Apparatus for preparing foods using parallel preparing logic and control method thereof

Abstract

The present disclosure relates to an apparatus for preparing foods using parallel preparing logic and a control method thereof, which assign a plurality of foods included in one or more first integrated order numbers in order of high preparing difficulty, wherein if a first preparing machine capable of preparing a first food among the plurality of foods at the current time is preparing a second food corresponding to a lower preparing difficulty than the first food among the plurality of foods, the second food may be assigned to a second preparing machine capable of preparing the second food at the current time, and on the basis of the preparing difficulty of an unassigned third food among the plurality of foods and the time at which the first preparing machine which is preparing the second food is expected to be switched to an available state, the third food may be assigned to the first preparing machine so that the preparing of the unassigned third food is reserved.

Description

A device for manufacturing food using parallel manufacturing logic and a control method thereof

[0001] The present disclosure relates to a device for manufacturing food, and more particularly, to a device for manufacturing food using parallel manufacturing logic.

[0002] Recently, the number of unmanned cafes has been increasing.

[0003] These unmanned cafes process orders in a 'first in, first out' manner when receiving multiple drink orders, which causes a delay in serving drinks when drinks with a short production process, such as Americano, are received after orders for drinks with a long production process, such as syrup drinks.

[0004] Additionally, because orders are processed in a 'first in, first out' manner, there is a problem in that the idle time of unused manufacturing equipment increases depending on the order of multiple beverage orders, significantly reducing the manufacturing speed of all received orders.

[0005] In addition, since multiple beverages are not assigned to manufacturing machines according to a preset logic to ensure efficient manufacturing, there is a problem in that when a large number of beverage orders are received, the machine operates inefficiently and the manufacturing speed drops significantly.

[0006] Accordingly, unlike the existing method, a parallel manufacturing logic is needed to address the problem of delayed ordering of specific beverages and to efficiently allocate a large number of beverages for production. However, such technology is not currently available.

[0007] The purpose of the embodiment disclosed in the present disclosure is to provide a device for manufacturing food using parallel manufacturing logic.

[0008] The problems to be solved by the present disclosure are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below.

[0009] A device for manufacturing food using parallel manufacturing logic according to the present disclosure for achieving the above-described technical task comprises: at least one storage unit for storing manufactured food; at least one pickup unit for storing food requested for pickup; a communication unit for receiving an integrated order number including an order for at least one food and communicating with a plurality of manufacturing machines; a memory for storing at least one instruction;And a processor for controlling a plurality of manufacturing machines and robots by executing at least one instruction, wherein the processor assigns a plurality of foods included in one or more first integrated order numbers in descending order of manufacturing difficulty, and if a first manufacturing machine capable of manufacturing a first food among the plurality of foods is currently manufacturing a second food among the plurality of foods, corresponding to a lower manufacturing difficulty than the first food, assigns the second food to a second manufacturing machine capable of manufacturing the second food at the present time, and assigns the manufacturing of the unassigned third food to the first manufacturing machine so that the manufacturing of the unassigned third food is reserved based on the manufacturing difficulty of the third food among the plurality of foods and the time at which the first manufacturing machine manufacturing the second food is expected to switch to an available state, and checks the status of the robot at preset time intervals, and the status of the robot includes a state of manufacturing food, a state of transporting food for manufacturing, a state of transporting food that has been manufactured, and a standby state, and if the robot is in the standby state, it checks whether there is food stored in the storage unit, and if there is food stored in the storage unit and the number of currently available pickup units is greater than or equal to a preset number, The robot may be controlled to move at least one food item among the food items stored in the storage unit to the available pickup unit, and when an order is received from a customer's terminal, location information of the terminal may be acquired, and the expected arrival time of the customer may be calculated based on the acquired location information, and the robot may be controlled to move the food item among the food items stored in the storage unit, which is determined to have the fastest expected arrival time for the customer, to the pickup unit.

[0010] In order to achieve the above-described technical problem, the present disclosure provides a method for controlling a food manufacturing device that controls a plurality of manufacturing machines and robots, and includes at least one storage unit for storing manufactured food and at least one pickup unit for storing food requested for pickup, the method comprising: a step of assigning a plurality of foods included in at least one first integrated order number in descending order of manufacturing difficulty; a step of assigning a second food, which has a lower manufacturing difficulty than the first food, to a second manufacturing machine capable of manufacturing the second food at the present time when a first manufacturing machine capable of manufacturing the first food at the present time is currently manufacturing the second food; a step of assigning a third food, which has not been assigned to the first manufacturing machine, to be manufactured based on a manufacturing difficulty of the third food among the plurality of foods and an expected time at which the first manufacturing machine manufacturing the second food is expected to switch to an available state; a step of checking a state of the robot at preset intervals, wherein the state of the robot includes a state of manufacturing food, a state of transporting food for manufacturing, a state of transporting manufactured food, and a standby state; The method may include: a step of checking whether there is food stored in the storage unit when the robot is in the standby state; a step of controlling the robot to move at least one food among the food stored in the storage unit to the available pickup unit when there is food stored in the storage unit and the number of currently available pickup units is greater than or equal to a preset number; a step of obtaining location information of the terminal when an order is received from a customer's terminal and calculating the expected arrival time of the customer based on the obtained location information; and a step of controlling the robot to move the food among the foods stored in the storage unit, which is determined to have the fastest expected arrival time of the customer, to the pickup unit.

[0011] In addition, a computer program stored in a computer-readable recording medium for executing the present disclosure may be further provided.

[0012] In addition, a computer-readable recording medium recording a computer program for executing a method for implementing the present disclosure may be further provided.

[0013] According to the above-described problem solving means of the present disclosure, an effect is provided of providing a device for manufacturing food using parallel manufacturing logic.

[0014] The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0015] FIG. 1 is a schematic diagram of a beverage manufacturing system according to an embodiment of the present disclosure.

[0016] FIG. 2 is a block diagram of a beverage manufacturing device according to an embodiment of the present disclosure.

