, the CPU 11 is a processor that executes various processes according to the program and controls the operation of the entire server. The program is, for example, an operating system (system software) for operating each unit of the supply and demand prediction device 10, or application software for realizing the functional blocks described below.

[0031] The RAM 13 also stores data and the like necessary for the CPU 11 to execute various processes. The CPU 11, the ROM 12, and the RAM 13 are interconnected via a bus 14. To this bus 14, an input / output interface 15 is also connected. An output unit 16, an input unit 17, a storage unit 18, and a communication unit 19 are connected to the input / output interface 15.

[0032] The output unit 16 is composed of a display, a speaker, etc., and outputs various information as images and sounds. The input unit 17 is composed of a keyboard, a mouse, a microphone, a camera, etc., and inputs various information according to the received instruction operation. Note that the output unit 16 and the input unit 17 may be integrated into one unit, for example, by a touch panel.

[0033] The storage unit 18 stores various data necessary for the server 1 to execute information processing, and is configured, for example, with a hard disk, a DRAM (Dynamic Random Access Memory), or the like. The communication unit 19 communicates with other devices via a network N including the Internet.

[0034] The supply and demand prediction device 10 may be provided with a drive to which a removable medium such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory is appropriately attached. The drive allows a program read from the removable medium to be installed in the storage unit 18. Further, the removable media can store various data stored in the storage unit 18 in the same manner as the storage unit 18 .

[0035] The supply and demand prediction device 10 is not limited to a device that operates independently, but may be a distributed server system that operates in cooperation with other devices by communicating via a network N, or a cloud server.

[0036] <Demand and supply forecasting device 10> FIG. 3 is a block diagram illustrating a configuration example of the supply and demand prediction device 10 functioning as a server in this embodiment. The supply and demand prediction device 10 has a production performance information acquisition unit 111, a model creation unit 112, a table creation unit 113, a production prediction unit 114, a shipping performance information acquisition unit 115, a category creation unit 116, and a shipping prediction unit 117. The supply and demand prediction device 10 also has a production information DB 181 and a shipping information DB 182.

[0037] The production performance information acquisition unit 111 is a means having a function of acquiring daily production information that enables identification of the survival rate according to the age of the laying hens, the egg laying rate, the average egg weight of the eggs, and the egg yield for each size of egg produced. The production performance information acquisition unit 111 may acquire, as production information, direct information that can identify each of the survival rate according to the age of the egg-laying hens, the egg-laying rate, the average egg weight of the eggs, and the egg yield for each size of egg produced, or it may acquire indirect information that can identify each of these.

[0038] Specifically, in the case of survival rate according to age of egg-laying hens, indirect information may be obtained, for example, as rearing start date, rearing start information that can identify the number of egg-laying hens at the start of rearing, and excluded number of hens information that can identify the number of egg-laying hens excluded due to accidents, illness, death, etc. That is, the age of egg-laying hens can be identified by counting the number of days elapsed since the rearing start date. In addition, the number of surviving egg-laying hens can be obtained by subtracting the excluded number from the number at the start of rearing, and the survival rate can be calculated by dividing the surviving number by the number at the start of rearing. This makes it possible to identify the survival rate according to age of egg-laying hens.

[0039] In addition, in the case of the egg-laying rate according to the age of the laying hens, for example, production volume information that can identify the total number of eggs produced can be obtained daily as indirect information. That is, the egg-laying rate according to the age of the laying hens can be identified by dividing the production volume by the number of surviving laying hens obtained when calculating the survival rate.

[0040] This production quantity information can also be size-specific production quantity information that specifies the number of eggs produced each day by size. In other words, by adding up the production quantities for each size of eggs, the total number of eggs produced each day (production quantity) can be specified. The egg sizes may be, for example, extra small, SS, S, MS, M, L, LL, extra large, etc. Also, there may be egg sizes that are too small or too large.

[0041] In the case of the average egg weight, for example, production weight information that can specify the total weight of eggs produced each day can be further obtained as indirect information. That is, the average egg weight according to the age of the egg-laying hens can be specified by dividing the production weight by the production quantity (total number) obtained when calculating the egg-laying rate.

[0042] Furthermore, in the case of the egg production volume by size of the produced eggs, for example, size-specific production quantity information that specifies the number of eggs produced by size each day may be further acquired as indirect information. In other words, the egg production rate by size of the produced eggs can be specified by dividing the number of eggs produced by size by the production quantity (total number) acquired when calculating the egg production rate.

[0043] In view of the above, the production performance information acquisition unit 111 may acquire indirect information such as information on the start date of rearing, information on the number of chickens started to be reared, information on the number of chickens removed, information on the production quantity, information on the production weight, and information on the production quantity by size as production information on a daily basis, instead of information that can directly identify the survival rate according to the age of the laying hens, the egg-laying rate, the average egg weight of the eggs, and the egg production volume by size produced.

[0044] The breeding start date information and breeding start number information can be obtained at the start of breeding and do not need to be obtained thereafter. Also, the excluded number of birds information can be obtained only when there is a change in the number of birds being bred and does not need to be obtained daily. Furthermore, the production quantity can be determined by adding up the size-specific production quantity information obtained. Therefore, the indirect information acquired daily as production information can be at least production weight information and size-specific production quantity information. The production information acquired by the production performance information acquisition unit 111 is stored in the production information DB 181.

[0045] The production performance information acquisition unit 111 also has a function of acquiring the production information including the start date of molting induction. Furthermore, the production history information acquisition unit 111 is also a means having a function of acquiring production information divided by place of origin (breeding area), by farm, or by chicken house. That is, the production history information acquisition unit 111 can acquire production information including place of origin information, farm information, and chicken house information, or can acquire information including classification information that can identify the place of origin, farm, and chicken house.

[0046] In this way, by dividing the sources of production information into smaller groups, it becomes possible to create multiple highly accurate standard performance models with finely divided ranges of application in the model creation unit 112, and it becomes possible to create multiple highly accurate egg weight tables with finely divided ranges of application in the table creation unit 113.

[0047] The model creation unit 112 is a means having a function of creating a standard performance model that correlates and specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hens, based on the production information acquired by the production history information acquisition unit 111. When the production information acquired by the production history information acquisition unit 111 is indirect information as described above, the model creation unit 112 specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hens based on the indirect information, and creates a standard performance model.

