How to automatically order ingredients

Abstract

To provide an automatic ordering method that can reduce the risk of waste and opportunity loss when food ingredients are ordered under constraints at restaurants. [Solution] A method for automatically ordering products from a restaurant in a system, in which a control unit of a server terminal references store data for the restaurant stored in a memory unit of the server terminal, references ordering constraint data for the product stored in the memory unit, and makes an ordering suggestion for the product from the restaurant based on the store data and the ordering constraint data.

Description

[Technical Field]

[0001] The present invention relates to an automatic ordering method under ordering constraints in a restaurant. [Background technology]

[0002] Traditionally, when ordering in restaurant operations, there have been situations where ordering restrictions exist that combine multiple products.Specifically, there are situations where "the total number of regular noodles and individual serving noodles must be a multiple of 90" or "orders to specific stores must be over 5,000 yen."However, such restrictions make ordering operations more complicated, increasing the burden of ordering work and also increasing the risk of waste and opportunity loss.

[0003] For example, in order to reduce waste, a method is disclosed in which, as shown in the technique disclosed in Patent Document 1, order conditions such as the number of order lots and frequency are adjusted based on a sales plan. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-182990 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the technology disclosed in Patent Document 1 adjusts orders based on sales plans, so it is still difficult to flexibly adjust order quantities within ordering constraints.

[0006] Therefore, an object of the present invention is to provide an ordering method that can reduce the risk of waste and opportunity loss when food ingredients and other items are ordered under constraints in restaurants. [Means for solving the problem]

[0007] In one aspect of the present invention, a method for automatically ordering ingredients for a restaurant is provided, in which a control unit of a server terminal acquires ingredient ordering data from a store terminal, refers to ordering constraint data, and sends an alert to the store terminal if the ordering constraint conditions are not met. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide an ordering method that can reduce the risk of waste and opportunity loss when food ingredients and other items are ordered under constraints in restaurants. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing a system for executing an automatic ordering method according to a first embodiment of the present invention. FIG. [Figure 2] FIG. 2 is a functional block diagram showing the server terminal 100 of FIG. [Figure 3] FIG. 2 is a functional block diagram showing the store terminal 200 of FIG. 1. [Figure 4] FIG. 2 is a diagram showing an example of store data stored in the server terminal 100. [Figure 5] FIG. 2 is a diagram showing an example of order constraint data stored in the server terminal 100. [Figure 6] 1 is a flowchart illustrating an automatic ordering method according to a first embodiment of the present invention. [Figure 7] 10 is a flowchart showing another example of an automatic ordering method according to the first embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the embodiments described below do not unduly limit the content of the present invention described in the claims. Furthermore, not all of the components shown in the embodiments are necessarily essential components of the present invention.

[0011] <Configuration> 1 is a block diagram showing a system for automatically ordering ingredients in a restaurant according to a first embodiment of the present invention. This system 1 includes a server terminal 100 that receives order data and processes orders from a restaurant terminal 200, which is managed by a restaurant user and orders ingredients, and restaurant terminals 200A and 200B that are managed by the restaurant user. For ease of explanation, each terminal is described as being a single terminal or a specific number of terminals, but the number of each terminal is not limited.

[0012] The server terminal 100 and the store terminals 200A and 200B are connected to each other via a network NW1. The network NW is configured by the Internet, an intranet, a wireless LAN (Local Area Network), a WAN (Wide Area Network), or the like.

[0013] The server terminal 100 may be, for example, a general-purpose computer such as a workstation or a personal computer, or may be logically realized by cloud computing.

[0014] The store terminals 200A and 200B are, for example, information processing devices such as personal computers and tablet terminals, but may also be configured as smartphones, mobile phones, PDAs, or the like.

[0015] In this embodiment, the system 1 is described as having a server terminal 100 and store terminals 200A and 200B, and a configuration in which users of each terminal use their respective terminals to operate the server terminal 100, but the server terminal 100 may be configured as a standalone unit and may itself have a function for each user to directly operate it. For ease of explanation, the store terminals 200A and 200B will be collectively referred to as the store terminal 200 below.