[0017] FIG. 3 and FIG. 4 are flowcharts of a method for controlling a beverage manufacturing device according to an embodiment of the present disclosure.

[0018] Figure 5 is a diagram illustrating the manufacturing difficulty of each beverage stored in memory.

[0019] Figure 6 is a drawing showing examples of beverages that can be manufactured by each manufacturing machine stored in memory.

[0020] Figure 7 is a drawing illustrating a method of controlling a robot to move a beverage stored in a storage rack to a pickup rack.

[0021] Figure 8 is a drawing illustrating a detailed process for manufacturing a beverage including multiple manufacturing processes.

[0022] Figures 9 to 13 are drawings illustrating the operation of a beverage manufacturing device.

[0023] Throughout this disclosure, the same reference numerals denote the same components. This disclosure does not describe all elements of the embodiments, and any content that is common in the technical field to which this disclosure pertains or that overlaps between embodiments is omitted. The terms "part, module, element, block" used in the specification may be implemented in software or hardware, and depending on the embodiments, multiple "parts, modules, elements, blocks" may be implemented as a single component, or a single "part, module, element, block" may include multiple components.

[0024] Throughout the specification, when a part is said to be "connected" to another part, this includes not only direct connection but also indirect connection, and indirect connection includes connection via a wireless communication network.

[0025] Additionally, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

[0026] Throughout the specification, when we say that an element is "on" another element, this includes not only cases where the element is in contact with the other element, but also cases where another element exists between the two elements.

[0027] The terms first, second, etc. are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

[0028] Singular expressions include plural expressions unless the context clearly indicates otherwise.

[0029] The identification codes for each step are used for convenience of explanation and do not describe the order of each step. Each step may be performed in a different order than specified unless the context clearly indicates a specific order.

[0030] The operating principle and embodiments of the present disclosure are described below with reference to the attached drawings.

[0031] In this specification, the term "beverage manufacturing device according to the present disclosure" encompasses various devices capable of performing computational processing and providing results to a user. For example, the beverage manufacturing device according to the present disclosure may include a computer, a server device, and a portable terminal, or may be any one of them.

[0032] Here, the computer may include, for example, a notebook, desktop, laptop, tablet PC, slate PC, etc. equipped with a web browser.

[0033] The above server device is a server that processes information by communicating with an external device, and may include an application server, a computing server, a database server, a file server, a game server, a mail server, a proxy server, and a web server.

[0034] The above portable terminal may include, for example, all kinds of handheld-based wireless communication devices such as PCS, GSM, PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminals, smart phones, etc., as well as wearable devices such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted devices (HMD).

[0035] The artificial intelligence-related functions according to the present disclosure are operated through a processor and a storage unit. The processor may be composed of one or more processors. In this case, one or more processors may be a general-purpose processor such as a CPU, an AP, a Digital Signal Processor (DSP), a graphics-only processor such as a GPU or a Vision Processing Unit (VPU), or an artificial intelligence-only processor such as an NPU. One or more processors control the processing of input data according to predefined operation rules or artificial intelligence models stored in the storage unit. Alternatively, if one or more processors are artificial intelligence-only processors, the artificial intelligence-only processor may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0036] The predefined operation rules or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that the basic artificial intelligence model is trained using a learning algorithm using a plurality of learning data, thereby creating the predefined operation rules or artificial intelligence models set to perform a desired characteristic (or purpose). This learning may be performed on the device itself on which the artificial intelligence according to the present disclosure is performed, or may be performed through a separate server and / or system. Examples of the learning algorithm include, but are not limited to, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning.

[0037] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weights, and performs neural network operations through operations between the operation results of the previous layer and the multiple weights. The multiple weights of the multiple neural network layers may be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights may be updated so that the loss value or cost value obtained from the artificial intelligence model is reduced or minimized during the learning process. The artificial neural network may include a deep neural network (DNN), and examples thereof include, but are not limited to, a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), a restricted boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), or a deep Q-network.

[0038] According to an exemplary embodiment of the present disclosure, a processor can implement artificial intelligence. Artificial intelligence refers to a machine learning method based on an artificial neural network that mimics human neurons (biological neurons) to enable machines to learn. Artificial intelligence methodologies can be categorized into supervised learning, where input and output data are provided together as training data, thereby determining the solution (output data) to a problem (input data); unsupervised learning, where only input data is provided without output data, so that the solution (output data) to a problem (input data) is not determined; and reinforcement learning, where a reward is provided from an external environment each time an action is taken in the current state, and learning proceeds in a direction that maximizes this reward. Furthermore, artificial intelligence methodologies can be categorized by the architecture of the learning model. The architectures of widely used deep learning technologies can be categorized into convolutional neural networks, recurrent neural networks, transformers, and generative adversarial networks.

[0039] The device may include an artificial intelligence model. The artificial intelligence model may be a single artificial intelligence model or may be implemented as multiple artificial intelligence models. The artificial intelligence model may be composed of a neural network (or artificial neural network) and may include statistical learning algorithms that mimic biological neurons in machine learning and cognitive science. A neural network may refer to a model in general that has problem-solving capabilities by changing the binding strength of synapses through learning, formed by artificial neurons (nodes) that form a network by combining synapses. The neurons of the neural network may include a combination of weights or biases. The neural network may include one or more layers composed of one or more neurons or nodes. For example, the device may include an input layer, a hidden layer, and an output layer. The neural network constituting the device can infer a desired outcome from an arbitrary input by changing the weights of the neurons through learning.

[0040] The processor can create a neural network, train (or learn) a neural network, perform a calculation based on received input data, generate an information signal based on the calculation result, or retrain the neural network. The models of the neural network can include various types of models such as CNN, R-CNN, RPN, RNN, S-DNN, S-SDNN, Deconvolution Network, DBN, RBM, Fully Convolutional Network, LSTM Network, Classification Network, etc., such as GoogleNet, AlexNet, VGG Network, etc., but are not limited thereto. The processor can include one or more processors for performing calculations according to the models of the neural network. For example, the neural network can include a deep neural network.