[0048] In addition, when the production performance information acquisition unit 111 acquires production information divided by production area (breeding region), by farm, or by chicken house, the model creation unit 112 can similarly have a function of creating a standard performance model for each production area, farm, or chicken house. This makes it possible to create highly accurate standard performance models whose scope of application is finely divided by production area, farm, or chicken house.

[0049] The model creation unit 112 may create a standard performance model based on the production information for a fixed period of time acquired by the production performance information acquisition unit 111, and may update the model periodically. This makes it possible to regularly create highly accurate standard performance models that reflect changes in the physical condition and environment of laying hens.

[0050] The table creation unit 113 is a means having a function of creating an egg weight table that specifies the egg-laying rate for each size according to the average egg weight, based on the production information acquired by the production performance information acquisition unit 111. When the production information acquired by the production performance information acquisition unit 111 is indirect information as described above, this table creation unit 113 specifies the egg-laying rate for each size based on the indirect information and creates the egg weight table.

[0051] In addition, when the production information acquired by the production performance information acquisition unit 111 includes the start date of molting induction, the table creation unit 113 also has a function of creating a molting induction table that specifies information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens, based on this production information.

[0052] In addition, when the production performance information acquisition unit 111 acquires production information divided by production area (breeding region), farm, or chicken house, the table creation unit 113 can similarly have a function of creating an egg weight table divided by production area, farm, or chicken house. This makes it possible to create highly accurate egg weight tables whose scope of application is finely divided by production area, farm, or chicken house.

[0053] In addition, like the model creation unit 112, the table creation unit 113 may also create an egg weight table and a molting induction table based on the production information for a fixed period of time acquired by the production performance information acquisition unit 111, and update them periodically. This makes it possible to regularly create highly accurate egg weight tables and molting induction tables that reflect changes in the physical condition and environment of laying hens.

[0054] The production prediction unit 114 is a means having the function of outputting supply prediction information that predicts production quantities by size according to the age of the egg-laying hens based on the standard performance model created by the model creation unit 112 and the egg weight table created by the table creation unit 113. That is, the production prediction unit 114 predicts the number of surviving chickens based on the survival rate of the standard performance model from the number of chickens at the beginning of rearing.Then, it predicts the production (egg) quantity based on the egg-laying rate of the standard performance model from the predicted number of surviving chickens.Then, it refers to an egg weight table based on the average egg weight of the standard performance model, multiplies the predicted production quantity by the egg-laying rate for each size, predicts the production quantity by size, and outputs supply prediction information.

[0055] In addition, the production prediction unit 114 is also a means having the function of outputting supply prediction information that predicts the production quantity by size according to the age of the egg-laying hens based on the standard performance model created by the model creation unit 112, the egg weight table created by the table creation unit 113, and the molting induction table. That is, the production prediction unit 114 predicts the number of surviving birds based on the survival rate of the standard performance model from the number of birds at the beginning of rearing, and further corrects the predicted number of surviving birds to the number of surviving birds after molting induction based on the survival rate correction information of the molting induction table. Next, the production (egg-laying) quantity is predicted from the corrected number of surviving birds based on the egg-laying rate of the standard performance model, and further corrects the predicted production quantity based on the egg-laying rate correction information of the molting induction table to the production (egg-laying) quantity after molting induction. Then, the average egg weight of the standard performance model is added by the average egg weight correction weight of the molting induction table to correct it to the average egg weight after molting induction, and the egg weight table is referred to based on the corrected average egg weight, and the corrected production quantity is multiplied by the egg-laying rate for each size to predict the production quantity by size. Therefore, the production forecasting unit 114 is also capable of dealing with cases where molting induction has been performed.

[0056] In addition, when the production performance information acquisition unit 111 acquires production information divided by production area (breeding region), by farm, or by chicken house, the production prediction unit 114 can similarly have a function of predicting production quantity by size divided by production area, by farm, or by chicken house. The supply forecast information forecasted by the production forecasting unit 114 may be stored in the production information DB 181, for example, by production area, by farm, or by chicken house, or may be stored in a separate database.

[0057] The shipping record information acquisition unit 115 is a means having a function of acquiring past shipping information that can specify the shipping quantity according to the shipping date for each size of egg. The shipping date may include the day of the week. The shipping quantity may be the number of eggs or the number per pack. The shipping record information acquiring unit 115 is also a means having a function of acquiring shipping information for each shipping destination. That is, the shipping record information acquiring unit 115 accepts shipping information including shipping destination information, or including classification information that can identify the shipping destination. The shipping destination information may also include classification information that can identify each store (sales destination). The shipping information acquired by the shipping record information acquiring unit 115 is stored in the shipping information DB 182 .

[0058] The classification creating unit 116 is a means having a function of creating an index classification that specifies a calculation method for predicting the shipping quantity according to the size of eggs based on the acquired shipping information for a predetermined period. The predetermined period can be, for example, the most recent one week, half a month, one month, three months, half a year, or one year. This division creating unit 116 can have a function of creating an index division for each shipping destination in the same way when the shipping record information acquiring unit 115 acquires shipping information for each shipping destination.

[0059] The shipment forecasting unit 117 is a means having the function of outputting demand forecast information that predicts the shipping quantity by size according to future scheduled shipping dates based on the shipping information for a specified period acquired by the shipping performance information acquisition unit 115 and the index classification created by the classification creation unit 116. This shipment prediction unit 117 can have a function of predicting the number of shipments by size for each shipping destination in the same way when the shipping record information acquisition unit 115 acquires shipping information for each shipping destination. The demand forecast information forecasted by the shipment forecasting unit 117 may be stored in the shipment information DB 182, for example, divided by shipping destination, or may be stored in a separate database.

[0060] The production information DB 181 is a database that stores the production information acquired by the production performance information acquisition unit 111, and is a means for storing direct production information such as the survival rate according to the age of the laying hens, the egg laying rate, the average egg weight of the eggs, and the amount of eggs laid by size of the eggs produced, or indirect production information such as the rearing start date information, the number of chickens at the start of rearing information, the number of chickens removed information, production quantity information, production weight information, and production quantity information by size, in association with each day. The production information DB 181 can also store the start date of molting induction. Furthermore, the production information DB 181 may store the production information by place of origin, by farm, or by chicken house.

