KR102682770B1 - Method, device and system for changing design of camping stove based on artificial intelligence - Google Patents

Abstract

According to one embodiment, in the method of changing the design of an artificial intelligence-based camping stove performed by a device, a first stove produced by a first company receives safety certification from the first country and is sold in the first country. If confirmed to exist, obtaining a first list, which is a list of safety certification items that must be verified in order to be sold in the first country; Upon receiving an order request for importing the first stove and selling it in a second country from a second company terminal, obtaining a second list, which is a list of safety certification items that must be verified for sale in the second country; Comparing the first list and the second list to analyze whether there are items that require additional verification to sell the first stove in the second country; If it is analyzed that additional verification of the first item is required to sell the first stove in the second country, confirming a first condition that is a condition for passing the first item; determining whether the first stove satisfies the first condition based on detailed information about the first stove; If it is determined that the first stove does not meet the first condition, matching detailed information of the first stove and setting information of the first condition to generate first matching information; applying the first matching information to an artificial intelligence model and selecting, based on the output of the artificial intelligence model, a part that needs to be changed in the first stove to satisfy the first condition; If the first part is selected as a part that needs to be changed to meet the first condition in the first stove, it is recommended that a change in the first part be necessary to export the first stove to the second country. generating a design change strategy for the first stove; And an artificial intelligence-based method of changing the design of a camping stove is provided, including providing a design change strategy of the first stove to a first company terminal.

Description

Method, device and system for changing the design of an artificial intelligence-based camping stove {METHOD, DEVICE AND SYSTEM FOR CHANGING DESIGN OF CAMPING STOVE BASED ON ARTIFICIAL INTELLIGENCE}

The examples below relate to technology for changing the design of a camping stove based on artificial intelligence.

In order to sell a stove in a specific country, sales can only be permitted after obtaining safety certification from that country. For example, in order to sell a stove in Korea, you must obtain KC certification to be allowed to sell the stove.

Because the laws related to safety certification are different for each country, the items that must be verified for safety certification are bound to be different, and since the safety certification items are different for each country, when exporting a stove, safety certification must be obtained for each country. There is the inconvenience of having to individually review whether it is possible.

In addition, if it is determined that safety certification will not be obtained in the country to which the stove is to be exported, the stove manufacturer must review for each country how to change the design of the stove and export it, which poses difficulties.

Therefore, there is an increasing demand to receive design change strategies on whether safety certification can be obtained in the country to which the export is intended and how to change the design of the stove if safety certification is not obtained, and research on related technologies is increasing. It is required.

Korean Patent No. 10-2456676 Korean Patent No. 10-1669937 Korean Patent Publication No. 10-2020-0089485 Korean Patent Publication No. 10-2017-0079196

According to one embodiment, the purpose is to provide a method, device, and system for changing the design of a camping stove based on artificial intelligence.

The object of the present invention is not limited to the object mentioned above, and other objects not mentioned can be clearly understood from the description below.

According to one embodiment, in the method of changing the design of an artificial intelligence-based camping stove performed by a device, a first stove produced by a first company receives safety certification from the first country and is sold in the first country. If confirmed to exist, obtaining a first list, which is a list of safety certification items that must be verified in order to be sold in the first country; Upon receiving an order request for importing the first stove and selling it in a second country from a second company terminal, obtaining a second list, which is a list of safety certification items that must be verified for sale in the second country; Comparing the first list and the second list to analyze whether there are items that require additional verification to sell the first stove in the second country; If it is analyzed that additional verification of the first item is required to sell the first stove in the second country, confirming a first condition that is a condition for passing the first item; determining whether the first stove satisfies the first condition based on detailed information about the first stove; If it is determined that the first stove does not meet the first condition, matching detailed information of the first stove and setting information of the first condition to generate first matching information; applying the first matching information to an artificial intelligence model and selecting, based on the output of the artificial intelligence model, a part that needs to be changed in the first stove to satisfy the first condition; If the first part is selected as a part that needs to be changed to meet the first condition in the first stove, it is recommended that a change in the first part be necessary to export the first stove to the second country. generating a design change strategy for the first stove; And an artificial intelligence-based method of changing the design of a camping stove is provided, including providing a design change strategy of the first stove to a first company terminal.

The step of analyzing whether there is an item requiring additional verification to sell the first stove in the second country includes comparing the first list and the second list, and determining that the first item is included in the first list. If it is confirmed that the first item is included only in the second list and not included in the second list, analyzing the first item as an item requiring additional verification; And when, as a result of comparing the first list and the second list, it is confirmed that the passing conditions of the first item included in the first list and the passing conditions of the first item included in the second list are different. , It may include the step of analyzing the first item as an item requiring additional verification.

The step of generating a design change strategy for the first stove recommending that changes to the first component are necessary to export the first stove to the second country may include obtaining a safety certification of the second stove from the second country. If it is confirmed that it is being sold in the second country, determining that a design change strategy for the first stove is possible using the second stove; When the first stove is sold in the first country, it is confirmed that the first product is sold with the first part installed, and when the second stove is sold in the second country, the first product is installed and sold with the first part. 2 Confirming that the product is installed and sold; and generating a design change strategy for the first stove recommending changing the first component from the first product to the second product in order to export the first stove to the second country.

According to one embodiment, it will help export stoves to each country by providing a design change strategy on whether safety certification can be obtained in the country to which you want to export and how to change the design of the stove if safety certification is not obtained. There is a possible effect.

Meanwhile, the effects according to the embodiments are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below.

Figure 1 is a diagram schematically showing the configuration of a system according to an embodiment.
Figure 2 is a flow chart to explain the process of changing the design of a camping stove based on artificial intelligence according to an embodiment.
FIG. 3 is a flowchart illustrating a process for creating a design change strategy for a first stove using a second stove sold in a second country according to an embodiment.
Figure 4 is a flowchart illustrating a process for creating a design change strategy for the first stove by selecting a product to be installed on the first stove according to an embodiment.
Figure 5 is a flowchart illustrating a process for transmitting a notification message requesting the supply of a replacement product according to an embodiment.
Figure 6 is a flowchart illustrating a process for transmitting a notification message requesting distribution of the supply of a substitute product through a plurality of suppliers according to an embodiment.
Figure 7 is an exemplary diagram of the configuration of a device according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the attached drawings. However, various changes can be made to the embodiments, so the scope of the patent application is not limited or limited by these embodiments. It should be understood that all changes, equivalents, or substitutes for the embodiments are included in the scope of rights.

Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosed form, and the scope of the present specification includes changes, equivalents, or substitutes included in the technical spirit.

Terms such as first or second may be used to describe various components, but these terms should be interpreted only for the purpose of distinguishing one component from another component. For example, a first component may be named a second component, and similarly, the second component may also be named a first component.

When a component is referred to as being “connected” to another component, it should be understood that it may be directly connected or connected to the other component, but that other components may exist in between.

The terms used in the examples are for descriptive purposes only and should not be construed as limiting. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the embodiments belong. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted in an ideal or excessively formal sense unless explicitly defined in the present application. No.

In addition, when describing with reference to the accompanying drawings, identical components will be assigned the same reference numerals regardless of the reference numerals, and duplicate descriptions thereof will be omitted. In describing the embodiments, if it is determined that detailed descriptions of related known technologies may unnecessarily obscure the gist of the embodiments, the detailed descriptions are omitted.

Embodiments may be implemented in various types of products such as personal computers, laptop computers, tablet computers, smart phones, televisions, smart home appliances, intelligent vehicles, kiosks, and wearable devices.

In an embodiment, an artificial intelligence (AI) system is a computer system that implements human-level intelligence, and unlike existing rule-based smart systems, it is a system in which machines learn and make decisions on their own. As artificial intelligence systems are used, recognition rates improve and sellers' tastes can be more accurately understood, and existing rule-based smart systems are gradually being replaced by deep learning-based artificial intelligence systems.

Artificial intelligence technology consists of machine learning and element technologies using machine learning. Machine learning is an algorithmic technology that classifies/learns the characteristics of input data on its own, and elemental technology is a technology that mimics the functions of the human brain such as cognition and judgment by utilizing machine learning algorithms such as deep learning, including linguistic understanding and visual It consists of technical areas such as understanding, reasoning/prediction, knowledge expression, and motion control.

The various fields where artificial intelligence technology is applied are as follows. Linguistic understanding is a technology that recognizes and applies/processes human language/characters and includes natural language processing, machine translation, conversation systems, question and answer, and voice recognition/synthesis. Visual understanding is a technology that recognizes and processes objects like human vision, and includes object recognition, object tracking, image search, person recognition, scene understanding, spatial understanding, and image improvement. Inferential prediction is a technology that judges information to make logical inferences and predictions, and includes knowledge/probability-based inference, optimization prediction, preference-based planning, and recommendation. Knowledge expression is a technology that automatically processes human experience information into knowledge data, and includes knowledge construction (data creation/classification) and knowledge management (data utilization). Motion control is a technology that controls the autonomous driving of vehicles and the movement of robots, and includes motion control (navigation, collision, driving), operation control (behavior control), etc.

Generally, in order to apply machine learning algorithms to real life, learning is performed using a trial and error method due to the nature of the basic methodology of machine learning. In particular, deep learning requires hundreds of thousands of iterations. It is impossible to execute this in an actual physical external environment, so instead, the actual physical external environment is virtually implemented on a computer and learning is performed through simulation.

Figure 1 is a diagram schematically showing the configuration of a system according to an embodiment.

Referring to FIG. 1, a system according to an embodiment may include a plurality of company terminals 100 and devices 200 that can communicate with each other through a communication network.

First, a communication network can be configured regardless of the communication mode, such as wired or wireless, and can be implemented in various forms to enable communication between servers and between servers and terminals.

Each of the plurality of company terminals 100 may be implemented as a computing device with a communication function, and may be implemented as, for example, a mobile phone, a desktop PC, a laptop PC, a tablet PC, a smartphone, etc., but is not limited thereto. It can also be implemented as various types of communication devices that can be connected to external servers.

The plurality of company terminals 100 are terminals used by representatives of each company, such as the first company terminal 110 used by the first company's staff, the second company terminal 120 used by the second company's staff, etc. may include. At this time, the first company is a company that produces stoves, and the second company is a company that imports and sells stoves.

Each of the plurality of company terminals 100 may be configured to perform all or part of the calculation function, storage/reference function, input/output function, and control function of a typical computer. A plurality of company terminals 100 may be configured to communicate with the device 200 in a wired or wireless manner.

Each of the plurality of company terminals 100 is connected to a web page operated by a person or organization providing services using the device 200, or is developed and distributed by a person or organization providing services using the device 200. An application can be installed. Each of the plurality of company terminals 100 may be linked with the device 200 through a web page or application.

Each of the plurality of company terminals 100 can access the device 200 through a web page or application provided by the device 200.

The device 200 may be its own server owned by a person or organization that provides services using the device 200, a cloud server, or a p2p (peer-to-peer) set of distributed nodes. It may be possible. The device 200 may be configured to perform all or part of the calculation function, storage/reference function, input/output function, and control function of a typical computer. The device 200 may be equipped with at least one artificial intelligence model that performs an inference function.

The device 200 may be configured to communicate wired or wirelessly with a plurality of company terminals 100, control the operation of each of the plurality of company terminals 100, and display certain information on the screen of each of the plurality of company terminals 100. You can control whether to display it or not.

The device 200 may be implemented as a server that provides management services such as stove production, export, and design change, and may provide a platform for stove management.

Meanwhile, for convenience of explanation, only the first company terminal 110 and the second company terminal 120 are shown in FIG. 1 among the plurality of company terminals 100, but the number of terminals may vary depending on the embodiment. . As long as the processing capacity of the device 200 allows, the number of terminals is not particularly limited.

According to one embodiment, when a first company produces a first stove, which is a camping stove, and the first stove is sold in the first country, a second company operating in a second country other than the first country You can receive orders for the first stove from the company. At this time, the safety certification items that must be verified for stove sales may vary from country to country, and only when all safety certification items are certified can sales of stoves be permitted.