[0041] Neural networks include CNN, RNN, perceptron, multilayer perceptron, Feed Forward (FF), Radial Basis Network (RBF), Deep Feed Forward (DFF), Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Auto Encoder (AE), Variational Auto Encoder (VAE), Denoising Auto Encoder (DAE), Sparse Auto Encoder (SAE), MC (Markov Chain), HN (Hopfield Network), BM (Boltzmann Machine), RBM (Restricted Boltzmann Machine), DBN (Depp Belief Network), DCN (Deep Convolutional Network), DN (Deconvolutional Network), DCIGN (Deep Convolutional Inverse Graphics Network), GAN (Generative Adversarial Network), LSM (Liquid State Machine), ELM (Extreme Learning) Machine), ESN (Echo State Network), DRN (Deep Residual Network), DNC (Differentiable Network) It will be understood by those skilled in the art that the neural network may include any neural network, including but not limited to a Neural Computer (NN), a Neural Turning Machine (NTM), a Capsule Network (CN), a Kohonen Network (KN), and an Attention Network (AN).

[0042] According to an exemplary embodiment of the present disclosure, the processor may be configured to perform a process for generating a CNN (Convolution Neural Network) such as GoogleNet, AlexNet, VGG Network, Region with Convolution Neural Network (R-CNN), Region Proposal Network (RPN), Recurrent Neural Network (RNN), Stacking-based deep Neural Network (S-DNN), State-Space Dynamic Neural Network (S-SDNN), Deconvolution Network, Deep Belief Network (DBN), Restrcted Boltzman Machine (RBM), Fully Convolutional Network, Long Short-Term Memory (LSTM) Network, Classification Network, Generative Modeling, eXplainable AI, Continual AI, Representation Learning, AI for Material Design, BERT, SP-BERT, MRC / QA for natural language processing, Text Analysis, Dialog System, GPT-3, GPT-4, Visual Analytics for vision processing, Visual Understanding, Video Synthesis, ResNet for data intelligence, Anomaly Detection, Prediction, Time-Series Forecasting, Various artificial intelligence structures and algorithms, including optimization, recommendation, and data creation, can be utilized, but are not limited thereto. Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0043] A food manufacturing device according to an embodiment of the present disclosure is a manufacturing device that manufactures food in an unmanned restaurant or cafe, and a robot (140) manufactures food and provides the manufactured food to a customer.

[0044] The embodiments described below will be described using beverages among foods, and the beverage manufacturing device (100) will be described as being installed in an unmanned cafe. However, the present disclosure is not limited to beverage manufacturing, and can be applied to any food that can be manufactured unmanned.

[0045] FIG. 1 is a schematic diagram of a beverage manufacturing system (10) according to an embodiment of the present disclosure.

[0046] Referring to FIG. 1, a beverage manufacturing system (10) according to an embodiment of the present disclosure includes a beverage manufacturing device (100), a server (200), a kiosk device (300), and a terminal (400).

[0047] However, in some embodiments, the beverage manufacturing system (10) may include fewer or more components than those illustrated in FIG. 1.

[0048] The beverage manufacturing device (100) may be installed in an unmanned cafe, and the kiosk device (300) may be installed together with the beverage manufacturing device (100) to receive orders from customers visiting the cafe.

[0049] The kiosk device (300) may include components such as an output unit, a communication unit (120), and a payment module so that a customer visiting a cafe can select at least one menu provided by the cafe and proceed to payment.

[0050] When an order is received from a kiosk device (300), the server (200) generates an integrated order number and transmits it to the beverage manufacturing device (100) so that the beverage is manufactured.

[0051] At this time, the server (200) may also receive an order received by the user's terminal (400).

[0052] For example, the server (200) can provide a service through a service application or the web, and the user can execute the service application of the terminal (400) to select information on the store from which he or she wishes to pick up a drink, select a menu to order, and then proceed with payment.

[0053] When the beverage manufacturing device (100) receives an integrated order number from the server (200), it manufactures the beverage included in the order.

[0054] At this time, when a situation arises where multiple beverages must be manufactured simultaneously, the beverage manufacturing device (100) according to the embodiment of the present disclosure uses parallel manufacturing logic to assign multiple beverages ordered to multiple manufacturing machines (150) to manufacture the beverages in order to solve the problems of the prior art.

[0055] Below, the operation process of the beverage manufacturing device (100) according to the embodiment of the present disclosure will be described in more detail with reference to other drawings.

[0056] FIG. 2 is a block diagram of a beverage manufacturing device (100) according to an embodiment of the present disclosure.

[0057] Referring to FIG. 2, a beverage manufacturing device (100) according to an embodiment of the present disclosure includes a processor (110), a communication unit (120), a memory (130), a robot (140), a manufacturing machine (150), a pickup module (160), a storage unit (170), a pickup unit (180), and a pickup door (190).

[0058] However, in some embodiments, the beverage manufacturing device (100) may include fewer or more components than those illustrated in FIG. 2.

[0059] The processor (110) may be implemented as a storage unit that stores data regarding an algorithm for controlling the operation of components within the device or a program that reproduces the algorithm, and at least one processor (110) that performs the aforementioned operation using the data stored in the storage unit. In this case, the storage unit and the processor (110) may each be implemented as separate chips. Alternatively, the storage unit and the processor (110) may be implemented as a single chip.

[0060] In addition, the processor (110) can control any one or a combination of the components described above to implement various embodiments according to the present disclosure described in the drawings below on the device.

[0061] The processor (110) can control the beverage manufacturing machine (150) and the robot (140) by executing at least one instruction stored in the memory (130).

[0062] The processor (110) can control all components within the beverage manufacturing device (100) including the robot (140).

[0063] In addition to operations related to the above-described application, the processor (110) can typically control the overall operation of the device. The processor (110) can process signals, data, information, etc. input or output through the components described above, or run application programs stored in the storage unit, thereby providing or processing appropriate information or functions to the user.

[0064] In addition, the processor (110) may control at least some of the components of the device to run an application program stored in the storage unit. Furthermore, the processor (110) may operate at least two or more of the components included in the device in combination to run the application program.