[0016] Fig. 2 is a functional block configuration diagram of the server terminal 100 of Fig. 1. The server terminal 100 includes a communication unit 110, a storage unit 120, and a control unit .

[0017] The communication unit 110 is a communication interface for communicating with the store terminals 200A and 200B via the network NW1, and communication is performed according to a communication protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol).

[0018] The storage unit 120 stores input data, programs for executing various control processes and functions in the control unit 130, and is composed of RAM (Random Access Memory), ROM (Read Only Memory), etc. The storage unit 120 also has a store data storage unit 121 that stores various data related to stores, and an order constraint data storage unit 122 that stores various data related to ingredient ordering constraint conditions. A database (not shown) storing various data may be constructed outside the storage unit 120 or the server terminal 100.

[0019] The control unit 130 controls the overall operation of the server terminal 100 by executing programs stored in the storage unit 120, and is composed of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc. The functions of the control unit 130 include an information receiving unit 131 that receives information from each store terminal, and an information processing unit 132 that references various data related to the store and various data related to ordering constraint conditions and executes ordering processing. The information receiving unit 131 and the information processing unit 132 are activated by programs stored in the storage unit 120 and executed by the server terminal 100, which is a computer (electronic calculator).

[0020] The information receiving unit 131 receives information from the store terminal 200 via the communication unit 110. For example, the information receiving unit 131 receives foodstuff ordering data from the store terminal 200.

[0021] The information processing unit 132 refers to the order constraint data that manages the order constraint conditions for the order data received from the store terminal 200, and executes predetermined processing such as order processing.

[0022] The control unit 130 may also have a screen generation unit (not shown), which generates screen information to be displayed via the user interface of the store terminal 200 upon request. For example, the control unit 130 generates the user interface by using image and text data (not shown) stored in the storage unit 120 as material and arranging various images and text in predetermined areas of the user interface based on predetermined layout rules.

[0023] The processing related to the image generation unit can also be executed by a GPU (Graphics Processing Unit).

[0024] Fig. 3 is a functional block diagram showing the store terminal 200 of Fig. 1. The store terminal 200 includes a communication unit 210, a display operation unit 220, a storage unit 230, and a control unit 240.

[0025] The communication unit 210 is a communication interface for communicating with the server terminal 100 via the network NW, and communication is performed according to a communication protocol such as TCP / IP.

[0026] The display operation unit 220 is a user interface used by store users of the restaurant to input instructions and to display text, images, etc. in accordance with input data from the control unit 240, and is composed of a display, keyboard, and mouse if the store terminal 200 is configured as a personal computer, and is composed of a touch panel, etc. if the store terminal 200 is configured as a smartphone or tablet terminal. This display operation unit 220 is started up by a control program stored in the storage unit 230 and executed by the store terminal 200, which is a computer (electronic calculator).

[0027] The storage unit 230 stores input data, programs for executing various control processes and functions in the control unit 240, and is composed of RAM, ROM, etc. The storage unit 230 also temporarily stores the contents of communication with the server terminal 100.

[0028] The control unit 240 controls the overall operation of the store terminal 200 by executing the programs stored in the storage unit 230, and is composed of a CPU, a GPU, and the like.

[0029] Although the configuration of the store terminal 200 has been explained using Figure 3, instead of the store terminal 200, a store management system (not shown) that manages the ordering data of each restaurant can manage the ordering data of ingredients for each store, and the server terminal 100 can also receive the ordering data from the store management system.

[0030] FIG. 4 is a diagram showing an example of store data stored in the server terminal 100. As shown in FIG.

[0031] The store data 1000 shown in Fig. 4 stores various data related to store users of a restaurant. For ease of explanation, Fig. 4 shows an example of one store user (for example, a store user unit) (a user identified by a user ID "10001"), but information on multiple store users can be stored.

