Commodity department management system

Abstract

The present invention is a product inflow and outflow management system and may include a management server that manages consumables for at least one franchise branch and communicates with a delivery person terminal and a manager terminal.

Description

Technology Field

[0001] The present invention relates to a product inflow and outflow management system. Background Technology

[0002] Individual franchise branches have relied on a manual method of checking inventory and placing orders; this approach had the problem of limiting efficient logistics operations due to a high possibility of human error and the difficulty of tracking inventory in real time.

[0003] In particular, even when existing ERP systems were in place, the lack of automated data integration often prevented real-time inventory changes by store from being reflected immediately, making it difficult to predict inventory shortages or excesses in advance.

[0004] Furthermore, in terms of logistics management, the lack of an automated system to effectively sort and deliver consumables ordered by each franchise branch made it difficult to optimize delivery routes and sequences, leading to problems such as delivery delays and increased logistics costs.

[0005] Furthermore, due to the lack of a system to track and inspect the condition of shipped goods, there were limitations in preventing problems such as loss or damage that could occur during delivery or responding quickly.

[0006] Meanwhile, the aforementioned background technology is technical information that the inventor possessed for the derivation of the present invention or acquired during the process of deriving the present invention, and it cannot necessarily be considered publicly known technology disclosed to the general public prior to the filing of the present invention. Prior art literature

[0007] Korean Registered Patent No. 101568134 The problem to be solved

[0008] The objective of the present invention is to provide a product inbound and outbound management system that maximizes logistics efficiency by managing the inventory of consumables for each franchise branch in real time, enabling efficient delivery through logistics automation, and providing inventory analysis and forecasting functions through integration with an ERP system.

[0009] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0010] A product inflow and outflow management system according to one embodiment of the present invention may include a management server that manages consumables for at least one franchise branch and communicates with a delivery person terminal and a manager terminal.

[0011] According to one embodiment, the management server comprises: an ERP integration module that checks and manages inventory data of consumables for each franchise branch in real time, automatically saves and analyzes incoming and outgoing details in the ERP system to generate ERP data, and predicts consumption patterns of specific items from the ERP data and prevents inventory shortages by utilizing artificial intelligence (an AI model utilizing deep learning or machine learning algorithms); a logistics automation module that supports the management of automated equipment for classifying ordered consumables for each franchise branch based on size or weight, and calculates delivery order and delivery route to support logistics distribution efficiency and provides them to the delivery person terminal; and an alert reporting module that, when the inventory of a specific consumable at a specific branch among the franchise branches falls below a preset standard, sends an alert message notifying the branch of the inventory quantity of the consumable, automatically generates a weekly or monthly inventory status report based on the ERP data by utilizing artificial intelligence (an AI model utilizing deep learning or machine learning algorithms), and provides the generated weekly or monthly inventory status report to the manager terminal. and may include a tracking inspection module that monitors in real time the status of consumables ordered from the franchise branch that are being shipped and distributed, records and manages the status of said consumables, and records and manages complaints received through the server.

[0012] According to one embodiment, the logistics automation module can classify at least one consumable ordered by a franchise branch based on size or weight using an automated facility to deliver it to the franchise branch.

[0013] According to one embodiment, the delivery person terminal may refer to a terminal carried by a delivery person who delivers at least one consumable item classified through the automation facility to a corresponding franchise branch.

[0014] According to one embodiment, at least one consumable classified through the automation facility may have the address and quantity of the franchise branch that placed the order entered so that it can be verified by a delivery person.

[0015] According to one embodiment, the manager terminal may refer to a terminal possessed by a manager who manages the ERP system, the automation equipment, the consumables, and the management server.

[0016] According to one embodiment, the notification reporting module receives sales information from each of the franchise branches, analyzes the inventory of a specific consumable at all franchise branches, and, based on the analyzed inventory, if the inventory of a specific consumable at a specific branch falls below a preset standard, sends a notification message to the branch notifying it of the inventory of the consumable.

[0017] According to one embodiment, the tracking inspection module can check the status of consumables in real time by receiving the status of consumables from the delivery person terminal, or monitor in real time using an image of consumables captured by an internal camera equipped in a delivery vehicle distributing consumables.

[0018] According to one embodiment, the logistics automation module comprises a total number of delivery points (N) and a distance (D) to the i-th delivery point. i ), average movement speed in the i-th interval (V i ), total weight of consumables at the i-th delivery point (S i ), Current vehicle load (L), Maximum load of delivery vehicle (L max Using ) and weights (w1, w2), the total optimal delivery time (T opt ) can be produced.

[0019] According to one embodiment, the logistics automation module has a distance (D) to the i-th delivery point. i ) and average movement speed in the i-th interval (V iThe travel time calculated from ) can be summed for each segment and used as a factor to calculate the total delivery time.

[0020] According to one embodiment, the logistics automation module comprises the total weight of consumables (S) at the i-th delivery point. i It is determined that additional processing time is required as ) increases, so the formula is designed to increase delivery time according to weight increase, but it can be characterized by using a logarithmic function so that the rate of increase in additional processing time is gradually mitigated.

[0021] According to one embodiment, the logistics automation module reflects the effect of the delivery speed decreasing as the current vehicle load (L) increases, wherein the current vehicle load (L) is the maximum load (L) of the delivery vehicle. max It can be characterized by being designed using the trigonometric function sin to express the non-linear effect of the delivery time increasing rapidly as it approaches ). Effects of the invention

[0022] According to one aspect of the present invention described above, the product inflow and outflow management system proposed by the present invention can manage the inventory of consumables at a franchise branch in real time, thereby preventing problems of inventory shortage or excess and providing efficient inventory management.