[0065] The processor (110) may be implemented as one or more processors. Hereinafter, even if the processor (110) is expressed as singular, it may be considered as plural. The processor (110) may control the configurations of the beverage manufacturing device (100). The processor (110) may refer to a data processing device built into hardware that has a physically structured circuit to perform a function expressed by a code or command included in a program. As such, the processor (110) is an example of a data processing device built into hardware, and may encompass processing devices such as a microprocessor, a central processing unit (CPU), a processor (110) core, a multiprocessor, an application-specific integrated circuit (ASIC), and a field programmable gate array (FPGA), but the scope of the present invention is not limited thereto. The processor (110) may separately include a learning processor (110) for performing artificial intelligence operations, or may include a learning processor (110) on its own.

[0066] The communication unit (120) may include one or more modules that connect the beverage manufacturing device (100) to one or more networks.

[0067] The communication unit (120) may include one or more components that enable communication with an external device, and may include, for example, at least one of a broadcast reception module, a wired communication module, a wireless communication module, a short-range communication module, and a location information module.

[0068] The wired communication module may include various wired communication modules such as a Local Area Network (LAN) module, a Wide Area Network (WAN) module, or a Value Added Network (VAN) module, as well as various cable communication modules such as a Universal Serial Bus (USB), a High Definition Multimedia Interface (HDMI), a Digital Visual Interface (DVI), RS-232 (recommended standard 232), power line communication, or plain old telephone service (POTS).

[0069] The wireless communication module may include a wireless communication module that supports various wireless communication methods such as GSM (global System for Mobile Communication), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), UMTS (universal mobile telecommunications system), TDMA (Time Division Multiple Access), LTE (Long Term Evolution), 4G, 5G, and 6G, in addition to a WiFi module and a Wireless Broadband module.

[0070] The wireless communication module may include a wireless communication interface including an antenna and a transmitter for transmitting communication signals. Furthermore, the wireless communication module may further include a signal conversion module that modulates a digital control signal output from the processor (110) through the wireless communication interface into an analog wireless signal under the control of the processor (110).

[0071] The short-range communication module is for short-range communication, and can support short-range communication using at least one of Bluetooth, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technologies.

[0072] The processor (110) can receive orders, requests, error messages, etc. of the kiosk device (300) through the communication unit (120), and can communicate with the server (200) to exchange various data.

[0073] The memory (130) can store data supporting various functions of the device. The memory (130) can store a plurality of application programs (or applications) running on the device, data for the operation of the device, and commands. At least some of these application programs may exist for the basic functions of the device. Meanwhile, the application programs can be stored in the memory (130), installed on the device, and driven to perform operations (or functions) by the processor (110).

[0074] The memory (130) can store data supporting various functions of the device and programs for the operation of the processor (110), input / output data (e.g., music files, still images, moving images, etc.) can be stored, and a plurality of application programs (or applications) run on the device, data for the operation of the device, and commands can be stored. At least some of these application programs can be downloaded from an external server (200) via wireless communication.

[0075] The memory (130) may include at least one type of storage medium among a flash memory (130) type, a hard disk type, an SSD (Solid State Disk type), an SDD (Silicon Disk Drive) type, a multimedia card micro type, a card type memory (e.g., SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory (130), a magnetic disk, and an optical disk. In addition, the memory (130) may be a database that is separate from the device but is connected by wire or wirelessly.

[0076] The memory (130) may be electrically connected to the processor (110) and may store at least one code executed by the processor (110). The memory (130) may collectively refer to various types of storage devices. The memory (130) may store information necessary for performing operations using artificial intelligence, machine learning, and artificial neural networks.

[0077] The memory (130) can store various learning models. The learning models stored in the memory (130) can infer result values ​​for new input data other than learning data, and the inferred values ​​can be used as a basis for judgment to perform a certain action. The learning models stored in the memory (130) can perform learning based on label information, and various backpropagation algorithms can be applied so that the loss function has a target value to increase the accuracy of learning.

[0078] Additionally, the memory (130) may have multiple processes for the beverage manufacturing device (100).

[0079] Additionally, the memory (130) may store a manufacturing recipe for manufacturing at least one type of beverage or food, a preset manufacturing difficulty based on the number of manufacturing processes included in the manufacturing recipe, and the types of beverages or food that can be manufactured in each manufacturing machine (150).

[0080] The pickup module (160) is a means for a customer who has ordered a beverage to request pickup of the beverage, and may include a keypad for entering a pickup number and a reader capable of recognizing a code (e.g., barcode, QRcode) output to the screen of a terminal (400) carried by the user.

[0081] The processor (110) can provide pickup information so that the customer can pick up the beverage when the beverage is ready to be prepared and manufactured after payment for the beverage ordered by the customer is completed.

[0082] At this time, if the processor (110) knows the customer's member information (member ID or mobile phone number), it can provide pickup information to the terminal (400) through a message or notification.

[0083] As another example, if the processor (110) does not know the customer's membership information, it can output and provide pickup information through the kiosk device (300).

[0084] As mentioned above, the pickup information may include at least one of a pickup number or a pickup code.

[0085] The storage unit (170) is a means for storing a finished beverage, and the beverage manufacturing device (100) may include at least one storage unit (170). In some embodiments, a beverage manufacturing device (100) equipped with sufficient pickup units (180) may not have a storage unit (170).

[0086] The pickup stand (180) is a means for storing beverages that have been requested to be picked up by a customer through a pickup module among beverages that have been manufactured, and the beverage manufacturing device (100) may include at least one pickup stand (180).

[0087] The pickup door (190) is a means for opening or closing the pickup stand (180). Normally, it is closed, and when pickup information is authenticated through the pickup module (160), the processor (110) opens the pickup door (190) so that the customer can take his or her beverage.

[0088] In some embodiments, the beverage manufacturing device (100) may further include an input unit, an output unit, a camera, a sensor unit, and an interface unit.

[0089] The input unit is for inputting video information (or signal), audio information (or signal), data, or information input from a user, and may include at least one camera, at least one microphone, and at least one user input unit. Voice data or image data collected from the input unit may be analyzed and processed into a user control command.