[0032] The various data related to store users may include, but are not limited to, basic information about the store users (e.g., store name, company name, store name, address, contact information, person in charge, etc.), order data (e.g., ingredient name (supply name), quantity, amount, delivery date, etc.), inventory data (e.g., ingredient name, quantity, expiration date, etc.), and forecast data (e.g., demand and supply forecasts for ingredients based on sales data and actual ingredient data).

[0033] FIG. 5 is a diagram showing an example of the order constraint data stored in the server terminal 100. As shown in FIG.

[0034] The ordering constraint data 1000 shown in Figure 5 stores various data related to the ordering constraint conditions for ingredients. For ease of explanation, Figure 5 shows an example of one supplier user (for example, a user identified by supplier ID "20001"), but information for multiple supplier users can also be stored.

[0035] The various data related to the ordering constraint user may include, but are not limited to, condition data relating to the minimum total amount (e.g., the minimum total amount at the time of ordering for each store or each supplier), quantity data for a single product (e.g., the orderable multiple unit for each product, the minimum orderable quantity, etc.), and quantity data for multiple products (e.g., the orderable multiple unit, the minimum orderable quantity, etc. for multiple products). This ordering constraint data can be received as preset data from the store terminal 200, the store management system, or a supplier terminal (not shown), and can also be stored in the memory unit 120 of the server terminal 100.

[0036] <Processing flow> With reference to FIG. 6 and subsequent figures, the flow of processing of an automatic ordering method for ingredients or supplies (hereinafter collectively referred to as ingredients) in a restaurant, which is executed by the system 1 of this embodiment, will be described. 6 is a flowchart showing a method for automatically ordering ingredients in a restaurant according to a first embodiment of the present invention. As a preprocessing step, the server terminal 100 receives basic store information (e.g., store name, company name, store name, address, contact information, person in charge, etc.), inventory data (e.g., ingredient name, quantity, expiration date (number of days to consume from the delivery date)), and forecast data (e.g., demand and supply forecasts for ingredients based on sales data and actual ingredient data), from the store terminal (or store management system), and stores the data as store data 1000 in the store data storage unit 121 of the memory unit 120.

[0037] Then, in the process of step S101, the information receiving unit 131 of the control unit 130 of the server terminal 100 receives the order data of the store from the store terminal 200. As described above, the order data may include, for example, the ingredient name (supply name), quantity, price, desired delivery date, etc. One or more ingredient names (supply names) can be received from the store terminal 200 as the ingredient name (supply name). The information receiving unit 131 of the control unit 130 stores the received information in the store data storage unit 121 of the storage unit 120 .

[0038] Subsequently, in the process of step S102, the information processing unit 132 of the control unit 130 of the server terminal 100 refers to the order constraint data 2000 stored in advance in the order constraint data storage unit 122 of the storage unit 120. The ordering constraint conditions included in the ordering constraint data 2000 include condition data related to the minimum total amount (e.g., the minimum total amount at the time of ordering by store or by supplier), quantity data for a single product (e.g., the orderable multiple unit for each product, the minimum orderable quantity, etc.), and quantity data for multiple products (e.g., the orderable multiple unit, the minimum orderable quantity for multiple products, etc.). More specifically, there are constraint conditions such as the requirement that for two types of noodles, regular noodles and single serving noodles, each noodle must be a multiple of 5 balls and the total must be a multiple of 90 balls / case, the requirement that for spaghetti, fettuccine, and children's pasta, the total must be a multiple of 3C / S, and the requirement that for orders to ABC Store, the total amount must be 5,000 yen or more.