[0023] In addition, operators can perform more accurate inventory forecasting and management, and prevent business disruptions caused by inventory shortages.

[0024] In addition, integration with the ERP system enables not only inventory management but also the automatic saving and analysis of incoming and outgoing transaction records, thereby enhancing business automation and efficiency.

[0025] In addition, the logistics automation module allows for the optimization of consumable sorting and delivery routes, significantly improving logistics distribution efficiency and enabling shorter delivery times and reduced costs.

[0026] In addition, it is possible to monitor inventory status in real time and send an immediate notification if the inventory of specific consumables falls below a set threshold, thereby enabling a rapid response.

[0027] In addition, the status of consumables being shipped can be monitored in real time, and immediate responses to problems can be made, thereby improving delivery quality and customer satisfaction.

[0028] The effects of the present invention are not limited to those mentioned above, and various effects may be included within the scope obvious to a person skilled in the art from the contents described below. Brief explanation of the drawing

[0029] FIG. 1 is a conceptual diagram of a product inflow and outflow management system according to one embodiment of the present invention. FIG. 2 is a conceptual diagram of a management server according to one embodiment of the present invention. Specific details for implementing the invention

[0030] The following detailed description of the invention refers to the accompanying drawings, which illustrate specific embodiments in which the invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that various embodiments of the invention are different but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the invention in relation to one embodiment.

[0031] When it is stated that one component is "connected" or "contracted" to another component, it should be understood that while it may be directly connected or contracted to that other component, there may also be other components in between. Conversely, when it is stated that one component is "directly connected" or "directly contracted" to another component, it should be understood that there are no other components in between.

[0032] Furthermore, it should be understood that the location or arrangement of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the invention. Accordingly, the following detailed description is not intended to be taken in a limiting sense, and the scope of the invention is limited only by the appended claims, including all equivalents thereof, provided appropriately described. Similar reference numerals in the drawings refer to the same or similar functions across various aspects.

[0033] Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the drawings.

[0035] FIG. 1 is a conceptual diagram of a product inflow and outflow management system according to one embodiment of the present invention.

[0036] Referring to FIG. 1, a product receiving and shipping management system according to one embodiment of the present invention may include a management server (100), a delivery person terminal (300), and a manager terminal (500).

[0037] The management server (100) manages consumables for at least one franchise branch according to the present invention and can communicate with a delivery person terminal and a manager terminal.

[0038] The delivery terminal (300) may refer to a terminal carried by a delivery person who delivers at least one consumable item classified through the above-mentioned automation facility to a corresponding franchise branch.

[0039] The administrator terminal (500) may refer to a terminal held by an administrator who manages the ERP system, the automation equipment, the consumables, and the management server (100).

[0040] The management server (100), delivery terminal (300), and administrator terminal (500) may be self-contained servers or cloud servers for providing services according to the present invention, or they may be a peer-to-peer (P2P) set of distributed nodes.

[0041] The management server (100) can perform one or more of the operations, storage, reference, input / output, and control functions of a general computer, and may include an artificial neural network described later based on input data.

[0042] The management server (100) may include a processor and memory. The processor may include devices capable of managing consumables for at least one franchise branch according to the present invention, communicating with a delivery person terminal and a manager terminal, and performing these functions. The processor may execute a program or control the management server (100). Program code executed by the processor may be stored in memory. The memory may store relevant information for performing a service according to the present invention or a program for implementing a method. The memory may be volatile memory or non-volatile memory.

[0043] The management server (100) can send data to an external device or receive data from an external device using a network.

[0044] The management server (100) can train an artificial neural network and can also use an artificial neural network that has been trained. The processor can train or execute an artificial neural network stored in memory, and the memory can store an artificial neural network that has been trained. The electronic device that trains the artificial neural network and the electronic device that uses it may be the same, but they may also be separate.

[0045] Artificial intelligence is a computer system that partially implements the functions of the human brain and is capable of learning, speculating, and making judgments on its own. As learning progresses, the probability of extracting the correct answer can increase. Artificial intelligence can be composed of learning and component technologies that utilize it. The learning aspect of AI is an algorithmic technology that classifies and learns features based on input data, while the component technologies may be techniques that utilize these learning algorithms to partially implement the functions of the human brain.

[0046] Artificial intelligence is a technology that facilitates the approach to problems where multiple probabilistic answers are possible, enabling it to logically and probabilistically infer optimal cycles, methods, and plans based on input data. AI inference techniques can include evaluating input data, optimization prediction, knowledge and probability-based reasoning, and preference-based planning.

[0047] Artificial neural networks are learning algorithms in the field of machine learning that programmatically implement the connections between neurons and synapses in the brain. By creating a neural network structure through programming and then training it, artificial neural networks can acquire desired functions. Although errors may exist, they can learn from massive datasets to produce appropriate output data from input data. They have the advantage of being able to obtain output data that has yielded statistically good results and are similar to human reasoning.

[0048] The management server (100) can infer individual characteristics and interests by analyzing consumers' online behavior data, social media activities, search history, etc., using an artificial intelligence algorithm built based on big data, and may include a number of pre-trained artificial neural networks for this purpose.

[0049] The network is a high-speed backbone network of a large-scale communication network capable of high-capacity, long-distance voice and data services, and may be a next-generation wired and wireless network for providing the Internet or high-speed multimedia services.

[0050] If the network is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of an asynchronous mobile communication network, a WCDMA (Wideband Code Division Multiple Access) network may be cited. In this case, although not shown in the drawing, the network may include an RNC (Radio Network Controller). Meanwhile, although a WCDMA network was given as an example, it may be a 3G LTE network, a 4G network, a next-generation communication network such as 5G, or other IP-based IP networks.