[0061] The shipping information DB 182 is a database that stores shipping information acquired by the shipping performance information acquisition unit 115, and is a means for associating and storing shipping information such as the shipping date (including the day of the week), shipping destination, and shipping quantity (including the quantity per pack). Furthermore, the shipping information DB 182 may store shipping information separately for each store or sales destination.

[0062] As described above, the supply and demand prediction device 10 of this embodiment functions as a device including a production performance information acquisition unit 111, a model creation unit 112, a table creation unit 113, a production forecasting unit 114, a shipment performance information acquisition unit 115, a category creation unit 116, and a shipment forecasting unit 117 by loading various programs (OS, applications, etc.) stored in the auxiliary storage device into the main storage device and executing them by the CPU 11.

[0063] Next, the process flow of the egg demand and supply prediction system according to one embodiment of the present invention will be described. 4 and 5 are sequence diagrams showing an example of a chicken egg supply and demand forecast process according to an embodiment of the present invention. Fig. 4 explains the flow of the basic egg production process, and Fig. 5 explains the flow of the production process when molting induction is performed.

[0064] First, to enjoy using this system, each user accesses the system's website using the communication functions of the producer terminal 20 and the seller terminal 30 and logs in to the system, thereby enabling the user to carry out tasks using the system.

[0065] The producer terminal 20 then requests the supply and demand prediction device 10 to input production information, thereby accepting (receiving) form information for inputting production information from the supply and demand prediction device 10. In step S301, the producer terminal 20 displays a form screen for inputting production information on a display device (monitor) based on the form information received from the supply and demand forecasting device 10, inputs specified production information, and transmits this production information to the supply and demand forecasting device 10.

[0066] In step S302, the supply and demand prediction device 10 acquires (receives) the production information transmitted from the producer terminal 20.

[0067] In step S303, the producer terminal 20 transmits a request for prediction of the egg production quantity to the supply and demand prediction device 10, inquiring about a prediction of future production of the egg-laying hens being raised. In step S304, the supply and demand prediction device 10 accepts (receives) the production quantity prediction request transmitted from the producer terminal 20.

[0068] Next, in step S305, the supply and demand prediction device 10 identifies the age of the egg-laying hens to be predicted based on a production quantity prediction request from the producer terminal 20, and predicts the production quantity by size according to the requested age based on the standard performance model and egg weight table described below. Then, in step S306, the supply and demand prediction device 10 outputs the predicted production quantities by size according to the age in days as supply prediction information and returns it to the producer terminal 20. After that, in step S307, the producer terminal 20 receives the supply forecast information transmitted from the supply and demand forecasting device 10, and displays it on the display device (monitor).

[0069] In this way, in order to address future concerns and questions such as how many eggs will be produced in the future and what size they will be, this system makes effective use of the production information entered by producers on a daily basis, refers to a standard performance model and egg weight table created based on production information that represents past results, and predicts future production quantities by size according to age based on this standard performance model and egg weight table (i.e., past results).

[0070] In addition, the flow of the supply process when molting induction is carried out in laying hens can be shown in Figure 5. After logging in to this system, in step S311, the producer terminal 20 inputs predetermined production information into the form information received from the supply and demand forecasting device 10 and transmits this production information to the supply and demand forecasting device 10.

[0071] In step S312, the supply and demand prediction device 10 acquires (receives) the production information transmitted from the producer terminal 20.

[0072] Next, in step S313, the supply and demand prediction device 10 creates a molting induction table based on the acquired production information, which specifies information for correcting the survival rate, egg-laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens.

[0073] In step S314, the producer terminal 20 transmits a request for prediction of the egg production quantity to the supply and demand prediction device 10, inquiring about a prediction of future production of the egg-laying hens being raised. In step S315, the supply and demand prediction device 10 accepts (receives) the production quantity prediction request transmitted from the producer terminal 20.

[0074] Next, in step S316, the supply and demand prediction device 10 identifies the age of the egg-laying hens to be predicted based on a production quantity prediction request from the producer terminal 20, and predicts the production quantity by size according to the requested age based on the standard performance model and egg weight table described below. Then, in step S317, the supply and demand prediction device 10 outputs the predicted production quantities by size according to the age in days as supply prediction information and returns it to the producer terminal 20. Thereafter, in step S318, the producer terminal 20 receives the supply forecast information transmitted from the supply and demand forecasting device 10, and displays it on the display device (monitor).

[0075] In this way, this system can also handle cases where molting induction has been performed, and in order to address future concerns and questions such as how many eggs the laying hens will produce after molting induction and what size they will be, the system predicts future production quantities by size according to age based on a standard performance model created from production information entered daily by producers, an egg weight table, and a molting induction table (i.e., past performance).

[0076] Here, the standard performance model used by the supply and demand prediction device 10 in the above-mentioned steps S305 and S316 can be shown in FIG. 6, for example. FIG. 6 is a schematic diagram showing an example of the configuration of a standard performance model used in the egg supply and demand prediction system according to one embodiment of the present invention. In FIG. 6, the standard performance model is shown as storing specific associations between survival rate, egg production rate, and average egg weight according to the age of the layer.

[0077] Survival rate is the ratio of the number of surviving egg-laying hens to the number of egg-laying hens at the start of rearing, in other words, the ratio when the number of egg-laying hens at the start of rearing is set to 1. Specifically, if there are 1,000 hens at the start of rearing and 999 are alive on the 133rd day, the survival rate is shown as "0.999." The egg-laying rate is expressed as a percentage (%), which is the ratio of the number of eggs produced to the number of (living) egg-laying hens being raised. For example, if there are 999 living egg-laying hens on the 133rd day of age and the number of eggs produced is 33, the egg-laying rate is shown as "3 (%)." The average egg weight indicates the average weight (g) of each egg produced. For example, if the number of eggs produced on the 133rd day of age is 33 and the total weight (weight of all eggs produced) is 1,380g, the average egg weight is shown as "41.8 (g)".