Accordingly, we collect data on each country's stove-related certification laws, safety certification items, etc., analyze whether there are any changed certification items based on the certification items of the country in which they are currently sold, and as a result of the analysis, determine whether there are any changed items. If confirmed, it is possible to analyze whether any part changes are necessary to pass the changed item, and as a result of the analysis, a design change strategy for the stove can be created that recommends which parts of the stove should be changed.

According to one embodiment, the device 200 selects which part of the stove needs to be changed in order to pass the changed item based on artificial intelligence and provides recommendation information recommending the selected part to the representative of the first company. You can.

In the present invention, artificial intelligence (AI) refers to technology that imitates human learning ability, reasoning ability, perception ability, etc. and implements this with a computer, and includes concepts such as machine learning and symbolic logic. may include. Machine Learning (ML) is an algorithmic technology that classifies or learns the characteristics of input data on its own. Artificial intelligence technology is a machine learning algorithm that analyzes input data, learns the results of the analysis, and makes judgments or predictions based on the results of the learning. Additionally, technologies that mimic the functions of the human brain, such as cognition and judgment, using machine learning algorithms can also be understood as the category of artificial intelligence. For example, technical fields such as verbal understanding, visual understanding, reasoning/prediction, knowledge representation, and motion control may be included.

Machine learning can refer to the process of training a neural network model using experience processing data. Machine learning can mean that computer software improves its own data processing capabilities. A neural network model is built by modeling the correlation between data, and the correlation can be expressed by a plurality of parameters. A neural network model extracts and analyzes features from given data to derive correlations between data. Repeating this process to optimize the parameters of the neural network model can be called machine learning. For example, a neural network model can learn the mapping (correlation) between input and output for data given as input-output pairs. Alternatively, a neural network model may learn the relationships by deriving regularities between given data even when only input data is given.

An artificial intelligence learning model or neural network model may be designed to implement the human brain structure on a computer, and may include a plurality of network nodes with weights that simulate neurons of a human neural network. A plurality of network nodes may have a connection relationship with each other by simulating the synaptic activity of neurons in which neurons exchange signals through synapses. In an artificial intelligence learning model, multiple network nodes are located in layers of different depths and can exchange data according to convolutional connection relationships. The artificial intelligence learning model may be, for example, an artificial neural network model (Artificial Neural Network), a convolution neural network (CNN) model, etc. As an example, an artificial intelligence learning model may be machine-learned according to methods such as supervised learning, unsupervised learning, and reinforcement learning. Machine learning algorithms for performing machine learning include Decision Tree, Bayesian Network, Support Vector Machine, Artificial Neural Network, and Ada-boost. , Perceptron, Genetic Programming, Clustering, etc. can be used.

Among them, CNN is a type of multilayer perceptrons designed to use minimal preprocessing. CNN consists of one or several convolution layers and general artificial neural network layers on top of them, and additionally utilizes weights and pooling layers. Thanks to this structure, CNN can fully utilize input data with a two-dimensional structure. Compared to other deep learning structures, CNN shows good performance in both video and audio fields. CNNs can also be trained via standard back propagation. CNNs have the advantage of being easier to train and using fewer parameters than other feedforward artificial neural network techniques.

Convolutional networks are neural networks that contain sets of nodes with bound parameters. The increasing size of available training data and the availability of computational power, combined with algorithmic advances such as piecewise linear unit and dropout training, have led to significant improvements in many computer vision tasks. For extremely large data sets, such as those available for many tasks today, overfitting is not critical, and increasing the size of the network improves test accuracy. Optimal use of computing resources becomes a limiting factor. For this purpose, distributed, scalable implementations of deep neural networks can be used.

Figure 2 is a flow chart to explain the process of changing the design of a camping stove based on artificial intelligence according to an embodiment.

Referring to FIG. 2, first, in step S201, the device 200 can confirm that the first stove produced by the first company has received safety certification from the first country and is being sold in the first country. Here, the first stove is a camping stove, produced by the first company, and sold in the first country.

Specifically, if the first stove produced by the first company has received safety certification from the first country and is being sold in the first country, the device 200 receives sales information of the first stove from the first company terminal 110. The information can be received, and based on the sales information of the first stove, it can be confirmed that the first stove is being sold in the first country. Here, the sales information of the first stove is information indicating in which country the first stove is sold and by how much.

In other words, in order to sell a stove in the first country, you must pass the safety certification items designated by the first country and receive safety certification. Therefore, if the first stove is sold in the first country, the first stove is sold in the first country. It can be confirmed that safety certification has already been received, and sales of the first stove may be permitted in the first country.

In step S202, the device 200 may obtain a first list, which is a list of safety certification items that must be verified in order to be sold in the first country. At this time, the device 200 may query information stored in the database and obtain the first list from the database. For this purpose, the database stores a list of safety certification items divided by country.

Specifically, when it is confirmed that the first stove produced by the first company has received safety certification from the first country and is being sold in the first country, the device 200 searches the information stored in the database and sells the first stove in the first country. A list of safety certification items that must be verified for certification can be extracted, and the extracted list can be set as the first list.

In step S203, the device 200 may receive an order request from the second company terminal 120 to import the first stove and sell it in the second country. At this time, the order request is a request to place an order for the first stove in order to import the first stove produced in the first country and sell it in the second country.

In step S204, the device 200 may obtain a second list, which is a list of safety certification items that must be verified in order to be sold in the second country. At this time, the device 200 may query the information stored in the database and obtain the second list from the database.

Specifically, when the device 200 receives an order request from the second company terminal 120 to import the first stove and sell it in the second country, it searches the information stored in the database and prepares the stove for sale in the second country. A list of safety certification items that must be verified can be extracted, and the extracted list can be set as the second list.

In step S205, the device 200 may compare the first list and the second list to analyze whether there are items that require additional verification in order to sell the first stove in the second country.

Specifically, the device 200 compares the first list and the second list, and as a result of comparing the first list and the second list, the first item is not included in the first list but is included only in the second list. If confirmed to exist, the first item can be analyzed as an item requiring additional verification.

For example, if the first list includes the second item and the third item, and the second list includes the first item, the second item, and the third item, the device 200 includes the first list and the third item. As a result of comparing the second list, it is confirmed that the first item is not included in the first list but is included only in the second list, so the first item can be analyzed as an item requiring additional verification.