[0051] The management server (100), delivery terminal (300), and administrator terminal (500) may include any terminal capable of exchanging data over a network, such as a desktop computer, laptop, tablet, or smartphone.

[0052] The management server (100), delivery terminal (300), and administrator terminal (500) may include one or more of the computational function, storage function, reference function, input / output function, and control function of a computer to perform the service according to the present invention.

[0053] The management server (100), the delivery terminal (300), and the administrator terminal (500) may access a website or install an application to receive the service according to the present invention. The management server (100) and the administrator terminal (500) may exchange data through the website or the application.

[0054] The network is a high-speed backbone network of a large-scale communication network capable of high-capacity, long-distance voice and data services, and may be a next-generation wired and wireless network for providing the Internet or high-speed multimedia services.

[0055] If the network is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of an asynchronous mobile communication network, a WCDMA (Wideband Code Division Multiple Access) network may be cited. In this case, although not shown in the drawing, the network (300) may include an RNC (Radio Network Controller). Meanwhile, although a WCDMA network was given as an example, it may be a 3G LTE network, a 4G network, a 5G network, or other next-generation communication networks, or other IP-based IP networks.

[0056] A system (1) according to one embodiment of the present invention manages consumables for at least one franchise branch, communicates with a delivery person terminal and a manager terminal to manage the inventory of consumables for each franchise branch in real time, enables efficient delivery through logistics automation, and can provide inventory analysis and forecasting functions through linkage with an ERP system.

[0058] FIG. 2 is a conceptual diagram of a management server according to one embodiment of the present invention.

[0059] Referring to FIG. 2, a management server (100) according to one embodiment of the present invention may include an ERP integration module (110), a logistics automation module (130), a notification reporting module (150), and a tracking inspection module (170).

[0060] The ERP integration module (110) can check and manage inventory data of consumables for each franchise branch in real time, automatically save and analyze incoming and outgoing records in the ERP system to generate ERP data, and use artificial intelligence (an AI model utilizing deep learning or machine learning algorithms) to predict consumption patterns of specific items from the ERP data and prevent inventory shortages.

[0061] The logistics automation module (130) supports the management of automated equipment that classifies ordered consumables based on size or weight for each franchise branch, and can calculate the delivery order and delivery route to support the efficiency of logistics distribution and provide them to the delivery person terminal (300).

[0062] Additionally, the logistics automation module (130) can classify at least one consumable ordered by a franchise branch based on size or weight using an automated facility to deliver it to the franchise branch.

[0063] At least one consumable item classified through the aforementioned automated equipment may have the address and quantity of the ordering franchise branch entered so that it can be verified by a delivery person.

[0064] Meanwhile, the logistics automation module (130) has a total number of delivery points (N) and a distance (D) to the i-th delivery point. i ), average movement speed in the i-th interval (V i ), total weight of consumables at the i-th delivery point (S i ), Current vehicle load (L), Maximum load of delivery vehicle (L max Based on ) and weights (w1, w2), calculate as shown in [Equation 1] below to obtain the total optimal delivery time (T opt ) can be produced.

[0065] [Mathematical Formula 1]

[0066]

[0067] Here, the total number of branches to be delivered (N) may refer to the number of franchise branches that ordered consumables through the server.

[0068] Distance to the i-th delivery point (D i ) may mean the distance from the consumables' shipping location using the unit 'km' to the franchise branch that ordered each consumable.

[0069] More specifically, the logistics automation module (130) collects distance data from a tool or device that provides the distance between a source and a destination, such as GPS, to the distance (D) to the i-th delivery point. i ) can be derived.

[0070] Average movement speed in the i-th interval (V i ) may mean the average travel speed from the consumable shipping point using 'km / h' units to the franchise branch that ordered each consumable.

[0071] More specifically, the logistics automation module (130) collects movement speed data from a tool or device that provides real-time traffic information between a source and a destination, such as GPS, and the average movement speed (V) in the i-th section i ) can be derived.

[0072] Total weight of consumables at the i-th delivery point (S) i ) may refer to the total weight of consumables delivered to the franchise branch that ordered consumables using the 'kg' unit.

[0073] More specifically, the logistics automation module (130) classifies the total weight of consumables (S) at the i-th delivery point through the automation equipment that classifies consumables based on their size or weight. i ) can be derived.

[0074] Currently, the vehicle load (L) may refer to the weight loaded in a delivery vehicle using the unit 'kg', and a portion of the consumables classified through the above-mentioned automated equipment can be derived from the amount and weight loaded in the delivery vehicle.

[0075] Maximum load capacity of delivery vehicles (L max ) can mean each maximum load capacity corresponding to multiple delivery vehicles using the 'kg' unit, and the logistics automation module (130) can be derived from the specifications of the delivery vehicle.

[0076] The weights (w1, w2) are adjustable values ​​based on experience data, have no separate units of use, and can be derived from input values ​​by an AI model trained on historical data.

[0077] More specifically, the AI ​​model trained on historical data has the total weight of consumables (S) at the i-th delivery point. i The increase in ) is the total optimal delivery time (T opt If it is determined that w1 has a greater impact on ), w1 can be entered as a value greater than w2.

[0078] That is, the weights (w1, w2) are the total weight of consumables (S) at the i-th delivery point by an AI model trained on past data. i ) and the maximum load capacity of the delivery vehicle (L) compared to the current vehicle load capacity (L) max Total optimal delivery time (T) opt It can be entered as a value to reflect greater importance in ).

[0079] The values ​​of the weights (w1, w2) can be adjusted by an AI model trained on past data, but the server administrator or operator can control the influence of the weight or load by directly setting the values ​​of the weights (w1, w2) input by the AI ​​model.