[0078] In addition, in the above-mentioned steps S305 and S316, the egg weight table used by the supply and demand prediction device 10 can be, for example, as shown in FIG. FIG. 7 is a schematic diagram showing an example of the configuration of an egg weight table used in the egg demand and supply prediction system according to one embodiment of the present invention. In FIG. 7, the egg weight table is shown as storing the average egg weight in association with the egg laying rate for each size of produced egg so that it can be determined.

[0079] The egg production rate by size is expressed as a percentage (%) of the number of eggs of the corresponding size relative to the total number of eggs produced. Specifically, if the average egg weight of the eggs produced is 41.8, and 95 extra small eggs, 150 SS eggs, 50 S eggs, 3 MS eggs, 1 M egg, 1 L egg, 0 LL eggs, and 0 extra large eggs are produced, the egg production rates by size are expressed as extra small [32(%)], SS "50(%)", S "17(%)", MS "1(%)", M "0(%)", L "0(%)", LL "0(%)", and extra large "0(%)".

[0080] In addition, in the above-mentioned steps S305 and S316, the production quantities by size predicted by the supply and demand prediction device 10 can be shown in, for example, FIG. FIG. 8 illustrates the supply forecast results of the egg supply and demand forecast system according to one embodiment of the present invention, where (A) is a schematic diagram showing the first stage simulation result 1, and (B) is a schematic diagram showing the second stage simulation result 2.

[0081] For example, when the supply and demand prediction device 10 receives a request from the producer terminal 20 to predict the production volume 132 days after the start of rearing (the egg-laying hens' age in days is 1), it first identifies the survival rate at 133, which is the egg-laying hens' age in days 132 after 132 days (1 + 132), based on the standard performance model. From the standard performance model, it is found that the survival rate of egg-laying hens at an age of 133 days is "0.999."

[0082] Next, the producer is identified based on the login information from the producer terminal 20, the number of egg-laying hens being raised by the producer is identified, and the number of surviving egg-laying hens at the age of 133 days is calculated. For example, if the producer was raising 100,000 egg-laying hens at the start of rearing, by multiplying the survival rate of 0.999 identified by the standard performance model, the number of surviving egg-laying hens at the age of 133 days can be predicted (calculated) to be "99,900," as shown in the field marked with symbol I in Fig. 8(A).

[0083] Next, the egg-laying rate of the layer hens when the age is 133 days is determined based on the standard performance model. From the standard performance model, it is found that the egg-laying rate of the layer hens when the age is 133 days is "3(%)". Then, by multiplying the previously calculated number of surviving layer hens when the age is 133 days, 99,900, by the egg-laying rate of 3(%) determined from the standard performance model, the number of eggs laid by the layer hens when the age is 133 days can be predicted (calculated) to be "2,997 (eggs)", as shown in the field marked with symbol II in FIG. 8(A).

[0084] Also, based on the standard performance model, the average egg weight of layer hens when the day age is 133 is specified. From the standard performance model, it is found that the average egg weight of layer hens when the day age is 133 is 41.8 (g). Furthermore, based on the egg weight table, the egg laying rate for each egg size when the average egg weight is 41.8 is specified. From the egg weight table, it is found that the egg laying rate for each egg size when the average egg weight is 41.8 is 32 (%) for very small, 50 (%) for SS, 17 (%) for S, 1 (%) for MS, and 0 (%) for M, L, LL, and extra large.

[0085] Then, by multiplying the number of eggs laid by the layer hen at 133 days of age (2,997) calculated earlier by the egg-laying rate for each size determined from the egg weight table, we can predict (calculate) the number of eggs laid by the layer hen at 133 days of age for each size as follows, as shown in record III in Figure 8(B) : very small: 959 eggs, SS: 1,499 eggs, S: 509 eggs, MS: 30 eggs, and M, L, LL, and extra large: 0 eggs each.

[0086] Therefore, the supply and demand prediction device 10 outputs the above-mentioned predicted numerical values ​​for each size as supply prediction information indicating the production volume predicted 132 days from now, and transmits (responds) it to the producer terminal 20.

[0087] In step S313 described above, the molting guidance table created by the supply and demand prediction device 10 can be, for example, as shown in FIG. FIG. 9 is a schematic diagram showing an example of the configuration of a molting induction table used in an egg supply and demand prediction system according to one embodiment of the present invention. In FIG. 9, the molting induction table is shown as storing the survival rate correction %, egg-laying rate correction %, and average egg weight correction % in association with the number of days after molting induction so that they can be specified.

[0088] The survival rate correction percentage indicates the corrected percentage of the number of surviving egg-laying hens after molting induction, and indicates a value that corrects the number of egg-laying hens obtained by multiplying the survival rate specified by the standard performance model shown in Figure 6 to fit the egg-laying hens after molting induction. In Figure 9, the survival rate correction value on the first day (day 1) after molting induction is shown as "100(%)." In other words, this shows that the number of laying hens obtained by multiplying the survival rate specified by the standard performance model shown in Figure 6 can be applied as is (100%).

[0089] The egg-laying rate correction percentage indicates the correction rate of the quantity (number) of eggs produced after molting induction as a percentage (%), and indicates the value by which the number of eggs produced, obtained by multiplying the egg-laying rate specified by the standard performance model shown in Figure 6, is corrected to suit the egg-laying hens after molting induction. In Figure 9, the egg production rate correction value on the first day (day 1) after molting induction is shown as "3 (%)." In other words, this indicates that the number of eggs obtained by multiplying the egg production rate specified by the standard performance model shown in Figure 6 is further multiplied by 3%.

[0090] In addition, the average egg weight correction % indicates the correction rate, expressed as a percentage (%), of the average weight (g) per egg produced by layer hens after molting induction, and indicates the value used to correct the average egg weight of eggs produced after molting induction to suit layer hens after molting induction. In Figure 9, the average egg weight correction value on the first day (day 1) after molting induction is shown as "3.5 (%)." In other words, this shows that an additional 3.5% of the weight is added to the average egg weight determined based on the age of the layer in days in the standard performance model shown in Figure 6.

[0091] A specific method for applying the survival rate correction %, egg-laying rate correction %, and average egg weight correction % shown in the above-mentioned molting induction table can be shown in FIG. FIG. 10 is a schematic diagram showing a simulation result 3 after molting induction, which explains the supply prediction result in the egg supply and demand prediction system according to one embodiment of the present invention.