In addition, the device 200 compares the first list and the second list, and determines that the passing conditions of the first item included in the first list are different from the passing conditions of the first item included in the second list. In this case, the first item can be analyzed as an item requiring additional verification.

For example, if the first item is an item to check whether a heat sensor is attached, the device 200 checks the passing condition of the first item included in the first list, and as a result, one or more heat sensors are detected. If it is attached, it can be confirmed as a passing condition, and as a result of checking the passing condition of the first item included in the second list, if two or more heat detection sensors are attached, it can be confirmed as a passing condition, and it is included in the first list. Since it is confirmed that the passing conditions of the first item included in the second list are different from the passing conditions of the first item included in the second list, the first item can be analyzed as an item requiring additional verification.

In step S206, the device 200 may determine whether there are any items that require additional verification as a result of analyzing whether there are any items that require additional verification in order to sell the first stove in the second country.

If it is determined that there are no items requiring additional verification in step S206, in step S207, the device 200 sends a notification message to the first company terminal 110 indicating that export to the second country is possible without changing the design of the first stove. It can be sent to .

That is, as a result of comparing the first list and the second list, the device 200 determines that the items included in the first list and the items included in the second list are the same and the passing conditions for each item are also the same. , Even without changing the design of the first stove, it can be determined that the first stove sold in the first country can be sold in the second country as is without any design changes, and to notify this, the design of the first stove has been changed. A notification message informing that export to a second country is possible without a device can be transmitted to the first company terminal 110.

If it is determined that there is an item requiring additional verification in step S206, in step S208, if it is analyzed that additional verification of the first item is required to sell the first stove in the second country, the first item You can check the first condition, which is a condition for passing.

That is, the device 200 can check the first item included in the second list and check the first condition set as a condition for passing the first item.

In step S209, the device 200 may determine whether the first stove satisfies the first condition based on detailed information about the first stove.

Specifically, the device 200 may receive detailed information on the first stove from the first company terminal 110, and determine whether the first stove satisfies the first condition based on the detailed information on the first stove. You can judge. Here, the detailed information about the first stove may include information about the specifications, specifications, and status of products installed for each part, etc. of the first stove.

In other words, the device 200 determines whether the first stove satisfies the first condition by determining the specifications, specifications, and status of products installed for each part, etc., of the first stove, based on the detailed information of the first stove. You can.

In step S210, the device 200 may check whether the first stove satisfies the first condition as a result of determining whether the first stove satisfies the first condition.

If it is confirmed that the first stove satisfies the first condition in step S210, in step S207, the device 200 sends a notification message to the first company terminal indicating that export to the second country is possible without changing the design of the first stove. It can be sent to (110).

That is, if additional verification of the first item is required to sell the first stove in the second country, the device 200 changes the design of the first stove if it is determined that the first stove satisfies the first condition. Even without doing so, it can be determined that the first stove sold in the first country can be sold in the second country as is without design changes, and to notify this, it can be exported to the second country without changing the design of the first stove. A notification message indicating this may be transmitted to the first company terminal 110.

If it is confirmed in step S210 that the first stove does not meet the first condition, in step S211, the device 200 matches the detailed information of the first stove and the setting information of the first condition to generate first matching information. can do. Here, the detailed information of the first stove may include information about the specifications, specifications, and product status of each part of the first stove, and the setting information of the first condition may include the contents of the first item and the satisfaction of the first condition. It may include information on standards, etc.

In step S212, the device 200 may apply the first matching information to a pre-trained artificial intelligence model. Here, the artificial intelligence model receives matching information that matches the detailed information of the stove and the condition setting information, analyzes the parts that need to be changed to meet the conditions in the stove, and selects the parts that need to be changed. It may be an algorithm that outputs information about.

In other words, the artificial intelligence model selects the parts that need to be changed to meet the conditions in the stove, considering the condition of the stove and the criteria for meeting the conditions, based on matching information that matches the detailed information of the stove and the condition setting information. You can.

For example, when first matching information that matches the detailed information of the first stove and the setting information of the first condition is input, the artificial intelligence model considers the state of the first stove and the satisfaction criteria of the first condition, 1 It is possible to analyze which part needs to be changed to satisfy the first condition in the first stove, and if it is analyzed that the first part needs to be changed to meet the first condition in the first stove, the first part is indicated. The output value can be output. Here, the first part is a specific part of the first stove and may be, for example, a screw, sensor, coil, resistor, switch, etc.

In step S213, the device 200 may select a part that needs to be changed to satisfy the first condition in the first stove based on the output of the artificial intelligence model.

For example, the device 200 applies the first matching information to the artificial intelligence model, checks the output of the artificial intelligence model, and if the output value is confirmed to be 1, a change is made in the first stove to satisfy the first condition. If the required part is selected as the first part and the output value is confirmed to be 2, the part that needs to be changed to satisfy the first condition in the first stove can be selected as the second part.

According to one embodiment, the artificial intelligence model can be trained to analyze which parts need to be changed to meet the conditions in the stove through matching information that matches the detailed information of the stove and the setting information of the conditions. Through this, the artificial intelligence model can take into account the condition of the stove and the criteria for meeting the conditions, analyze which parts need to be changed in the stove to meet the conditions, and output information about the parts that need to be changed. To this end, the artificial intelligence model may be trained to analyze which parts need to be changed to meet the conditions in the stove.

The learning device in which the artificial intelligence model is learned may be the same device as the device 200 for selecting parts that need to be changed using the learned artificial intelligence model, or it may be a separate device. Below, the process by which the artificial intelligence model is learned is explained.

First, the learning device can generate input to be input to the artificial intelligence model. At this time, the learning device may generate input based on matching information that matches the detailed information of the stove and the condition setting information in order to input it into the artificial intelligence model.

Specifically, the learning device may perform a preprocessing process on matching information. The pre-processed matching information can be used as input to the artificial intelligence model, or the input of the artificial intelligence model can be created through normal processing to remove unnecessary information.

Next, the learning device can apply input to the artificial intelligence model.

The artificial intelligence model may be an artificial intelligence model learned according to reinforcement learning. The artificial intelligence model may be a Q-Network, Deep Q-Network (DQN), or relational network (RN) structure suitable for outputting abstract inference through reinforcement learning.