[0080] The administrator or operator of the server can directly input weight (w1, w2) values ​​into the management server (100) or logistics automation module (130) through the administrator terminal (500) so that they are reflected in [Equation 1].

[0081] Total Optimal Delivery Time (T opt ) uses a 'time' unit and can mean a value calculated from [Mathematical Formula 1], and the logistics automation module (130) can determine the delivery order of franchise branches according to the calculated delivery time.

[0082] [Mathematical Formula 1] is the distance to the i-th delivery point (D i ) and average movement speed in the i-th interval (V i It can be characterized by using the travel time calculated from ) as a factor to calculate the total delivery time by summing the travel times for each segment.

[0083] [Mathematical Formula 1] is the total weight of consumables (S) at the above i-th delivery point i It is determined that additional processing time is required as ) increases, so the formula is designed to increase delivery time according to weight increase, but it can be characterized by using a logarithmic function so that the rate of increase in additional processing time is gradually mitigated.

[0084] [Mathematical Formula 1] reflects the effect of the delivery speed decreasing as the current vehicle load (L) increases, wherein the current vehicle load (L) is the maximum load (L) of the delivery vehicle max It can be characterized by being designed using the trigonometric function sin to express the non-linear effect of the delivery time increasing rapidly as it approaches ).

[0085] [Mathematical Formula 1] can calculate the optimal delivery route and order by utilizing real-time data collected from automated facilities.

[0086] In addition, [Equation 1] can model a realistic scenario in which delivery time increases as more heavy items are loaded by reflecting the proportional and inverse relationships between each variable.

[0087] In addition, [Equation 1] can be applied in conjunction with real-time GPS data for changes over time, and the server administrator or operator can set the optimal delivery route by adjusting the weight (w1, w2) values.

[0088] To explain the variables and formula operations described above in order, the logistics automation module (130) can measure the size and weight of each consumable ordered through the automation equipment and store them in a database, collect the location (GPS coordinates) of each delivery point and real-time traffic information to calculate distance and speed, and calculate the optimal delivery order by applying the current load of the vehicle to the formula.

[0089] That is, the logistics automation module (130) can calculate the delivery order of the franchise branch according to the total optimal delivery time (Topt), which is a value calculated from [Equation 1], and can send the delivery order to the delivery terminal (300).

[0090] Here, the delivery person may be designed to manually input a specific route through the delivery person terminal (300) to correct the delivery speed.

[0091] The logistics automation module (130) can adjust the route by recalculating the formula according to real-time changes (traffic conditions, additional orders, etc.), because even the same route can have a different optimal route derived over time.

[0092] [Mathematical Equation 1] allows each variable to be easily derived from the system and consists of basic mathematical operations (distance / velocity, logarithmic function, trigonometric function, etc.), so it can be easily implemented by an ordinary technician.

[0093] The logistics automation module (130) can find a route that minimizes the total delivery time by summing the travel times of each section through [Equation 1], and can continuously update the optimal delivery route by utilizing GPS data and real-time traffic information.

[0094] In addition, the logistics automation module (130) can perform route optimization by reflecting the tendency for the logistics movement speed to decrease as the vehicle's load increases through [Equation 1], and can reflect the physical characteristic that the speed decreases rapidly when the load exceeds a certain level by using trigonometric functions.

[0095] In addition, the logistics automation module (130) can manage the overall logistics flow by linking the data measured from the automation equipment with the ERP system through [Equation 1], build an AI-based logistics optimization system, and expand into a more sophisticated prediction model through machine learning in the future.

[0096] The notification reporting module (150) can send a notification message to a specific branch among franchise branches to inform the branch of the inventory amount of the consumable when the inventory of the consumable at that branch falls below a preset standard.

[0097] Additionally, the notification reporting module (150) can automatically generate a weekly or monthly inventory status report by utilizing artificial intelligence (an AI model utilizing deep learning or machine learning algorithms) based on the ERP data, and provide the generated weekly or monthly inventory status report to the administrator terminal (500).

[0098] The notification reporting module (150) can receive sales information from each of the franchise branches and analyze the inventory of specific consumables at all franchise branches.

[0099] Additionally, the notification reporting module (150) can send a notification message to a specific branch notifying the inventory amount of the consumables when the inventory of a specific consumable at a specific branch falls below a preset standard based on the analyzed inventory amount.

[0100] Meanwhile, the notification reporting module (150) reports the average consumption (D of a specific consumable) of a specific consumable during a recent specific period. avg ), current stock quantity of a specific consumable (O), maximum storage capacity of a specific consumable (O max ), total quantity of specific consumables currently ordered (S), estimated delivery time (T), and weight (w a , w b Based on ), calculate the inventory warning index (R) as shown in [Equation 2] below. alert ) can be produced.

[0101] [Mathematical Formula 2]

[0102]

[0103] Here, the average consumption of a specific consumable (D during a recent specific period) avg ) may refer to the consumption of specific consumables by each franchise branch using the unit of 'piece / day'.

[0104] More specifically, the notification reporting module (150) generates ERP data based on the receiving and shipping records of the ERP integration module (110) to determine the average consumption (D) of a specific consumable during a recent specific period. avg ) can be derived.

[0105] The current stock quantity (O) of a specific consumable may refer to the current remaining quantity of a specific consumable at the franchise branch using the unit of 'piece'.

[0106] More specifically, the notification reporting module (150) can derive the current inventory amount (O) of a specific consumable from the inventory data of consumables per franchise branch that the ERP integration module (110) checks and manages in real time.

[0107] Maximum stock capacity of a specific consumable (O max ) uses the unit of 'pieces' and may refer to the quantity initially set by the server administrator or operator according to the expiration date or consumption date of the consumable.