[0090] The beverage manufacturing device (100) can receive various control signals through the input unit.

[0091] The output unit is for generating output related to visual, auditory, or tactile sensations, and may include at least one of a display unit, an audio output unit, a haptic module, and an optical output unit. The display unit may be formed as a layer structure with a touch sensor or formed as an integral part, thereby implementing a touch screen. Such a touch screen may function as a user input unit that provides an input interface between the device and a user, and at the same time, may provide an output interface between the device and the user.

[0092] The display unit displays (outputs) information processed by this device. For example, the display unit may display execution screen information of an application program (e.g., an application) running on this device, or UI (User Interface) or GUI (Graphical User Interface) information based on such execution screen information.

[0093] The audio output unit can output audio data received through the communication unit (120) or stored in the storage unit, or output audio signals related to functions performed by the device. Such audio output units can include a receiver, a speaker, a buzzer, and the like.

[0094] The beverage manufacturing device (100) can output information that beverage manufacturing is complete and information that beverage pickup preparation is complete through an output unit, and can output information using at least one output means among a video output means and a voice output means.

[0095] The sensor unit senses at least one of the internal information of the device, the surrounding environmental information surrounding the device, and the user information, and generates a sensing signal corresponding thereto. Based on this sensing signal, the processor (110) can control the operation or behavior of the device, or perform data processing, functions, or operations related to an application program installed on the device.

[0096] As described above, the sensor unit may include at least one of a proximity sensor, an illumination sensor, a touch sensor, an acceleration sensor, a magnetic sensor, a G-sensor, a gyroscope sensor, a motion sensor, an RGB sensor, an infrared sensor (IR sensor), a fingerprint recognition sensor, an ultrasonic sensor, an optical sensor (e.g., a camera), a microphone, an environmental sensor (e.g., at least one of a barometer, a hygrometer, a thermometer, a radiation detection sensor, a heat detection sensor, and a gas detection sensor), and a chemical sensor (e.g., a healthcare sensor, a biometric recognition sensor, etc.). Meanwhile, the present device may utilize information sensed by at least two or more of these sensors in combination.

[0097] The camera processes image frames, such as still images or video, obtained by the image sensor in shooting mode. The processed image frames can be displayed on the display or stored in the storage unit.

[0098] The camera may consist of a sensor unit.

[0099] In one embodiment, the processor (110) can confirm whether a person enters or leaves an unmanned cafe based on information sensed through a sensor unit or camera.

[0100] The user input unit is for receiving information from the user, and when information is input through the user input unit, the processor (110) can control the operation of the device to correspond to the input information. The user input unit may include a hardware physical key (e.g., a button located on at least one of the front, rear, and side of the device, a dome switch, a jog wheel, a jog switch, etc.) and a software touch key. As an example, the touch key may be a virtual key, a soft key, or a visual key displayed on a touch screen type display unit through software processing, or may be a touch key disposed on a part other than the touch screen. Meanwhile, the virtual key or visual key may have various forms and be displayed on the touch screen, and may be, for example, formed of a graphic, text, an icon, a video, or a combination thereof.

[0101] The interface unit serves as a passageway for various types of external devices connected to the device. The interface unit may include at least one of a wired / wireless headset port, an external charger port, a wired / wireless data port, a memory card port, a port for connecting a device equipped with an identification module (SIM), an audio I / O (Input / Output) port, a video I / O (Input / Output) port, and an earphone port. The device may perform appropriate control related to the external device connected to the interface unit.

[0102] FIG. 3 and FIG. 4 are flowcharts of a method for controlling a beverage manufacturing device (100) according to an embodiment of the present disclosure.

[0103] Figure 5 is a drawing illustrating the manufacturing difficulty of each beverage stored in memory (130).

[0104] Figure 6 is a drawing showing examples of beverages that can be manufactured by each manufacturing machine (150) stored in memory (130).

[0105] Figure 7 is a drawing illustrating controlling a robot (140) to move a beverage stored in a storage unit (170) to a pickup unit (180).

[0106] Figure 8 is a drawing illustrating a detailed process for manufacturing a beverage including multiple manufacturing processes.

[0107] Figures 9 to 13 are drawings illustrating the operation of a beverage manufacturing device (100).

[0108] Referring to FIGS. 3 to 13, a method for controlling a beverage manufacturing device (100) according to an embodiment of the present disclosure will be described in detail.

[0109] The processor (110) receives the integrated order number through the communication unit (120). (S100)

[0110] More specifically, the processor (110) receives a first integrated order number from the server (200). The first integrated order number includes at least one beverage order.

[0111] The processor (110) verifies whether the first integrated order number is an order for multiple beverages. (S150)

[0112] If the first integrated order number is an order for one beverage, the processor (110) assigns the ordered beverage to a manufacturing machine (150) and requests the manufacturing machine (150) to manufacture the beverage. At this time, if the manufacturing machine (150) capable of manufacturing the beverage is currently manufacturing a beverage for a previous order, the processor (110) may assign the manufacturing to be reserved.

[0113] When the first integrated order number in S150 is an order for multiple beverages, the processor (110) executes parallel manufacturing logic to perform the following processes.

[0114] At this time, when multiple first integrated order numbers are received within a preset time range, the processor (110) groups the first beverages included in the multiple first integrated order numbers and assigns them to be manufactured together.

[0115] For example, assuming that the preset time is 20 seconds and two different integrated order numbers are received at 10-second intervals, the processor (110) recognizes the two integrated order numbers as the first integrated order number and assigns manufacturing through parallel manufacturing logic for the beverages included therein.

[0116] In contrast, when two different integrated order numbers are received at 30-second intervals, the processor (110) recognizes the previous integrated order number as the first integrated order number and assigns manufacturing through parallel manufacturing logic for the beverages included therein, and recognizes the integrated order number received 30 seconds later as the second integrated order number and assigns manufacturing through parallel manufacturing logic for the beverages included therein separately.