Artificial intelligence models learned through reinforcement learning can be updated and optimized by reflecting evaluations on various rewards. For example, the artificial intelligence model can be updated and optimized through first and second rewards.

For example, the first compensation can be increased by classifying the part as a part that needs to be changed when the performance of a specific part affects the satisfaction criteria of the condition, and the second compensation can be increased if the performance of a specific part affects the satisfaction criteria of the condition. This can be increased by classifying the part as not requiring change when it is not affecting it.

Next, the learning device can obtain output from the artificial intelligence model.

The output of the artificial intelligence model may be information about parts selected as parts requiring change. At this time, the artificial intelligence model can select parts that need to be changed to meet the conditions in the stove through matching information and output information about the selected parts.

Next, the learning device can evaluate the output of the artificial intelligence model and pay rewards.

Evaluation of the output of the artificial intelligence model can be divided into first and second rewards. When the performance of a specific part affects the satisfaction criteria of a condition, the learning device awards the greater the first reward as it classifies the part as a part requiring change, and determines whether the performance of a specific part affects the satisfaction criteria of the condition. The more the part is classified as a part that does not require change, the more secondary compensation can be awarded.

Next, the learning device can update the artificial intelligence model based on the evaluation.

The learning device sets certain states so that the expected value of the sum of rewards is maximized in the environment where the artificial intelligence model selects the parts that need to be changed to meet the conditions in the stove. The artificial intelligence model can be updated through the process of optimizing the policy that determines the actions to be taken.

For example, if there is a problem with selecting the first part as a part that needs to be changed to meet the first condition in the first stove, the learning device includes information indicating that there is a problem with selecting the first part. AI generates first learning data and applies the first learning data to the artificial intelligence model so that the first part is not selected as a part that needs to be changed to meet the first condition in a stove similar to the first stove. Through the process of learning the model, the artificial intelligence model can be updated.

Meanwhile, the process of optimizing the policy can be accomplished through estimating the maximum expected value of the sum of rewards or the maximum value of the Q-function, or estimating the minimum value of the loss function of the Q-function. Estimation of the minimum value of the loss function can be done through stochastic gradient descent (SGD), etc. The process of optimizing the policy is not limited to this, and various optimization algorithms used in reinforcement learning can be used.

The learning device can gradually update the artificial intelligence model by repeating the learning process of the artificial intelligence model as described above.

Specifically, in selecting the parts that need to be changed to meet the conditions in the stove, the learning device takes into account the condition of the stove and the criteria for meeting the conditions, and analyzes which parts need to be changed to meet the conditions in the stove. , you can select the parts that need to be changed and learn an artificial intelligence model that outputs information about the selected parts.

In other words, when the learning device analyzes the parts that need to be changed to meet the conditions in the stove through matching information, it reflects reinforcement learning through the first and second rewards, etc. and adjusts the analysis criteria to create an artificial intelligence model. It can be learned.

In step S214, if the first part is selected as a part that needs to be changed to satisfy the first condition in the first stove, the device 200 determines whether the first part needs to be changed in order to export the first stove to the second country. A design change strategy for the first stove can be created that recommends what is needed.

That is, if the first part is selected as a part that needs to be changed to satisfy the first condition in the first stove, the device 200 satisfies the first condition and changes the first part in the first stove. It can be determined that it is possible to pass the item, and since safety certification from the second country can be obtained only after passing the first item, it can be determined that a change in the first part is necessary to export the first stove to the second country. Through this, it is possible to create a design change strategy for the first stove that recommends changes to the first component. At this time, a detailed description of which product the first component will be changed to will be described later with reference to FIGS. 3 and 4.

In step S215, the device 200 may provide a design change strategy for the first stove to the first company terminal 110. At this time, the design change strategy of the first stove may include information about the first list, the second list, the first item, the first condition, and the first part.

FIG. 3 is a flowchart illustrating a process for creating a design change strategy for a first stove using a second stove sold in a second country according to an embodiment.

Referring to FIG. 3, first, in step S301, the device 200 can confirm whether there is a stove being sold in the second country by receiving safety certification from the second country.

Specifically, the device 200 may collect information on stoves sold in the second country from an external server or database and check whether there is a stove sold in the second country based on the collected stove information.

If it is confirmed in step S301 that there are no stoves being sold in the second country, step S401 may be performed, and a detailed description regarding this will be described later with reference to FIG. 4.

If it is confirmed in step S301 that there is a stove that has received safety certification from the second country and is being sold in the second country, in step S302, the device 200 determines that the second stove has received safety certification from the second country and is sold in the second country. If it is confirmed that it is being sold, it may be determined that a design change strategy for the first stove using the second stove is possible.

In other words, in order to sell a stove in a second country, you must pass the safety certification items designated by the second country and receive safety certification. Therefore, if a second stove is being sold in a second country, the second stove is sold in the second country. It can be confirmed that the device 200 has already received safety certification, and since the second stove has received safety certification from the second country and is being sold in the second country, the design of the first stove can be changed using the second stove. The strategy can be judged to be possible.

In step S303, the device 200 may confirm that the first product is sold with the first component when the first stove is sold in the first country, and when the second stove is sold in the second country, the device 200 may confirm that the first product is sold with the first component. You can see that the second product is being sold as part 1.

For example, if the first component is a heat detection sensor, the device 200 may confirm that the first sensor as a heat detection sensor is mounted on the first stove, based on detailed information of the first stove, and 2 Based on the detailed information of the stove, it can be confirmed that the second sensor is installed as a heat detection sensor in the second stove.

That is, the device 200 can confirm that the first stove equipped with the first product as the first part is sold in the first country, and the second stove equipped with the second product as the first part is sold in the second country. You can check what is being sold here.

At step S304, the device 200 may generate a design change strategy for the first stove that recommends changing the first component from the first product to the second product in order to export the first stove to the second country.

That is, when the first part is selected as a part that needs to be changed to satisfy the first condition in the first stove, the device 200 is installed with the first product as the first part in the first stove, and the second stove is installed in the first stove. A second product is mounted as a first part, and if the first product mounted as a first part on the first stove is changed to the second product using the product mounted on the second stove, the first condition It can be determined that passing the first item is possible by satisfying , and through this, a design change strategy for the first stove that recommends changing the first part from the first product to the second product can be created.