[0108] The administrator or operator of the server can directly input the maximum storage quantity of each consumable to the management server (100) or ERP integration module (110) through the administrator terminal (500), and based on this, the ERP integration module (110) can input the maximum storage inventory quantity (O) of each consumable. max Can save ).

[0109] More specifically, the notification reporting module (150) determines the maximum storage capacity of a specific consumable (O) from the maximum storage capacity stored in the ERP integration module (110). max ) can be derived.

[0110] The total quantity (S) of a specific consumable currently ordered may refer to the total quantity of a specific consumable ordered by the relevant franchise branch using the unit of 'piece'.

[0111] More specifically, the notification reporting module (150) can derive the total amount (S) of a specific consumable currently ordered from the order data ordered by the franchise branch.

[0112] The estimated delivery time (T) may refer to the time expected for the delivery of the relevant consumables ordered by the franchise branch using 'day' units.

[0113] More specifically, the notification reporting module (150) can derive the estimated delivery time (T) through the logistics automation module (130).

[0114] weight(w a , w b) is a value adjustable based on experience data, has no separate unit of use, and can be derived from the input value by an AI model that has learned past data.

[0115] More specifically, an AI model trained on historical data 'maximum storable inventory (O) of a specific consumable relative to the current inventory (O) of the specific consumable max Average consumption of a specific consumable (D) during a specific period more recent than )' avg ) is the Inventory Warning Index (R alert If it is determined that greater sensitivity should be reflected in ), w a ul w b You can enter a larger value.

[0116] That is, weights (w a , w b ) is the average consumption of a specific consumable (D) during a recent specific period by an AI model trained on historical data. avg ) and the maximum storable inventory of a specific consumable relative to the current inventory (O) of the specific consumable (O max Total Inventory Warning Index (R) alert It can be entered as a value to reflect sensitivity to ).

[0117] As described above, the weights (w) are obtained by an AI model that has learned past data. a , w b The value of ) can be adjusted, but the server administrator or operator must control the weights (w) input by the AI ​​model. a , w b You can adjust the effect of weight or load by directly setting the value.

[0118] The server administrator or operator sends a weight (w) to the management server (100) or the notification reporting module (150) through the administrator terminal (500). a , w b You can directly input the value to be reflected in [Equation 2].

[0119] Inventory Warning Index (Ralert ) is the average consumption of a specific consumable (D) during a recent specific period. avg In a proportional relationship with ), as consumption increases, the risk of stock shortage increases, which may increase the probability of sending a stock shortage notification message.

[0120] In addition, the stock warning index (R alert ) is the current stock quantity (O) of a specific consumable and the maximum stock quantity (O) that can be stored of a specific consumable max In an inverse relationship with the maximum storage capacity, the higher the current inventory ratio, the lower the risk of shortage and the lower the probability of sending out a shortage alert message.

[0121] In addition, the stock warning index (R alert ) is proportional to the total amount (S) of a specific consumable currently ordered, so as the order quantity increases, the risk of stock shortage increases, and the probability of sending a stock shortage notification message may increase.

[0122] [Mathematical Formula 2] is the average consumption of a specific consumable (D) during a recent specific period. avg It can be characterized by using a logarithmic function to moderately adjust the growth rate while reflecting that the likelihood of a shortage of specific consumables at the franchise branch increases as ) increases.

[0123] That is, [Equation 2] can be characterized by being designed to use a logarithmic function to mitigate the change when consumption increases rapidly while reflecting the overall trend.

[0124] In addition, [Equation 2] may be characterized by using the trigonometric function sin to lower the stock warning index (Ralert) as the current stock quantity (O) of a specific consumable of the franchise approaches the maximum stock quantity (Omax) of the specific consumable.

[0125] That is, [Equation 2] can be characterized by being designed so that the inventory warning index (Ralert) changes small when the current inventory amount (O) of a specific consumable of the franchise is large, and the inventory warning index (Ralert) changes large when the current inventory amount (O) of a specific consumable of the franchise is small, using the trigonometric function sin.

[0126] In addition, [Equation 2] may be characterized by using the value obtained by dividing the total amount (S) of a specific consumable currently ordered from the franchise branch by the estimated delivery time (T) to reflect that the need for additional warnings is reduced when there are many consumables already ordered and the delivery time is short.

[0127] That is, [Equation 2] may be characterized by being designed so that the inventory warning index (Ralert) decreases as the total amount (S) of a specific consumable currently ordered from the franchise branch increases and the expected delivery time (T) decreases, thereby preventing unnecessary warnings.

[0128] The notification reporting module (150) can predict inventory shortages in advance by comprehensively analyzing inventory levels, consumption patterns, and order status through [Equation 2].

[0129] Additionally, the notification reporting module (150) can automatically send a stock shortage notification message to the corresponding point when a specific threshold (e.g., 1.5) is exceeded through [Equation 2].

[0130] In addition, the notification reporting module (150) can perform analysis daily or at regular intervals in conjunction with real-time inventory data through [Equation 2].

[0131] To explain each of the aforementioned variables and formula operations in order, the notification reporting module (150) [reports] the average consumption amount (D) of a specific consumable during a recent specific period through the ERP integration module (110). avg ), current stock quantity of a specific consumable (O), maximum storage capacity of a specific consumable (Omax ) can be derived, and the total quantity (S) of a specific consumable currently ordered and the estimated delivery time (T) can be derived through the logistics automation module (130), and each derived variable is substituted into the formula [Equation 2] to obtain an inventory warning index (R alert ) can be produced.

[0132] The notification reporting module (150) is an inventory warning index (R) calculated by [Equation 2]. alert If ) exceeds a certain threshold (e.g., 1.5), a notification message can be sent to the relevant franchise branch.