[0092] For example, if molting induction is performed when the egg-laying hens are 500 days old and the production quantity of egg-laying hens on the first day (first day) after molting induction is predicted, the producer is identified based on the login information from the producer terminal 20, and the number of egg-laying hens being raised by the producer is identified. The number of surviving egg-laying hens at the age of 500 days is calculated by multiplying the identified survival rate by the standard performance model. Furthermore, to correct the number of surviving egg-laying hens when the age is 500 days, the survival rate correction value for the first day (day 1) after molting induction is specified. From the molting induction table, it is found that the survival rate correction value for day 1 of molting induction is "100(%)."

[0093] For example, if the number of surviving egg-laying hens of the producer in question, obtained by multiplying the survival rate at an age of 500 determined from the standard performance model, is 94,884 (birds), then by multiplying this by the survival rate correction value of 100 (%) determined from the molting induction table, the number of surviving egg-laying hens on the 500th day after the start of rearing is applied as is (100%), as shown in field IV in Figure 10, and the corrected number of surviving egg-laying hens can be predicted (calculated) to be "94,884 (birds)."

[0094] Next, specify the egg-laying rate correction value for the first day after molting induction (day 1). From the molting induction table, it is found that the egg-laying rate correction value for the first day of molting induction is "3 (%)." For example, if the egg-laying rate of layer hens at an age of 500 days, determined based on the standard performance model, is 82.4, then by multiplying the previously calculated number of surviving layer hens at an age of 500 (94,884) by the egg-laying rate of 82.4 (%) determined from the standard performance model, the number of eggs laid by layer hens at an age of 500 days can be predicted (calculated) to be "78,184 (eggs)", as shown in the field marked with symbol V in Figure 10.

[0095] Furthermore, by multiplying the predicted number of eggs laid by the layer hen, 78,184, by the egg-laying rate correction value of 3 (%) determined from the molting induction table, the corrected number of eggs laid by the layer hen at the age of 500 days can be predicted (calculated) to be “2,346 (eggs),” as shown in the field marked with symbol VI in Figure 10.

[0096] In addition, the average egg weight correction value on the first day (day 1) after molting induction is specified. From the molting induction table, it is found that the average egg weight correction value on day 1 of molting induction is "3.5 (%)." For example, if the average egg weight at 500 days old determined from the standard performance model is 66.4 (g), add the average egg weight correction value of 3.5 (%) determined from the molting induction table to this. In other words, by adding 2.3 to 66.4, the corrected average egg weight can be predicted (calculated) to be "68.7 (g)".

[0097] After that, although not shown in the figure, similarly to the above, the egg-laying rate for each size of egg when the average egg weight is 68.7 is determined based on the egg weight table, and the number of eggs laid by each size of egg-laying hen when the age is 500 days, determined earlier as 2,346, is multiplied by the egg-laying rate for each size determined from the egg weight table, thereby making it possible to predict (calculate) the number of eggs laid by each size of egg-laying hen when the age is 500 days.

[0098] Next, a detailed flow of egg supply and demand prediction processing in the supply and demand prediction device 10 will be described. FIG. 11 is a flowchart illustrating an example of the operation of the supply prediction process in the supply and demand prediction device.

[0099] In step S401, the production performance information acquisition unit 111 performs a process of determining whether or not it has acquired (received) production information transmitted from the producer terminal 20. If the production performance information acquisition unit 111 has acquired the production information (YES in S401), it proceeds to step S402, and if not (NO in S401), it proceeds to step S404.

[0100] Next, in step S402, table creation unit 113 performs a process of determining whether or not a molting induction start date is included in the production information acquired by production performance information acquisition unit 111. If table creation unit 113 determines that the production information includes a molting induction start date (YES in S402), it proceeds to step S403, and if not (NO in S402), the operation of supply and demand prediction device 10 then ends (END).

[0101] In step S403, the table creation unit 113 performs processing to further create a molting induction table that specifies information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens, based on the production information including the molting induction start date acquired by the production performance information acquisition unit 111. Thereafter, the operation of the supply and demand prediction device 10 ends (END).

[0102] In step S404, the production forecasting unit 114 performs a process of determining whether or not a production quantity forecast request for eggs has been accepted (received). If the production forecasting unit 114 accepts a production quantity forecast request (YES in S404), the process proceeds to step S405, and if not (NO in S404), the operation of the supply and demand forecasting device 10 ends (END).

[0103] In step S405, the production prediction unit 114 performs a process of predicting the size-specific production quantity according to the age of the layer-laying hens based on the standard performance model and the egg weight table. In addition, when the production quantity prediction request corresponds to after molting induction, the production prediction unit 114 performs a process of predicting the size-specific production quantity according to the age of the layer-laying hens based on the standard performance model, the egg weight table, and the molting induction table.

[0104] Then, in step S406, the production forecasting unit 114 performs a process of outputting the predicted size-specific production quantities according to the age of the laying hens as supply forecast information (returning it to the producer terminal 20). Thereafter, the operation of the supply and demand prediction device 10 ends (END).

[0105] Next, another process flow of the egg demand and supply prediction system according to one embodiment of the present invention will be described. FIG. 12 is a sequence diagram illustrating the flow of egg shipping processing as the flow of demand prediction processing in the egg supply and demand prediction system according to one embodiment of the present invention.

[0106] The seller terminal 30 accepts (receives) form information for inputting shipping information from the supply and demand prediction device 10 by the seller requesting the supply and demand prediction device 10 to input shipping information.

[0107] In step S501, the seller terminal 30 displays a form screen for inputting shipping information on a display device (monitor) based on the form information received from the supply and demand forecasting device 10, inputs the specified shipping information, and transmits this shipping information to the supply and demand forecasting device 10.

[0108] In step S502, the supply and demand prediction device 10 acquires (receives) the shipping information transmitted from the seller terminal 30. Next, in step S503, the supply and demand prediction device 10 creates an index category that specifies a calculation method for predicting the shipping quantity according to the size of eggs, based on the acquired shipping information for a predetermined period.

[0109] In step S504, the seller terminal 30 transmits to the supply and demand prediction device 10 a request for prediction of egg shipping quantities, inquiring about size-specific shipping quantities according to future scheduled shipping dates. In step S505, the supply and demand prediction device 10 accepts (receives) the shipping quantity prediction request transmitted from the seller terminal 30.