Figure 4 is a flowchart illustrating a process for creating a design change strategy for the first stove by selecting a product to be installed on the first stove according to an embodiment.

Referring to FIG. 4 , first, in step S401, the device 200 may classify products that can be installed as first parts in the first stove into a first group.

Specifically, the device 200 collects product information from an external server or database, identifies products that can be installed as the first part in the first stove based on the collected product information, and groups the confirmed products into the first group. It can be classified as: Here, product information may include information about the type of device that can be installed, installation area, product performance, specifications, specifications, sales price, inventory quantity, product size, etc.

For example, when the first component is a heat detection sensor, the device 200 determines that the first sensor can be mounted from the first stove to the first component, and the second sensor can be mounted from the first stove to the first component. If it is confirmed that installation is possible, the first sensor and the second sensor can be classified into the first group.

In step S402, the device 200 may classify products with better performance than the first product into the second group among the products classified into the first group. At this time, the device 200 may classify products that meet the first condition among the products classified into the first group into the second group.

That is, based on the collected product information, the device 200 checks the performance of each of the products classified into the first group and the performance of the first product, and then determines the performance of the first product among the products classified into the first group. This good product can be classified into the second group. At this time, the device 200 may check the performance of each of the products classified into the first group and classify the products whose performance satisfies the first condition into the second group.

In step S403, the device 200 may assign a higher first score to each of the products classified into the second group as the selling price is lower.

For example, if the third product and the fourth product are classified into the second group, the device 200 gives the third product a first score of 5 when the price of the third product is confirmed to be 500 won. And, if the price of the fourth product is confirmed to be 400 won, a first score of 6 points can be given to the fourth product.

In step S404, the device 200 may assign a higher second score to each of the products classified into the second group as the inventory quantity increases.

For example, if the third product and the fourth product are classified into the second group, the device 200 assigns a second score of 5 to the third product when the inventory quantity of the third product is confirmed to be 500 pieces. And, if the inventory quantity of the fourth product is confirmed to be 600, a second score of 6 points can be given to the fourth product.

In step S405, the device 200 may assign a higher third score to each of the products classified into the second group as the product size becomes smaller.

For example, if the third product and the fourth product are classified into the second group, if the device 200 determines that the product size of the third product is 5cm, it gives the third product a third score of 5 points. And, if the product size of the fourth product is confirmed to be 4cm, a third score of 6 points can be given to the fourth product.

The device 200 may set the maximum value that can be given to each of the first score, second score, and third score to be the same score.

When a first score, a second score, and a third score are respectively assigned to each of the products classified into the second group, the device 200 applies a first weight to each of the assigned first scores, and applies the first weight to each of the assigned first scores. A second weight may be applied to the 2 scores, and a third weight may be applied to the third scores respectively assigned. Here, the first weight may be set to a higher value than the second weight, and the second weight may be set to a higher value than the third weight.

For example, a third product is classified into the second group, and for the third product, the first score is 10 points, the second score is 10 points, the third score is 10 points, and the first weight is 1.3. is set, the second weight is set to 1.2, and the third weight is set to 1.1, the device 200 applies the first weight to the first score and calculates 13 through “X 1.3” You can change the first score from 10 to 13, apply a second weight to the second score, calculate 12 through “X 1.2”, and change the second score from 10 to 12. By applying a third weight to the third score, 11 can be calculated through “X 1.1” and the third score can be changed from 10 to 11 points.

In step S406, the device 200 may calculate the total score by adding up the first score, second score, and third score for each of the products classified into the second group.

In step S407, the device 200 may compare the total scores of each of the products classified into the second group and select the product with the highest total score among the products classified into the second group as the third product.

At step S408, the device 200 may generate a design change strategy for the first stove that recommends changing the first component from the first product to the third product in order to export the first stove to the second country.

That is, when the first part is selected as a part that needs to be changed to meet the first condition in the first stove, the device 200 is installed in the first stove with a first product that does not meet the first condition, Among the products that can be installed as the first part, a product with better performance than the first product is selected, and among the selected products, a third product is selected considering sales price, inventory quantity, and product size, and a third product is selected for the first stove. If the first product installed as part 1 is changed to a third product, it can be determined that the first condition is satisfied through the third product and the first item can be passed, and through this, the first part can be replaced with the first product. A design change strategy for the first stove that recommends changing to a third product can be created.

Figure 5 is a flowchart illustrating a process for transmitting a notification message requesting the supply of a replacement product according to an embodiment.

According to one embodiment, each step shown in FIG. 5 may be performed after step S215.

Referring to FIG. 5, first, in step S501, when it is finally confirmed to change the first part from the first product to a replacement product according to the design change strategy of the first stove, the device 200 moves to the second country. The minimum quantity of substitute products that must be secured in order to export the first stove can be set as the first quantity. Here, the replacement product may be either a second product or a third product.

Specifically, through step S304, a design change strategy for the first stove is generated that recommends changing the first component from the first product to the second product in order to export the first stove to the second country, and through step S215. , After providing the design change strategy of the first stove to the first company terminal 110, the device 200 receives information from the first company terminal 110 about changing the first part from the first product to the second product. Once approval is received, it can be determined that the change of the first part from the first product to the second product according to the design change strategy of the first stove has been finalized, and the minimum required to export the first stove to the second country is The quantity of the second product that must be secured can be set as the first quantity.

In addition, through step S408, a design change strategy of the first stove is generated that recommends changing the first component from the first product to the third product in order to export the first stove to the second country, and through step S215, After providing the design change strategy of the first stove to the first company terminal 110, the device 200 receives approval from the first company terminal 110 to change the first part from the first product to the third product. Upon receipt, it can be determined that the change of the first part from the first product to the third product according to the design change strategy of the first stove has been finally confirmed, and the minimum required amount is required to export the first stove to the second country. The quantity of the third product that must be secured can be set as the first quantity.