[0039] Next, in step S103, the information processing unit 132 of the control unit 130 of the server terminal 100 determines whether the received order data satisfies the constraint conditions based on the order conditions included in the order constraint data 2000. For example, if the order data received from the store terminal 200 is for 50 and 30 regular noodles and individual serving noodles, respectively, the constraint conditions are "for the two types of regular noodles and individual serving noodles, each noodle must be a multiple of 5 noodles, and the total must be a multiple of 90 noodles / Case," so some of the constraint conditions are met, but not all of them.

[0040] Here, if the constraint condition is satisfied as a result of the process in step S103, the information processing unit 132 of the control unit 130 of the server terminal 100 executes the order processing based on the received order data as the process in step S104.

[0041] Here, if the processing result of step S103 shows that the constraint conditions are not satisfied, then in step S105, the information processing unit 132 of the control unit 130 of the server terminal 100 sends an alert to the store terminal 200 to the effect that the constraint conditions are not satisfied for the received order data. For example, as an alert, the information processing unit 132 can send information necessary to satisfy the order constraint conditions, such as "There is a shortage of 10 bowls of individual serving noodles."

[0042] 7 is a flowchart showing another example of the method for automatically ordering ingredients in a restaurant according to the first embodiment of the present invention. In this example, the server terminal 100 refers to store data such as inventory data and forecast data of the store, instead of receiving order data from the store terminal 200, and makes an order proposal to the store.

[0043] First, in the process of S201, the information processing unit 132 of the server terminal 100 references the store data 1000, which includes inventory data and forecast data for the target store and is stored in the store data storage unit 121 of the memory unit 120. Examples of inventory data include the target store's ingredient name, quantity, expiration date (number of days to consume from the delivery date), etc., while examples of forecast data include ingredient demand and supply forecasts based on the target store's sales data and ingredient performance data. Here, the information processing unit 132 references the inventory data and forecast data to identify ingredients that need to be ordered.

[0044] Next, in step S202, the information processing unit 132 of the server terminal 100 references the ordering constraint data 2000 in the storage unit 120 and checks the ordering constraint conditions of the supplier of the target store. As in the above example, the ordering constraint conditions include constraint conditions such as that for the two types of noodles, regular noodles and individual serving noodles, each noodle must be a multiple of 5 noodles and the total must be a multiple of 90 noodles / case, constraint conditions such as that for spaghetti, fettuccine, and children's pasta, the total must be a multiple of 3 C / S, and constraint conditions such as that for orders to ABC Store, the total amount must be 5,000 yen or more. Here, the information processing unit 132 specifies constraint conditions for the identified ingredients.

[0045] Next, in step S203, if the identified ingredients do not satisfy the constraints, the information processing unit 132 of the server terminal 100 sends information including the quantity or price of ingredients that satisfy the constraints to the store terminal 200 as an order proposal. Patterns that satisfy the constraints may include increasing the number of ingredients to be ordered, or ordering ingredients different from those to be ordered. When making the proposal, the information processing unit 132 determines the combination of ingredients and quantities that will most effectively reduce waste and opportunity loss based on the demand and supply forecasts, inventory quantities, delivery dates (best before dates), and / or price information for the ingredients.

[0046] Although the embodiments of the present invention have been described above, they can be embodied in various other forms, and various omissions, substitutions, and modifications can be made. These embodiments, modifications, and omissions, substitutions, and modifications are included in the technical scope of the claims and their equivalents. [Explanation of symbols]

[0047] 1 System 100 Server terminal, 110 Communication unit, 120 Storage unit, 130 Control unit, 200 Store terminal, NW1 Network

Claims

1. A method for automatically ordering products at a restaurant, comprising: The control unit of the server terminal Refer to the inventory data and supply and demand forecast data of the restaurant stored in the storage unit of the server terminal, Identifying products that need to be ordered based on the inventory data and supply and demand forecast data; Refer to order constraint data stored in the storage unit, which includes constraints on the quantity and price of the product; The method proposes to the restaurant to order the identified product in combination with a different product that satisfies the constraints.

2. 10. The method of claim 1, The control unit The method includes receiving order data for the product from a store terminal of the restaurant.

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