[0110] Next, in step S506, in response to a shipping quantity forecast request from the seller terminal 30, the supply and demand forecasting device 10 predicts the size-specific shipping quantity for the requested future shipping date based on the shipping information for a specified period and the index classification. Then, in step S507, the supply and demand prediction device 10 outputs the predicted demand prediction information and returns it to the seller terminal 30. Thereafter, in step S508, the seller terminal 30 receives the demand forecast information transmitted from the supply and demand forecasting device 10, and displays it on a display device (monitor).

[0111] In this way, in order to address future concerns and questions such as what the future egg shipping quantities will be and what the sizes will be, this system effectively utilizes the shipping information entered by sellers on a daily basis to create index categories from shipping information that is past performance, and predicts shipping quantities by size according to future shipping dates based on the shipping information for a specified period (i.e., past performance) and index categories.

[0112] Here, in the above-mentioned step S503, the index divisions created by the supply and demand prediction device 10 can be, for example, as shown in FIG. FIG. 13 is a schematic diagram showing an example of the configuration of index categories used in a chicken egg supply and demand prediction system according to one embodiment of the present invention. In Figure 13, the index categories are shown to be stored in association with production area information and farm information that identify the producer, customer information that identifies the sales destination, and forecast calculation category information that serves as an index category for each size of egg that identifies the product.

[0113] This index classification can be created, for example, from the shipping record shown in FIG. Figure 14 explains shipping information for a specified period obtained by an egg supply and demand prediction system according to one embodiment of the present invention, where Figure 14(A) is a schematic diagram showing a first shipping result, Figure 14(B) is a schematic diagram showing a second shipping result, and Figure 14(C) is a schematic diagram showing a third shipping result.

[0114] Figure 14(A) shows the actual shipping quantity for a specified period of small size eggs, for a period of seven days (one week), as follows: Saturday, June 1, 2024, 150; Sunday, June 2, 2024, 100; Monday, June 3, 2024, 100; Tuesday, June 4, 2024, 100; Wednesday, June 5, 2024, 150; Thursday, June 6, 2024, 100; and Friday, June 7, 2024, 100.

[0115] In the index classification shown in Figure 13, the forecast calculation category for when shipments occur every day for seven days like this is set to "1", and the calculation method is to predict (calculate) the daily shipment quantity for the next seven days as the average of the total amount over the seven days.

[0116] In addition, Figure 14 (B) shows the actual shipping quantity for a specified period of medium-sized eggs, with the shipping quantity on Saturday, June 1, 2024 being 200, the shipping quantity on Sunday, June 2, 2024 being 0, the shipping quantity on Monday, June 3, 2024 being 200, the shipping quantity on Tuesday, June 4, 2024 being 200, the shipping quantity on Wednesday, June 5, 2024 being 200, the shipping quantity on Thursday, June 6, 2024 being 200, and the shipping quantity on Friday, June 7, 2024 being 200, for a period of 7 days (one week).

[0117] In the index classification shown in Figure 13, when shipments occur for 6 days out of 7 days (one week), excluding one specific day or day of the week, the forecast calculation classification is "2," and the calculation method is to predict (calculate) the shipment quantity for the next 6 days, excluding that specific day or day of the week, by averaging the total quantity for the 6 days over the 6 days.

[0118] Furthermore, Figure 14(C) shows the actual shipping quantity for a specified period of MIX-sized eggs, with the shipping quantity on Saturday, June 1, 2024 being 0, the shipping quantity on Sunday, June 2, 2024 being 0, the shipping quantity on Monday, June 3, 2024 being 500, the shipping quantity on Tuesday, June 4, 2024 being 0, the shipping quantity on Wednesday, June 5, 2024 being 600, the shipping quantity on Thursday, June 6, 2024 being 0, and the shipping quantity on Friday, June 7, 2024 being 0, for a period of 7 days (one week).

[0119] In the index classification shown in Figure 13, the forecast calculation classification for cases in which shipments occur only on specific days or days of the week is "3," and the calculation method is to predict (calculate) the quantity that has already been shipped on a future day or day of the week that corresponds to the day or day on which shipments have already been shipped.

[0120] In step S504 described above, the size-specific shipping quantities corresponding to future shipping dates predicted by the supply and demand prediction device 10 can be shown in FIG. 15, for example. FIG. 15 explains the results of shipment forecasting in an egg supply and demand forecasting system according to one embodiment of the present invention, where (A) is a schematic diagram showing a shipment forecast based on index category 1, (B) is a schematic diagram showing a shipment forecast based on index category 2, and (C) is a schematic diagram showing a shipment forecast based on index category 3.

[0121] The size-specific shipping quantities according to future shipping dates are predicted based on the shipping information and index categories for a predetermined period, as described above. For example, when a forecast of the shipping quantity of small size eggs for the next seven days (one week) is requested from the seller terminal 30, the supply and demand prediction device 10 identifies the forecast calculation category for small size eggs based on the index categories shown in Fig. 13. From the index categories, it is found that the forecast calculation category for small size eggs is "1".

[0122] Here, if the shipping record for a specified period of S-sized eggs is 800 for a seven-day period, as shown in FIG. 14(A), the average shipping quantity over the seven days, 114, can be predicted (calculated) as the shipping quantity for each day for the next seven days. Specifically, the shipping quantity for Saturday, June 8, 2024 is 114, the shipping quantity for Sunday, June 9, 2024 is 114, the shipping quantity for Monday, June 10, 2024 is 114, the shipping quantity for Tuesday, June 11, 2024 is 114, the shipping quantity for Wednesday, June 12, 2024 is 114, the shipping quantity for Thursday, June 13, 2024 is 114, and the shipping quantity for Friday, June 14, 2024 is 114. The shipping forecast for the next seven days (one week) is shown.

[0123] Also, for example, when the supply and demand prediction device 10 receives a request from the seller terminal 30 to predict the shipping quantity of medium-sized eggs for the next seven days (one week), the device specifies the prediction calculation category for medium-sized eggs based on the index categories shown in Fig. 13. From the index categories, it is clear that the prediction calculation category for medium-sized eggs is "2".