[0117] The beverage manufacturing device (100) according to the embodiment of the present disclosure, through this configuration, distributes the manufacturing of different beverage orders received within a preset time, thereby enabling the manufacturing machine (150) and the robot (140) to manufacture beverages with maximum efficiency while ensuring that the order order is followed, thereby preventing a delay in manufacturing the customer's beverage.

[0118] The processor (110) assigns manufacturing to the manufacturing machine (150) in order of increasing manufacturing difficulty. (S200)

[0119] In detail, the processor (110) assigns a plurality of first beverages included in one or more first integrated order numbers in order of increasing manufacturing difficulty.

[0120] Figure 5 is a drawing illustrating the manufacturing difficulty of each beverage stored in memory (130).

[0121] Referring to FIG. 5, the memory (130) stores the manufacturing difficulty of each type of beverage that has been predetermined.

[0122] In the embodiments of the present disclosure, it is assumed that the difficulty of manufacturing a beverage is higher as more different manufacturing processes are included.

[0123] For example, Americano (Hot) is more difficult to make than espresso because it involves adding water.

[0124] Also, Americano (Ice) is more difficult to make than Americano (Hot) because it involves an additional manufacturing process of adding ice.

[0125] Also, since Caffe Latte (Hot) involves an additional manufacturing process of adding milk, it is more difficult to manufacture than Americano (Hot).

[0126] Also, since Caffe Latte (Ice) involves an additional manufacturing process of adding ice, it is more difficult to manufacture than Caffe Latte (Hot).

[0127] Figure 6 is a drawing showing examples of beverages that can be manufactured by each manufacturing machine (150) stored in memory (130).

[0128] Referring to FIG. 6, the memory (130) stores beverages that can be manufactured by each manufacturing machine (150) equipped in the unmanned cafe.

[0129] In this way, the processor (110) performs an assignment process for a plurality of first beverages in order of increasing difficulty in manufacturing, and checks whether a manufacturing machine (150) capable of manufacturing the first beverage in the assigned order is currently available. (S230)

[0130] The processor (110) assigns the beverage to be manufactured by the manufacturing machine (150) if the manufacturing machine (150) is available through S230 and if the manufacturing machine (150) exists.

[0131] At this time, if the manufacturing machine (150) capable of manufacturing a specific beverage among the plurality of first beverages at the current time of assignment is manufacturing another beverage, the processor (110) assigns a first beverage with a lower manufacturing difficulty than the beverage to the manufacturing machine (150) capable of manufacturing the beverage at the current time of assignment. (S250)

[0132] For example, assuming that the first integrated order number includes beverages A, B, C, and D, and that the manufacturing difficulty of beverage A is the highest, followed by beverages B, C, and D, in that order, the processor (110) assigns the manufacturing of beverage A first, but if the manufacturing machine (150) capable of manufacturing beverage A is currently manufacturing the beverage of the previous order, it assigns beverage B. In addition, if the manufacturing machine (150) capable of manufacturing beverage B is also currently manufacturing the beverage of the previous order, it assigns beverage C.

[0133] When performing this process, at least some of the first beverages may not have been allocated. In this case, the processor (110) performs the following process.

[0134] After beverage allocation through S200 is completed, the processor (110) checks whether there is a first beverage among the first beverages that has not yet been allocated for production. (S270)

[0135] The processor (110) assigns the manufacturing machine (150) to make a reservation for the manufacturing of a beverage not assigned in S200. (S300)

[0136] In detail, the processor (110) assigns a production machine (150) to reserve the production of the unassigned first beverage based on the difficulty of producing the unassigned first beverage and the expected time when the production machine (150) producing another beverage is expected to switch to an available state.

[0137] In the embodiment of the present disclosure, checking whether the manufacturing machine (150) is capable of manufacturing a beverage means checking whether the manufacturing machine (150) is a device that is functionally capable of manufacturing the beverage, and checking whether the manufacturing machine (150) is available means checking whether the manufacturing machine (150) is a device that is capable of manufacturing the beverage and is currently available or is manufacturing a beverage for a previous order.

[0138] If a second integrated order number is received while the production of the first beverage included in the first integrated order number is not completed, the processor (110) performs the production assignment of the second beverage included in the second integrated order number.

[0139] The processor (110) checks whether the manufacturing machine (150) capable of manufacturing the second beverage included in the second integrated order number is currently available. (S400)

[0140] At this time, if there are multiple beverage orders included in the second integrated order number, the processor (110) can also assign manufacturing for the second beverage included in the second integrated order number using parallel manufacturing logic.

[0141] If a manufacturing machine (150) capable of manufacturing a second beverage is currently available, the processor (110) performs a pre-assignment to manufacture the second beverage on the manufacturing machine (150).

[0142] And, the processor (110) performs assignment to the manufacturing machine (150) so that the manufacturing of the unassigned second beverage is reserved based on the manufacturing difficulty of each second beverage among the second beverages that is not assigned by the above-mentioned prior assignment and the expected time when the manufacturing machine (150) is expected to be switched to an available state. (S450)

[0143] In one embodiment, the processor (110) may perform an assignment so that a beverage other than coffee is prepared first among the beverages. Additionally, the processor (110) may determine the assignment order based on the type of syrup used in the beverage.

[0144] In one embodiment, the processor (110) may perform beverage preparation assignments to prepare beverages in the following order: a beverage using refrigerated syrup, a beverage using room temperature syrup, and a beverage without syrup.

[0145] In one embodiment, if the production of a specific beverage fails, the processor (110) can control the beverage to be discarded, the status of the production machine (150) that produced the beverage to be checked after a preset time (e.g., 10 seconds), and the beverage to be produced again immediately.

[0146] At this time, if the processor (110) determines that the status of the manufacturing machine (150) that manufactured the beverage is not normal, it may request that the beverage be manufactured immediately or in the next turn by giving priority to another manufacturing machine (150) capable of manufacturing the beverage.

[0147] Referring to FIG. 7, a method for efficiently utilizing a beverage manufacturing device (100) a robot (140), a storage unit (170), and a pickup unit (180) is illustrated.