[0133] The administrator or user of the server can adjust the frequency of notifications regarding the shortage of consumables at franchise branches by directly inputting a certain threshold value into the management server (100) or the notification reporting module (150) through the administrator terminal (500).

[0134] Server administrators or users [use] an inventory warning index (R) based on real-time changes in the consumption of each consumable for each franchise branch alert Since the value can change continuously, a certain threshold can be updated at specific time intervals (e.g., every hour or every day) through the administrator terminal (500).

[0135] The notification reporting module (150) can automatically increase the warning sensitivity when the expected delivery time (T) is extended and send a notification for additional orders.

[0136] [Mathematical Formula 2] can derive each variable from the ERP integration module (110) and the logistics automation module (130), and can be easily implemented by a person of ordinary skill using a simple formula that uses logarithmic and trigonometric functions.

[0137] The notification reporting module (150) can predict the possibility of shortage in real time by analyzing the average consumption and current inventory levels through [Equation 2], and can send a warning message only when it is actually urgent by reflecting the consumables currently ordered and the delivery time.

[0138] In addition, the notification reporting module (150) can reduce unnecessary urgent orders and reduce logistics costs by predicting the expected shortage time in advance through [Equation 2] and inducing orders at an appropriate time, and can automatically analyze weekly and monthly inventory status to present the optimal inventory management strategy to the manager.

[0139] The tracking inspection module (170) can monitor the status of consumables that have been shipped and are being distributed from franchise branches in real time, record and manage the status of said consumables, and record and manage complaints received through the server.

[0140] The tracking inspection module (170) can check the status of consumables in real time by receiving the status of consumables from the delivery terminal (300), or monitor in real time using an image of consumables captured by an internal camera equipped in a delivery vehicle that distributes consumables.

[0141] Meanwhile, the tracking inspection module (170) is an impact amount (T) during delivery. imp ), change in temperature (C change ), ratio of loading space to item volume (V ratio ), delivery distance( Dgps ) and weights(w x , w y Based on ), calculate the possibility of abnormal status of consumables (S) as shown in [Mathematical Formula 3] below. po ) can be produced.

[0142] [Mathematical Formula 3]

[0143]

[0144] Here, the impact during delivery (T imp ) is 'm / s 2 It uses the unit of ' and can refer to the degree of impact that occurs to the delivery vehicle delivering ordered consumables to the franchise branch, that is, a value that quantifies the likelihood of the consumables receiving external impact during the delivery process.

[0145] More specifically, the tracking inspection module (170) obtains the impact amount (T during delivery) from impact data collected from an acceleration sensor or impact sensor and an internal camera equipped in a delivery vehicle delivering consumables. imp ) can be derived.

[0146] For example, the tracking inspection module (170) derives an average value using the maximum change in acceleration detected over a specific period of time to determine the impact amount during delivery (T imp ) can be derived.

[0147] Change in temperature (C change ) may refer to the degree of temperature change in the space where consumables are loaded in a delivery vehicle using the unit '°C', or the amount of change when comparing the temperature at the time of shipment and the time of delivery completion of the consumables.

[0148] More specifically, the tracking inspection module (170) obtains a temperature change amount (C) from temperature data collected before delivery departure and temperature data collected after delivery completion from a temperature-measuring sensor equipped in a delivery vehicle delivering consumables. change ) can be derived.

[0149] Ratio of storage space to item volume (V) ratio There is no separate unit used, and it can be derived from the ratio of the total volume of consumables loaded in the delivery vehicle to the loading space of the delivery vehicle.

[0150] When a delivery vehicle is full of goods, the probability of damage to delivered consumables is low; however, when a delivery vehicle is loaded with a small amount of goods and has a lot of empty space, the probability of damage to consumables increases, so the ratio of loading space to goods volume (V ratio ) is the possibility of abnormal condition of consumables (S po It can be reflected as an important factor when calculating ).

[0151] Delivery distance (D gps ) can mean the distance a delivery vehicle using the unit 'km' delivers to a designated franchise branch.

[0152] More specifically, the tracking inspection module (170) collects distance data from a tool or device that provides the distance between the origin and the destination, such as GPS, to provide the delivery distance (D gps ) can be derived.

[0153] weight(w x , w y ) is a value adjustable based on experience data, has no separate unit of use, and can be derived from the input value by an AI model that has learned past data.

[0154] More specifically, if an AI model trained on historical data is vulnerable to shocks, w x The value of w y It can be set higher, and if road conditions in a specific area are poor, w y You can also adjust the value of to reflect the influence of distance more significantly.

[0155] That is, weights (w x , w y ) is the impact during delivery (T) by an AI model trained on historical data imp ), change in temperature (C change ), ratio of loading space to item volume (V ratio ), delivery distance (D gps Any one of the variables of the possibility of a consumable's condition abnormality (S poIt can be entered as a value to reflect greater importance in ).

[0156] As described above, the weights (w) are obtained by an AI model that has learned past data. x , w y The value of ) can be adjusted, but the server administrator or operator must control the weights (w) input by the AI ​​model. x , w y You can adjust the effect of weight or load by directly setting the value.

[0157] The server administrator or operator sends a weight (w) to the management server (100) or the tracking inspection module (170) through the administrator terminal (500). x , w y You can directly input the value to be reflected in [Equation 3].

[0158] Possibility of abnormal condition of consumables (S po ) is the impact during delivery (T imp ) and temperature change amount (C change It can be adjusted to reflect the effect on the condition abnormality of consumables even if shock and temperature suddenly increase, through a logarithmic proportional relationship.