[0124] Here, if the actual shipping record of medium-sized eggs for a specified period is 1,200 for 6 days excluding a specific day or day of the week out of 7 days (one week) as shown in FIG. 14(B), the average quantity over 6 days, 200, can be predicted (calculated) as the shipping quantity for the next 6 days excluding a specific day or day of the week out of the next 7 days (one week). Specifically, the shipping quantity for Saturday, June 8, 2024 is 200, Sunday, June 9, 2024 is 0, Monday, June 10, 2024 is 200, Tuesday, June 11, 2024 is 200, Wednesday, June 12, 2024 is 200, Thursday, June 13, 2024 is 200, and Friday, June 14, 2024 is 200. The shipping forecast for the next 7 days (one week) is shown.

[0125] Furthermore, for example, when the supply and demand prediction device 10 receives a request from the seller terminal 30 to predict the shipping quantity of MIX size eggs for the next 7 days (one week), the device specifies the prediction calculation category for MIX size eggs based on the index categories shown in Fig. 13. From the index categories, it is clear that the prediction calculation category for MIX size eggs is "3."

[0126] Here, if the actual shipping records for mix-sized eggs for a specified period include shipments only on specific days or weeks out of a seven-day period (week), as shown in Figure 14(C), the quantities that have been shipped can be predicted (calculated) for future days or weeks that correspond to the days or weeks on which shipments have been made. Specifically, if the shipment quantity on Monday, June 3, 2024 is 500, the shipment quantity on Wednesday, June 5, 2024 is 600, and the shipping end quantity on other days and days of the week is 0, then the shipment quantity on Saturday, June 8, 2024 will be 0, the shipment quantity on Sunday, June 9, 2024 will be 0, the shipment quantity on Monday, June 10, 2024 will be 500, the shipment quantity on Tuesday, June 11, 2024 will be 0, the shipment quantity on Wednesday, June 12, 2024 will be 600, the shipment quantity on Thursday, June 13, 2024 will be 0, and the shipment quantity on Friday, June 13, 2024 will be 0. This shows the shipment forecast for the next 7 days (one week).

[0127] Next, a detailed flow of another egg supply and demand prediction process in the supply and demand prediction device 10 will be described. FIG. 16 is a flowchart illustrating an example of the operation of the shipment forecasting process in the supply and demand forecasting device.

[0128] In step S601, the shipping performance information acquisition unit 115 performs processing to determine whether or not it has acquired (received) shipping information transmitted from the seller terminal 30. If the shipping performance information acquisition unit 115 has acquired shipping information (YES in S601), the process proceeds to step S602, and if not (NO in S601), the process proceeds to step S603. In step S602, the category creation unit 116 performs a process of creating an index category that specifies a calculation method for predicting the shipping quantity according to the size of eggs, based on the shipping information for a specified period acquired by the shipping performance information acquisition unit 115. Thereafter, the operation of the supply and demand prediction device 10 ends (END).

[0129] In step S603, the shipment prediction unit 117 performs a process of determining whether or not a shipment quantity prediction request for eggs has been accepted (received). If the shipment prediction unit 117 accepts a shipment quantity prediction request (YES in S603), the process proceeds to step S604, and if not (NO in S603), the operation of the supply and demand prediction device 10 then ends (END). In step S604, the shipment prediction unit 117 performs a process of predicting the size-specific shipment quantity according to the scheduled shipping date, based on the shipping information for a predetermined period and the index classification.

[0130] Then, in step S605, the shipment forecasting unit 117 performs processing to output the size-specific shipping quantities corresponding to the forecasted scheduled shipping dates as demand forecast information (to return to the seller terminal 30). Thereafter, the operation of the supply and demand prediction device 10 ends (END).

[0131] As described above, according to this embodiment, not only can egg supply and demand predictions be made by anyone, anywhere, at any time, but the results can also be visualized as specific numerical values, such as production quantities and shipping quantities by size. Therefore, even if producers have overproduction, they can reduce low-priced sales by checking future production forecasts. This will lead to strengthening the foundation of the domestic poultry industry and solving the labor shortage. On the other hand, sellers can predict shipments by checking the production areas and quantities that can be handled, even when they receive sales information from their retailers on Saturdays, Sundays, or at night, leading to a stable supply of eggs and preventing lost sales opportunities. Furthermore, supply and demand forecasts are made based on the performance of each production area (region), farm, and chicken coop, making them more accurate and in line with actual conditions.

[0132] The above-described series of processes is merely an example and is not particularly limited. In other words, it is sufficient that the information processing system is provided with a function capable of executing the above-mentioned series of processes as a whole, and the type of functional block used to realize this function is not limited to the above example.

[0133] Although one embodiment of the present invention has been described above, the above-described embodiment is merely an example for facilitating understanding of the present invention and is not intended to limit the present invention. Furthermore, the present invention is not limited to the above-described embodiment, and any modifications, improvements, etc. that can achieve the object of the present invention are included in the present invention. [Industrial Applicability]

[0134] This invention is expected to be useful as a supply and demand forecasting system that not only enables producers to use production history information to predict production quantities by size according to the age of egg-laying hens in days, separated by production area, farm, or chicken coop, and enables sellers to use sales history information to predict shipping numbers by size for each shipping destination, including stores (sales destinations), but also enables sellers to propose shipping quantities by size in response to supply forecast information and producers to adjust production quantities by size in response to demand forecast information, by centralizing and managing production history information and sales history information. [Explanation of symbols]

[0135] 10 Demand forecasting device (server) 20 Producer terminal 30 Merchant Terminal 111 Production performance information acquisition department 112 Model Creation Department 113 Table Creation Department 114 Production Forecast Department 115 Shipping Record Information Acquisition Department 116 Classification section 117 Shipping Forecast Department 181 Production Information DB (Database) 182 Shipping information DB (database)

Claims

1. a production performance information acquiring means for acquiring daily production information that can specify the survival rate, egg laying rate, average egg weight, and egg yield for each size of produced egg according to the age of the egg-laying hens; A model creation means for creating a standard performance model that correlates and specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hens based on the acquired production information; A table creation means for creating an egg weight table that specifies egg laying rates for each size according to average egg weight based on the acquired production information; a production forecasting means for outputting supply forecast information that predicts the production quantity by size according to the age of the egg-laying hens based on the standard performance model and the egg weight table; A system for predicting supply and demand of eggs, comprising:

2. The production performance information acquisition means acquires the production information including a molting induction start date, The table creation means further creates a molting induction table that specifies information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens, based on the acquired production information; The production forecasting means outputs supply forecast information that predicts the production quantity by size according to the age of the egg-laying hens based on the standard performance model, the egg weight table, and the molting induction table.