[0148] The processor (110) checks the status of the robot (140) at preset intervals. (S500)

[0149] In detail, the processor (110) checks at preset intervals whether the robot (140) is manufacturing a beverage, transporting a beverage for manufacturing, transporting a completed beverage to a storage unit (170), or is in a standby state.

[0150] When the robot (140) is in standby mode, the processor (110) checks whether there is a beverage stored in the storage unit (170). (S520)

[0151] If there is a beverage stored in the storage unit (170), the processor (110) checks whether there are N or more currently available pickup units (180). (S540)

[0152] The processor (110) controls the robot (140) to move at least one beverage from the storage unit (170) to the pickup unit (180) when there are N or more currently available pickup units (180). (S560)

[0153] In an additional embodiment of the above process, the processor (110) can control the robot (140) to move the beverage expected to be most quickly picked up among the beverages stored in the storage unit (170) to the pickup unit (180).

[0154] In one embodiment, the processor (110) may control the robot (140) to preemptively move the beverage with the earliest pickup number from the storage unit (170) to the pickup unit (180).

[0155] In one embodiment, when an order is received from a terminal (400), the processor (110) may obtain location information of the terminal (400) and calculate the time the customer will arrive at the store based on the location information of the terminal (400). In addition, the processor (110) may control the robot (140) to move the beverage, among the beverages stored in the storage unit (170), which is determined to have the fastest expected arrival time for the customer, to the pickup unit (180).

[0156] In one embodiment, the processor (110) can recognize a terminal (400) entering the store through a sensor unit installed in the store, and control a robot (140) to move a beverage ordered from the terminal (400) entering the store from a storage unit (170) to a pickup unit (180).

[0157] The beverage manufacturing device (100) according to the embodiment of the present disclosure can efficiently operate the robot (140) by moving the beverage in the storage unit (170) to the pickup unit (180) in advance when the robot (140) is in a standby state through the above process.

[0158] Figure 8 is a drawing illustrating a detailed process for manufacturing a beverage including multiple manufacturing processes.

[0159] Although there are beverages that are manufactured using a single manufacturing machine (150), there are beverages that include multiple different manufacturing processes and thus move between different manufacturing machines (150) to be manufactured, and the beverage manufacturing device (100) can perform a process such as that shown in FIG. 8.

[0160] In one embodiment, when manufacturing a beverage that includes a plurality of different manufacturing processes, the processor (110) may control the robot (140) to move the beverage from the current manufacturing process to a manufacturing machine (150) or a separate manufacturing space to proceed with the next manufacturing process.

[0161] At this time, a separate manufacturing space means a space for performing a manufacturing process performed by a robot (140) without requiring a manufacturing machine (150).

[0162] If a specific manufacturing machine (150) for performing the next manufacturing process is not currently available, the processor (110) maintains the beverage in its current location (e.g., manufacturing machine (150), manufacturing space) and moves the beverage when the specific manufacturing machine (150) becomes available. At this time, if the current manufacturing process for beverage A has been completed in the first manufacturing machine (150), but the second manufacturing machine (150) that must perform the next manufacturing process is not available and the first manufacturing machine (150) must be used to manufacture another beverage B, the processor (110) may temporarily move beverage A to a storage unit (170) to manufacture beverage B. In addition, the processor (110) may control the robot (140) to move beverage A from the storage unit (170) to the second manufacturing machine (150) when the second manufacturing machine (150) becomes available.

[0163] The processor (110) checks whether the beverage to be manufactured includes multiple manufacturing processes. (S810)

[0164] The first manufacturing process in the first manufacturing machine of the beverage is completed. (S820)

[0165] The processor (110) checks whether the second manufacturing machine for the second manufacturing process of the beverage is currently available for use. (S830)

[0166] At this time, the processor (110) controls the robot to move the beverage to the second manufacturing machine if the second manufacturing machine is available.

[0167] The processor (110) determines whether the first manufacturing machine must be used to manufacture the next beverage. (S840)

[0168] At this time, if the first manufacturing machine must be used to manufacture the next beverage, the processor (110) moves the beverage to the storage unit (170) and moves the next beverage to the first manufacturing machine.

[0169] If the first manufacturing machine does not need to be used to manufacture the next beverage, the processor (110) keeps the beverage in its current position. (S850)

[0170] When the second manufacturing machine is switched to an available state, the processor (110) moves the beverage to the second manufacturing machine. (S860)

[0171] When the second manufacturing process of the beverage in the second manufacturing machine is completed, the processor (110) verifies whether all manufacturing processes of the beverage are completed. (S870)

[0172] The processor (110) controls the robot to move the beverage to the storage unit when all manufacturing processes of the beverage are completed.

[0173] Processor (110) If all manufacturing processes of the beverage are not completed, the third manufacturing process of the beverage is performed. (S880)

[0174] Referring to FIGS. 9 to 13, it is illustrated that a robot (140) moves a beverage to a manufacturing machine (150) corresponding to each manufacturing process to manufacture the beverage.

[0175] And, when a customer requests to pick up a beverage through the pickup module (160), the beverage is moved to the pickup stand (180) and the pickup door (190) is opened to become ready for pickup.

[0176] In one embodiment, the beverage manufacturing device (100) may include a longitudinal display portion on the upper side of the pickup door (190).

[0177] When a pickup request is completed through the pickup module (160), the processor (110) can open the pickup door (190) of the pickup stand (180) where the corresponding beverage is located and output information indicating the location of the pickup stand (180) through the display unit. For example, the processor (110) can provide the user with the enjoyment of the video by playing a video moving from one side of the display unit to the location of the pickup stand (180) while informing the user of the location of the pickup stand (180).

[0178] The method according to one embodiment of the present disclosure described above can be implemented as a program (or application) and stored in a medium to be executed in combination with a hardware server.