In other words, when it is finally determined that the first part is changed from the first product to a replacement product of any one of the second product and the third product according to the design change strategy of the first stove, the device 200 is operated in the second country. The minimum quantity of substitute products that must be secured to export the first stove can be set as the first quantity. At this time, the minimum quantity of replacement products that must be secured may be determined according to the order quantity.

When the device 200 receives an order request for importing a first stove and selling it in a second country from the second company terminal 120, the device 200 can confirm the order quantity through the order request and use the order quantity to determine the first quantity. You can set it.

In step S502, the device 200 may check the first supplier that is set as the first supplier among suppliers that supply alternative products. To this end, the priorities of suppliers are set for each product, and the priorities of suppliers may change periodically depending on product inventory status, contract status with suppliers, etc.

For example, if there are a first supplier, a second supplier, and a third supplier for the second product, the first supplier is set as the first supplier, the second supplier is set as the second supplier, and , when the third supplier is set as the third priority supplier, the device 200 selects one of the suppliers supplying the second product when it is finally confirmed to change the first part from the first product to the second product. You can check the first supply source that is set as the ranked supply source.

In step S503, the device 200 may check the inventory amount of the replacement product stored in the warehouse of the first supplier as the first inventory amount. For this purpose, the database of the device 200 stores warehouse inventory details divided by supplier, and the device 200 can obtain the warehouse details of the first supplier by querying the information stored in the database. Based on the warehouse inventory history, it is possible to check how many replacement products are stored in the warehouse of the first supplier and set the confirmed number as the first inventory.

In step S504, the device 200 may check whether the first inventory quantity is greater than the first quantity.

If it is confirmed in step S504 that the first inventory quantity is greater than the first quantity, in step S505, the device 200 sends a notification message requesting supply of the substitute product to the first company so that the substitute product is supplied through the first supplier. Can be transmitted to the first supplier terminal. To this end, the device 200 may be configured to communicate wired or wirelessly with the first supplier terminal.

That is, if the device 200 determines that the first inventory quantity is greater than the first quantity, the minimum quantity of substitute products that must be secured in order to export the first stove to the second country can be secured only by supply from the first supplier. If it is determined that the substitute product is supplied through the first supplier, a notification message requesting supply of the substitute product to the first supplier may be transmitted to the first supplier terminal.

If it is determined in step S504 that the first inventory quantity is not greater than the first quantity, in step S506, the device 200 may check the second supply source that is set as the second-priority supply source among the supply sources that supply the replacement product.

In step S507, the device 200 may check the inventory amount of the replacement product stored in the warehouse of the second supplier as the second inventory amount. At this time, the device 200 can check the second inventory amount using the same method as the method of checking the first inventory amount.

In step S508, the device 200 may check whether the sum of the first inventory quantity and the second inventory quantity is greater than the first quantity.

If the sum of the first inventory quantity and the second inventory quantity is confirmed to be greater than the first quantity in step S508, in step S509, the device 200 supplies the replacement product through the first supply source and the second supply source. A notification message requesting supply to the first company may be transmitted to the first supplier terminal and the second supplier terminal. To this end, the device 200 may be configured to communicate wired or wirelessly with the second supplier terminal.

That is, if the device 200 determines that the first inventory quantity is not greater than the first quantity, the minimum quantity of substitute products that must be secured to export the first stove to the second country can be secured only by supply from the first supplier. If it is determined that this is not possible, a notification message requesting supply of the substitute product to the first supplier may be transmitted to the first supplier terminal and the second supplier terminal so that the substitute product is supplied through the first supplier and the second supplier. At this time, the substitute product supplied to the first company may be distributed and supplied through the first supplier and the second supplier, and a detailed description regarding this will be described later with reference to FIG. 6.

If it is confirmed in step S508 that the sum of the first inventory quantity and the second inventory quantity is not greater than the first quantity, the device 200 returns to step S506 and is set as the second priority supplier among suppliers supplying alternative products. After confirming the third supply source and confirming the inventory quantity of the substitute product stored in the warehouse of the third supplier as the third inventory quantity, in step S508, the device 200 determines the first inventory quantity, the second inventory quantity, and the third inventory quantity. It is possible to check whether the summed value is greater than the first quantity.

Figure 6 is a flowchart illustrating a process for transmitting a notification message requesting distribution of the supply of a substitute product through a plurality of suppliers according to an embodiment.

Referring to FIG. 6, first, in step S601, the device 200 may calculate the first difference amount by subtracting the first quantity from the sum of the first inventory quantity and the second inventory quantity.

In step S602, the device 200 may check whether the first difference amount is less than the first reference amount. Here, the first reference amount may be set differently depending on the embodiment.

If it is confirmed that the first difference amount is less than the first reference amount in step S602, the device 200 may calculate the third inventory amount as a value obtained by subtracting the first inventory amount from the first quantity in step S603.

In step S604, the device 200 transmits a notification message requesting supply of a replacement product of the first stock amount to the first company to the first supplier terminal, and supplies a replacement product of the third stock amount to the first company. The requested notification message can be transmitted to the second supplier terminal.

If it is confirmed in step S602 that the first difference amount is not less than the first reference amount, in step S605, the device 200 calculates the fourth inventory amount as a value multiplied by the first quantity and the first ratio, and calculates the fourth inventory amount by multiplying the first quantity and the first ratio. The fifth inventory quantity can be calculated by multiplying the ratio by 2. Here, the first ratio may be set differently depending on the embodiment, the second ratio may be set to a lower value than the first ratio, and the sum of the first ratio and the second ratio is 100%.

For example, when the first ratio is set to 60% and the second ratio is set to 40%, if the first quantity is 300, the device 200 produces 180 units calculated through “X 0.6”. can be calculated as the fourth inventory quantity, and 120 units calculated through “X 0.4” can be calculated as the fifth inventory quantity.

In step S606, the device 200 may check whether the first inventory amount is greater than the fourth inventory amount.

If it is confirmed in step S606 that the first inventory amount is greater than the fourth inventory amount, in step S607, the device 200 transmits a notification message requesting that a replacement product for the fourth inventory amount be supplied to the first supplier to the first supplier terminal. And, a notification message requesting that a replacement product of the fifth inventory amount be supplied to the first company may be transmitted to the second supplier terminal.