2. The egg demand and supply forecasting system according to claim 1 .

3. A shipping record information acquisition means for acquiring past shipping information that can identify the shipping quantity according to the shipping date for each size of egg; A classification creating means for creating an index classification that identifies a calculation method for predicting a shipping quantity according to the size of eggs based on the acquired shipping information for a predetermined period of time; a shipment forecasting means for outputting demand forecast information that forecasts a size-based shipment quantity according to a scheduled shipping date based on the shipping information for the predetermined period and the index category; A system for predicting supply and demand of eggs, comprising:

4. A producer terminal used by a producer who raises egg-laying hens to produce eggs, a seller terminal used by a seller who sells eggs, and a supply and demand prediction device that predicts the production quantity of eggs by size and the shipping quantity of eggs by size are communicatively connected via a network, The producer terminal, A means for inputting daily production information that allows the determination of the survival rate, egg laying rate, average egg weight, and egg yield for each size of egg produced according to the age of the egg-laying hens; A means for transmitting the input production information to the supply and demand prediction device; A means for transmitting a request for forecasting an egg production quantity to the supply and demand forecasting device; A means for receiving supply forecast information from the supply and demand forecasting device; Equipped with The seller terminal is A means for inputting past shipping information that allows identification of shipping quantities according to shipping dates for each size of eggs; A means for transmitting the input shipping information to the supply and demand prediction device; A means for transmitting a request for forecasting a shipping quantity of eggs to the supply and demand forecasting device; A means for receiving demand forecast information from the supply and demand forecasting device; Equipped with The supply and demand prediction device includes: a production performance information acquiring means for acquiring the production information from the producer terminal; A model creation means for creating a standard performance model that correlates and specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hens based on the acquired production information; a table creation means for creating an egg weight table that identifies the amount of eggs laid by size according to the average egg weight based on the production information; a production forecasting means for outputting supply forecast information that predicts the production quantity by size according to the age of the egg-laying hens based on the standard performance model and the egg weight table in response to a request for forecasting the production quantity of eggs from the producer terminal; In addition to providing a shipping record information acquiring means for acquiring the shipping information from the seller terminal; A classification creating means for creating an index classification that identifies a calculation method for predicting a shipping quantity according to the size of eggs based on the acquired shipping information for a predetermined period of time; a shipment forecasting means for outputting demand forecast information that predicts the number of eggs to be shipped by size according to a scheduled shipping date based on the shipping information for the predetermined period and the index classification in response to a request for forecasting the number of eggs to be shipped from the seller terminal; Equipped with A system for predicting supply and demand for eggs.

5. A producer terminal used by a producer who raises egg-laying hens to produce eggs, a seller terminal used by a seller who sells eggs, and a supply and demand prediction device that predicts the production quantity of eggs by size and the shipping quantity of eggs by size are communicatively connected via a network, The producer terminal, A means for inputting daily production information that allows the determination of the survival rate, egg laying rate, average egg weight, and egg yield for each size of egg produced according to the age of the egg-laying hens; A means for transmitting the input production information to the supply and demand prediction device; A means for transmitting a request for forecasting an egg production quantity to the supply and demand forecasting device; A means for receiving supply forecast information from the supply and demand forecasting device; Equipped with The seller terminal is A means for inputting past shipping information that allows identification of shipping quantities according to shipping dates for each size of eggs; A means for transmitting the input shipping information to the supply and demand prediction device; A means for transmitting a request for forecasting a shipping quantity of eggs to the supply and demand forecasting device; A means for receiving demand forecast information from the supply and demand forecasting device; Equipped with The supply and demand prediction device includes: a production performance information acquiring means for acquiring the production information from the producer terminal; A model creation means for creating a standard performance model that correlates and specifies the survival rate, egg laying rate, and average egg weight according to the age of the egg-laying hens based on the acquired production information; a table creating means for creating an egg weight table for specifying the amount of eggs laid by size according to the average egg weight based on the production information, and for creating a molting induction table for specifying information for correcting the survival rate, egg laying rate, and average egg weight of the layer hens according to the number of days after the start of molting induction of the layer hens; a production forecasting means for outputting supply forecast information that predicts the size-based production quantity according to the age of egg-laying hens based on the standard performance model, the egg weight table, and the molting induction table in response to a request for forecasting the production quantity of eggs from the producer terminal; In addition to providing a shipping record information acquiring means for acquiring the shipping information from the seller terminal; A classification creating means for creating an index classification that identifies a calculation method for predicting a shipping quantity according to the size of eggs based on the acquired shipping information for a predetermined period of time; a shipment forecasting means for outputting demand forecast information that predicts the number of eggs to be shipped by size according to a scheduled shipping date based on the shipping information for the predetermined period and the index classification in response to a request for forecasting the number of eggs to be shipped from the seller terminal; Equipped with A system for predicting supply and demand for eggs.

6. 6. The system for predicting supply and demand for eggs according to claim 1, wherein the production performance information acquisition means acquires the production information by production area, by farm, or by chicken house.

7. 7. The egg supply and demand forecasting system according to claim 6, wherein the model creation means creates the standard performance model for each production area, each farm, or each chicken house.

8. 7. The system for predicting supply and demand for eggs according to claim 6, wherein the table creating means creates the egg weight table separately for each producing area, each farm, or each chicken house.

9. 7. The system for predicting supply and demand for eggs according to claim 6, wherein the production forecasting means forecasts the size-specific production quantities by production area, by farm, or by chicken house.

10. 6. The system for predicting supply and demand for eggs according to claim 3, wherein the shipping performance information acquisition means acquires the shipping information for each shipping destination.

11. 11. The system for predicting supply and demand of eggs according to claim 10, wherein the classification creating means creates the index classification for each shipping destination.

12. 11. The system for predicting supply and demand of eggs according to claim 10, wherein the shipping prediction means predicts the number of eggs to be shipped by size for each shipping destination.

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