[0179] The above-described program may include codes coded in a computer language, such as C, C++, JAVA, or machine language, that can be read by the processor (CPU) of the computer through the device interface of the computer, so that the computer reads the program and executes the methods implemented as a program. Such codes may include functional codes related to functions that define functions necessary for executing the methods, and may include control codes related to execution procedures necessary for the processor of the computer to execute the functions according to a predetermined procedure. In addition, such codes may further include memory reference-related codes regarding which location (address address) of the internal or external memory of the computer should reference additional information or media necessary for the processor of the computer to execute the functions. In addition, if the processor of the computer needs to communicate with any other computer or server located remotely in order to execute the functions, the code may further include communication-related code regarding how to communicate with any other computer or server located remotely using the communication module of the computer, and what information or media to send and receive during communication.

[0180] The above storage medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, examples of the storage medium include, but are not limited to, ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage device. That is, the program can be stored in various recording media on various servers that the computer can access or in various recording media on the user's computer. In addition, the medium can be distributed across network-connected computer systems, so that computer-readable code can be stored in a distributed manner.

[0181] The steps of a method or algorithm described in connection with the embodiments of the present disclosure may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination thereof. The software module may reside in a random access memory (RAM), a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, a CD-ROM, or any other form of computer-readable recording medium well known in the art to which the present disclosure pertains.

[0182] While the embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will appreciate that the present disclosure can be implemented in other specific forms without altering the technical spirit or essential features thereof. Therefore, the embodiments described above should be understood to be illustrative in all respects and not restrictive.

Claims

1. At least one storage unit for storing finished food; At least one pickup station where food requested for pickup is stored; A communication unit receiving a unified order number containing an order for at least one food and communicating with a plurality of manufacturing machines; Memory in which at least one instruction is stored; and A processor that controls a plurality of manufacturing machines and robots by executing at least one instruction, The above processor, A plurality of foods included in one or more first integrated order numbers are assigned in descending order of manufacturing difficulty, and if a first manufacturing machine capable of manufacturing a first food among the plurality of foods at the current time is manufacturing a second food among the plurality of foods that has a lower manufacturing difficulty than the first food, the second food is assigned to a second manufacturing machine capable of manufacturing the second food at the current time. Based on the difficulty of manufacturing the unassigned third food among the above multiple foods and the expected time when the first manufacturing machine manufacturing the second food is expected to switch to an available state, the manufacturing of the unassigned third food is assigned to the first manufacturing machine so that the manufacturing of the unassigned third food is reserved. The status of the robot is checked at preset intervals, and the status of the robot includes a state of manufacturing food, a state of transporting food for manufacturing, a state of transporting food that has been manufactured, and a standby state. When the above robot is in the above standby state, it checks whether there is food stored in the above storage unit, If there is food stored in the storage unit and the number of currently available pickup units is greater than or equal to a preset number, the robot is controlled to move at least one of the foods stored in the storage unit to the available pickup unit. When an order is received from a customer's terminal, the location information of the terminal is obtained, and the customer's expected arrival time is calculated based on the obtained location information. Characterized in that the robot is controlled to move the food among the food stored in the storage unit, which is judged to have the fastest expected arrival time for the customer, to the pickup unit. Food preparation device.

2. In paragraph 1, The above processor, When a plurality of first integrated order numbers are received within a preset time range, manufacturing is assigned to the first food included in the plurality of first integrated order numbers. Food preparation device.

3. In paragraph 2, The above processor, If a second integrated order number is received while the manufacturing of the fourth food included in the first integrated order number is not completed, a manufacturing machine capable of manufacturing at the current point in time is pre-assigned to manufacture the fifth food included in the second integrated order number. A method characterized in that an integrated order number received beyond the above-mentioned preset time range is determined as the second integrated order number. Food preparation device.

4. In paragraph 1, The above processor, If another second integrated order number is received while the production of the fourth food included in the first integrated order number is not completed, Characterized in that the production of the unassigned food is assigned to the first manufacturing machine so that the production of the unassigned food is reserved based on the production difficulty of the unassigned food among the fifth foods included in the second integrated order number and the expected time when the first manufacturing machine is expected to be switched to an available state. Food preparation device.

5. In paragraph 1, The above processor, Among the above foods, the allocation is made so that non-coffee beverages are prepared first, characterized in that the order of allocation is determined based on the type of syrup used in the beverage. Food preparation device.

6. In paragraph 5, The above processor, Characterized in that the beverage manufacturing assignment is performed to manufacture beverages in the order of beverages using refrigerated syrup, beverages using room temperature syrup, and beverages not using syrup. Food preparation device.

7. In paragraph 1, The above processor, If the production of a specific food fails, the food that failed to be produced is discarded, and after a preset time, the status of the production machine that produced the discarded food is checked and the discarded food is immediately re-manufactured. Food preparation device.

8. A method for controlling a food manufacturing device that controls a plurality of manufacturing machines and robots, and includes at least one storage unit for storing manufactured food and at least one pickup unit for storing food requested for pickup, A step of assigning a plurality of foods included in one or more first integrated order numbers in order of increasing difficulty in manufacturing; A step of assigning, when a first manufacturing machine capable of manufacturing a first food among the plurality of foods at the present time is manufacturing a second food among the plurality of foods with a lower manufacturing difficulty than the first food, to a second manufacturing machine capable of manufacturing the second food at the present time; A step of assigning the manufacturing of the unassigned third food to the first manufacturing machine based on the manufacturing difficulty of the unassigned third food among the plurality of foods and the expected time at which the first manufacturing machine manufacturing the second food is expected to switch to an available state; A step of checking the status of the robot at preset intervals - the status of the robot includes a state of manufacturing food, a state of transporting food for manufacturing, a state of transporting food that has been manufactured, and a standby state; A step of checking whether there is food stored in the storage unit when the robot is in the standby state; A step of controlling the robot to move at least one food item among the food items stored in the storage unit to the available pickup unit when there is food stored in the storage unit and the number of currently available pickup units is greater than or equal to a preset number; When an order is received from a customer's terminal, a step of obtaining location information of the terminal and calculating the customer's expected arrival time based on the obtained location information; and A step of controlling the robot to move the food, which is determined to have the fastest expected arrival time for the customer among the food stored in the storage unit, to the pickup unit; Method for controlling a food manufacturing device.

Images