If it is confirmed in step S606 that the first inventory amount is not greater than the fourth inventory amount, in step S608, the device 200 may calculate the sixth inventory amount as a value obtained by subtracting the first inventory amount from the fourth inventory amount.

In step S609, the device 200 may calculate the seventh inventory amount as the value of adding the fifth inventory amount and the sixth inventory amount.

In step S610, the device 200 transmits a notification message requesting supply of a replacement product of the first stock amount to the first company to the first supplier terminal, and supplies a replacement product of the seventh stock amount to the first company. The requested notification message can be transmitted to the second supplier terminal.

If it is confirmed that the second inventory quantity is greater than the seventh inventory quantity, the device 200 transmits a notification message to the first supplier terminal requesting that a replacement product for the first inventory quantity be supplied to the first company, and replaces the seventh inventory quantity. A notification message requesting that the product be supplied to the first company may be transmitted to the second supplier terminal.

If it is confirmed that the second inventory amount is not greater than the seventh inventory volume, the device 200 calculates the eighth inventory volume by subtracting the second inventory volume from the seventh inventory volume, and supplies a replacement product for the first inventory volume to the first company. A notification message requesting to supply a replacement product of the second stock amount is sent to the first supplier terminal, a notification message requesting supply of a replacement product of the second stock amount to the first company is sent to the second supplier terminal, and a notification message requesting supply of a replacement product of the eighth stock amount is sent to the first supplier terminal. 1 A notification message requesting supply to a company can be sent to a third-party supplier terminal. To this end, the device 200 may be configured to communicate wired or wirelessly with a third supplier terminal.

Figure 7 is an exemplary diagram of the configuration of a device according to an embodiment.

Device 200 according to one embodiment includes a processor 210 and memory 220. The processor 210 may include at least one device described above with reference to FIGS. 1 to 6 or may perform at least one method described above with reference to FIGS. 1 to 6 . A person or organization using the device 200 may provide services related to some or all of the methods described above with reference to FIGS. 1 to 6 .

The memory 220 may store information related to the methods described above or store a program in which methods described later are implemented. Memory 220 may be volatile memory or non-volatile memory.

The processor 210 can execute programs and control the device 200. The code of the program executed by the processor 210 may be stored in the memory 220. The device 200 is connected to an external device (eg, a personal computer or a network) through an input/output device (not shown) and can exchange data through wired or wireless communication.

The device 200 may be used to learn an artificial intelligence model or use a learned artificial intelligence model. Memory 220 may include a learning or learned artificial intelligence model. The processor 210 may learn or execute the artificial intelligence model algorithm stored in the memory 220. The learning device that trains the artificial intelligence model and the device 200 that uses the learned artificial intelligence model may be the same or may be separate.

The embodiments described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, the devices, methods, and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, and a field programmable gate (FPGA). It may be implemented using one or more general-purpose or special-purpose computers, such as an array, programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A processing device may execute an operating system (OS) and one or more software applications that run on the operating system. Additionally, a processing device may access, store, manipulate, process, and generate data in response to the execution of software. For ease of understanding, a single processing device may be described as being used; however, those skilled in the art will understand that a processing device includes multiple processing elements and/or multiple types of processing elements. It can be seen that it may include. For example, a processing device may include a plurality of processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes magneto-optical media and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing unit to operate as desired, or may be processed independently or collectively. You can command the device. Software and/or data may be used on any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to a processing device. , or may be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

Although the embodiments have been described with limited drawings as described above, those skilled in the art can apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the following claims.

Claims (3)

In a method of changing the design of an artificial intelligence-based camping stove performed by a device,
If the first stove produced by the first company has received safety certification from the first country and is confirmed to be sold in the first country, the first list is a list of safety certification items that must be verified in order to be sold in the first country. Obtaining a;
Upon receiving an order request for importing the first stove and selling it in a second country from a second company terminal, obtaining a second list, which is a list of safety certification items that must be verified for sale in the second country;
Comparing the first list and the second list to analyze whether there are items that require additional verification to sell the first stove in the second country;
If it is analyzed that additional verification of the first item is required to sell the first stove in the second country, confirming a first condition that is a condition for passing the first item;
determining whether the first stove satisfies the first condition based on detailed information about the first stove;
If it is determined that the first stove does not meet the first condition, matching detailed information of the first stove and setting information of the first condition to generate first matching information;
After applying the first matching information to an artificial intelligence model learned to analyze which parts need to be changed to meet the conditions in the stove through matching information that matches the detailed information of the stove and the condition setting information, Based on the first matching information, the artificial intelligence model considers the state of the first stove and the satisfaction criteria of the first condition and determines that a change in the first part is necessary to satisfy the first condition in the first stove. When analyzing and outputting an output value indicating the first part, based on the output of the artificial intelligence model, selecting a part that needs to be changed to meet the first condition in the first stove as the first part. ;
When the first component is selected, generating a design change strategy for the first stove that recommends changes to the first component that are necessary to export the first stove to the second country; and
Including providing a design change strategy of the first stove to the first company terminal,
How to change the design of an artificial intelligence-based camping stove. According to paragraph 1,
The step of analyzing whether there are items that require additional verification in order to sell the first stove in the second country,
As a result of comparing the first list and the second list, if it is confirmed that the first item is not included in the first list but is included only in the second list, the first item is additionally verified. Analyzing it into necessary items; and
When, as a result of comparing the first list and the second list, it is confirmed that the passing conditions of the first item included in the first list and the passing conditions of the first item included in the second list are different, Comprising the step of analyzing the first item as an item requiring additional verification,
How to change the design of an artificial intelligence-based camping stove. According to paragraph 1,
Generating a design change strategy for the first stove recommending changes to the first component needed to export the first stove to the second country, comprising:
When it is confirmed that the second stove has received safety certification from the second country and is being sold in the second country, determining that a design change strategy for the first stove is possible using the second stove;
When the first stove is sold in the first country, it is confirmed that the first product is sold with the first part installed, and when the second stove is sold in the second country, the first product is installed and sold with the first part. 2 Confirming that the product is installed and sold; and
generating a design change strategy for the first stove recommending changing the first component from the first product to the second product for exporting the first stove to the second country,
How to change the design of an artificial intelligence-based camping stove.