[0159] In addition, the possibility of abnormal condition of consumables (S po ) is the ratio of loading space to item volume (V ratio In an inverse relationship with ), the more space there is, the higher the likelihood of shaking, so the risk of damage to consumables may increase.

[0160] In addition, the possibility of abnormal condition of consumables (S po ) is the delivery distance (D gps It can fluctuate periodically depending on ), which can reflect a pattern where vibrations become stronger at a specific distance.

[0161] [Mathematical Formula 3] is the impulse during delivery (T imp ) and temperature change amount (C change ) Possibility of abnormal condition of consumables (S poIt can be characterized by having a direct effect on ), but being designed to change gradually by applying a logarithmic function to prevent abrupt changes.

[0162] That is, [Equation 3] uses a logarithmic function to calculate the impulse during shipping (T imp ) or change in temperature (C change Even if ) yields an extremely high value, it can prevent the influence of each variable from becoming too large.

[0163] In addition, [Equation 3] has the possibility that road conditions or vehicle vibrations may change periodically, so the delivery distance (D gps It can be characterized by reflecting changes according to distance using the trigonometric function sin.

[0164] To explain the aforementioned variables and formula operations in order, the tracking inspection module (170) collects impact data and temperature data through various sensors (acceleration sensor or impact sensor, internal camera, temperature measurement sensor, etc.) inside the delivery vehicle when the delivery vehicle starts operating, and each variable (impact amount during delivery (T) imp ), change in temperature (C change ), ratio of loading space to item volume (V ratio ), delivery distance (D gps )) can be derived, and by substituting each variable data into the formula [Mathematical Formula 3], the possibility of abnormal status of consumables (S po ) can be produced.

[0165] The tracking inspection module (170) is the possibility of abnormal status of the consumable (S) calculated from [Equation 3]. po If the value of ) is above a preset threshold, a warning message can be sent to the delivery driver terminal and the manager terminal.

[0166] The tracking inspection module (170) is the possibility of abnormal status of the consumable (S) calculated from [Equation 3]. poThe final status data after delivery completion relative to the value of ) can be stored on the server and analyzed for a certain period to be used for improving future prediction models.

[0167] [Mathematical Formula 3] can continuously update impact data and temperature data collected through sensors (accelerometer or impact sensor, internal camera, temperature measurement sensor, etc.) over time, and the possibility of abnormal condition of consumables (S po ) can be calculated in real time.

[0168] In addition, [Mathematical Formula 3] can compare data measured at preset time intervals (e.g., 5-minute intervals) by the server administrator or operator, and the calculated probability of abnormal status of consumables (S po It is possible to check ) and analyze the possibility of abnormal conditions in consumables being shipped.

[0169] The tracking inspection module (170) detects the possibility of abnormal status of consumables (S) for a certain period of time. po If the value of ) remains high, additional measures (such as sending a confirmation request message to the delivery person's terminal or the administrator's terminal) may be performed.

[0170] The tracking inspection module (170) can quantify the possibility of abnormal condition of consumables by comprehensively considering the impact amount during delivery, temperature change, volume loading ratio, delivery distance, etc. through [Equation 3].

[0171] In addition, the tracking inspection module (170) allows the delivery person to identify and manage consumables that are likely to cause problems in advance through [Equation 3].

[0172] [Mathematical Formula 3] can derive each variable based on sensor data, and through simple calculations such as logarithmic and trigonometric functions, the possibility of abnormal status of consumables (S po Since it can calculate ), a person of ordinary skill can easily implement it.

[0174] The embodiments described above are for illustrative purposes only, and those skilled in the art will understand that the embodiments described above can be easily modified into other specific forms without altering the technical concept or essential features of the embodiments described above. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. For example, each component described as a single unit may be implemented in a distributed manner, and components described as distributed may likewise be implemented in a combined form.

[0176] The scope of protection sought through this specification is defined by the claims set forth below rather than by the detailed description, and should be interpreted to include all modifications or variations derived from the meaning and scope of the claims and the concept of equivalents. Explanation of the symbols

[0177] 100: Management Server

Claims

Claim 1 A product inbound and outbound management system comprising: a management server that manages consumables for at least one franchise branch and communicates with a delivery person terminal and a manager terminal; wherein the management server comprises: an ERP linkage module that checks and manages inventory data of consumables for each franchise branch in real time, automatically saves and analyzes inbound and outbound details in an ERP system to generate ERP data, and predicts consumption patterns of specific items from the ERP data and prevents inventory shortages by utilizing artificial intelligence (an AI model utilizing deep learning or machine learning algorithms); a logistics automation module that supports the management of automated equipment that classifies consumables ordered by each franchise branch based on size or weight, and calculates delivery order and delivery route to support logistics distribution efficiency and provides them to the delivery person terminal; and, when the inventory of a specific consumable at a specific branch among the franchise branches falls below a preset standard, sends an alert message notifying the branch of the inventory quantity of the said consumable, automatically generates a weekly or monthly inventory status report based on the ERP data by utilizing artificial intelligence (an AI model utilizing deep learning or machine learning algorithms), and provides the generated weekly or monthly inventory status report to the manager A notification reporting module provided to a terminal; and a tracking inspection module that monitors in real time the status of consumables ordered from the franchise branch that are shipped and in circulation, records and manages the status of said consumables, and records and manages complaints received through a server;The system includes, wherein the logistics automation module classifies at least one consumable ordered by a franchise branch based on size or weight using automated equipment to deliver it to the corresponding franchise branch, the delivery person terminal refers to a terminal held by a delivery person delivering at least one consumable classified through the automated equipment to the corresponding franchise branch, the at least one consumable classified through the automated equipment has the address and quantity of the ordering franchise branch entered so that it can be verified by the delivery person, the manager terminal refers to a terminal held by a manager who manages the ERP system, the automated equipment, the consumable, and the management server, the notification reporting module receives sales information from each of the franchise branches and analyzes the inventory quantity of a specific consumable at all franchise branches, and if the inventory of a specific consumable at a specific branch falls below a preset standard based on the analyzed inventory quantity, sends a notification message to the branch notifying the inventory quantity of the consumable, and the tracking inspection module receives the status of the consumable from the delivery person terminal and checks the status of the consumable in real time, or an internal camera equipped in a delivery vehicle distributing the consumable The system monitors consumables in real time using video captured from a camera, and the notification reporting module includes the average consumption amount (D) of a specific consumable during a recent specific period. avg ), current stock quantity of a specific consumable (O), maximum storage capacity of a specific consumable (O max ), total quantity of specific consumables currently ordered (S), estimated delivery time (T), and weight (w a , w b Based on ), the average consumption of a specific consumable (D) during a recent specific period avg Reflecting that the likelihood of a specific consumable stock shortage at the franchise branch increases as ) increases, a logarithmic function is used to moderate the growth rate; the trigonometric function sin is used to lower the stock warning index (Ralert) as the current stock quantity (O) of the specific consumable at the franchise approaches the maximum storage capacity (Omax); and the stock warning index (R) is calculated by computing a formula designed using the value obtained by dividing the total quantity (S) of the specific consumable currently ordered from the franchise branch by the estimated delivery lead time (T). alert Calculate ) and the average consumption of a specific consumable (D) during the aforementioned recent specific period. avg ) refers to the consumption amount of specific consumables by each franchise branch using the unit of 'piece / day', and the above notification reporting module refers to the average consumption amount of specific consumables (D) during a recent specific period through ERP data generated according to the receiving and shipping records of the above ERP integration module. avg ) is derived, and the current inventory quantity (O) of the specific consumable above refers to the current remaining quantity of the specific consumable at the relevant franchise branch using the unit of 'piece', and the notification reporting module derives the current inventory quantity (O) of the specific consumable from the inventory data of consumables per franchise branch that is checked and managed in real time by the ERP integration module, and the maximum storable inventory quantity (O) of the specific consumable above max ) uses the unit of 'piece' and refers to a quantity initially pre-set by the server administrator or operator according to the expiration date or use-by date of the relevant consumable, and the above notification reporting module receives the maximum storage quantity of each consumable directly from the management server or the ERP integration module through the administrator terminal, and from the maximum storage quantity stored in the ERP integration module, the maximum storage inventory quantity of a specific consumable (O max ) derives, and the total quantity (S) of the specific consumable currently ordered refers to the total quantity of the specific consumable ordered by the relevant franchise branch using the unit of 'piece', and the notification reporting module derives the total quantity (S) of the specific consumable currently ordered from the order data ordered by the relevant franchise branch, and the estimated delivery time (T) refers to the time expected for delivery of the consumable ordered by the relevant franchise branch using the unit of 'day', and the notification reporting module derives the estimated delivery time (T) through the logistics automation module, and the weight (w a , w b ) is a value adjustable based on experiential data with no separate unit of use, and is derived from values ​​input by an AI model trained on historical data, wherein the average consumption of a specific consumable (D) during a recent specific period is derived by the AI ​​model trained on historical data. avg ) and the maximum storable inventory of a specific consumable relative to the current inventory (O) of the specific consumable (O max Total Inventory Warning Index (R) alert It is input as a value to reflect sensitivity to ), and the above AI model learns past data to 'maximum storable inventory quantity (O) of a specific consumable relative to the current inventory quantity (O) of a specific consumable'. max Average consumption of a specific consumable (D) during a specific period more recent than )' avg ) is the Inventory Warning Index (R alert If it is determined that greater sensitivity should be reflected in ), w a ul w b Enter a value greater than the above inventory warning index (R alert ) is the average consumption of a specific consumable (D) during a recent specific period. avg In a proportional relationship with ), as consumption increases, the risk of stock shortage increases, and the probability of sending a stock shortage alert message increases, and the current stock quantity (O) of a specific consumable and the maximum storable stock quantity (O) of a specific consumable max It is characterized by an inverse relationship with the current inventory ratio relative to the maximum storage capacity, such that the higher the ratio, the lower the risk of shortage and the lower the probability of sending an inventory shortage alert message, and a proportional relationship with the total quantity (S) of a specific consumable currently ordered, such that the higher the order quantity, the higher the risk of shortage and the higher the probability of sending an inventory shortage alert message, and the above inventory warning index (R alert The formula for calculating ) is designed to use a logarithmic function to reflect the overall trend while mitigating the change when consumption increases rapidly, and is designed to use the trigonometric function sin so that the inventory warning index (Ralert) changes small when the current inventory quantity (O) of a specific consumable of the franchise is high, and changes large when the current inventory quantity (O) of a specific consumable of the franchise is low; it is characterized by using the value obtained by dividing the total quantity (S) of the specific consumable currently ordered from the franchise branch by the estimated delivery time (T) to reflect that the need for additional warnings is reduced when there are many already ordered consumables and the delivery time is short; and the above notification reporting module is characterized by the inventory warning index (R alert A product inflow and outflow management system that predicts inventory shortages in advance by comprehensively analyzing inventory quantity, consumption patterns, and order status through a formula that calculates ), automatically sends an inventory shortage notification message to the relevant branch when a specific threshold value set and directly input through the manager terminal (500) is exceeded, performs analysis daily or at regular intervals in conjunction with real-time inventory data, and the notification reporting module automatically increases the warning sensitivity and sends a notification for additional ordering when the estimated delivery time (T) is prolonged. 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