A cloud platform-based goods management monitoring system and method

Abstract

The present invention relates to the field of goods management technology. Specifically, it is a goods management monitoring system and method based on a cloud platform. The goods management monitoring system includes a data acquisition module, a data analysis module, a goods management module and an alarm prompt module; the data acquisition module is to connect to the database on the server to obtain the data information of the warehouse and the goods through the database of the project deployed on the server when the client issues a goods distribution request; the data analysis module is to analyze the matching values ​​between the storage locations through the data information of the storage locations of the attribute characteristics of the goods; the goods management module is to analyze the impact rate of misplaced goods on the current goods distribution through the data information of the warehouse; the alarm prompt module is to make an alarm decision on the impact rate of goods distribution through the distribution impact analysis unit. In the present invention, by analyzing the matching relationship between the storage locations and goods in the warehouse and the impact rate of distribution, timely sorting of misplaced goods can improve the operation efficiency of the warehouse.

Description

Technical Field

[0001] The present invention relates to the technical field of goods management, and in particular to a goods management monitoring system and method based on a cloud platform. Background Art

[0002] With the advent of the information age, data has become an important cornerstone for corporate decision-making and development. Data collection, as an important link in obtaining data, has also received increasing attention. However, due to the diversity of data sources and the huge amount of data, the traditional manual collection method can no longer meet the needs of modern enterprises for data acquisition. Cloud platforms have emerged as the times require. Cloud platforms can not only improve data collection efficiency but also ensure data execution and security. Through cloud platforms, goods are managed and monitored. Through cloud computing technology, the information, inventory, flow and other data of goods are stored in the cloud to achieve remote, intelligent and efficient management of goods. The advantages of cloud platform goods management are: cost saving, no need to purchase and maintain expensive hardware equipment and software systems, only need to pay on-demand service fees. Improve efficiency, access the cloud platform through the Internet, you can query, transfer, inventory and other operations on goods anytime and anywhere, and realize real-time data synchronization and sharing. Enhance security, through the data backup and recovery function of the cloud platform, you can prevent data loss and damage, and at the same time, you can set different permissions and roles to protect the privacy and integrity of data. Flexible expansion, through the elastic scaling function of the cloud platform, you can dynamically adjust resources and services according to business needs to adapt to different scales and scenarios.

[0003] With the existing technology, more and more warehouses are beginning to use cloud platforms to monitor warehouses. When the storage locations of goods in the warehouse are irregular and the storage locations of misplaced goods are not sorted out in time, the management costs of goods and the impact rate of goods delivery orders will increase, resulting in low warehouse operation efficiency and warehousing operation efficiency. Summary of the invention

[0004] The purpose of the present invention is to provide a cloud platform-based goods management and monitoring system and method to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a commodity management and monitoring method based on a cloud platform, the commodity management and monitoring method specifically comprising the following steps:

[0006] S100, collecting data information of goods in the warehouse through the cloud platform, building a matching model based on the data information of the goods and the warehouse, analyzing the matching values ​​between the goods in the warehouse and the storage locations based on the matching model, building a corresponding relationship between the goods and the storage locations in the warehouse based on the matching values ​​between the goods and the storage locations, forming a storage location matching relationship, and storing the storage location matching relationship in the data terminal to avoid an increase in required storage resources due to mismatch between goods and storage locations;

[0007] S200. Although the cloud platform has established a corresponding relationship between goods and storage locations and formed a storage location matching relationship to store goods, in actual storage, there may be a situation where the storage location of goods is inconsistent with the corresponding storage location due to personnel errors and other reasons. On the basis of not wasting human resources to relocate and store goods, the logistics impact of distribution is analyzed, and the warehouse is inspected according to the storage location matching relationship to obtain data information of goods in the warehouse whose storage location does not match the storage location; data information of goods that currently need to be distributed is obtained through the terminal background, and the impact rate of misplaced goods on current distribution is analyzed according to the data information of the goods that currently need to be distributed and the storage data information of the goods in the current warehouse;

[0008] S300. Analyze the impact rate of misplaced goods on subsequent delivery based on the real-time storage data information of warehouse goods and the impact rate of misplaced goods on current delivery. When the impact rate of misplaced goods on subsequent delivery is greater than or equal to a preset impact threshold, issue an early warning and remind staff to manage the goods, prompting management personnel to take timely action to reduce resource losses.

[0009] Furthermore, the specific method of analyzing the matching values ​​between the goods and the storage locations in the warehouse based on the matching model to construct the corresponding relationship between the goods and the storage locations to form the storage location matching relationship in S100 is as follows:

[0010] S101. Obtain the warehouse location information, and generate a set U of the warehouse location information, where U = {U1, U2, U3 ... UJ}, where UJ represents the Jth warehouse location mapped to the three-dimensional space, j = 1, 2, 3 ... J, and J represents the total number of warehouse locations in the warehouse; obtain data information of goods through the cloud platform, where the data information of the goods includes the turnover rate, attribute characteristics, volume and quality of the goods, and generate an incompatible product pair set E based on the attribute characteristics of the goods;

[0011] S102, constructing a cargo location matching model, through which a suitable storage location is allocated to each product according to the demand and characteristics of the product, thereby improving the space utilization, operation efficiency and safety of the warehouse;

[0012] F(s)=w1 / C(s)+w2*S(s)+w3 / D(s)

[0013]

[0014]

[0015] g3(s)=sij+sik≤1,(i,k)∈E

[0016] F(s) is the matching value between goods and storage locations, which is the weighted sum of storage cost, shelf stability and product classification disorder. The weighted sum means that different goals have different importance, so it is multiplied by a weight coefficient. Among them, g1(s), g2(s) and g3(s) are constraints, which represent shelf capacity, single allocation and compatibility respectively. Constraints refer to the restrictions that must be met when obtaining the matching value between goods and storage locations. If the constraints are not met, the solution is infeasible or invalid. C(s) is the storage cost, which is related to the moving distance and turnover rate of the goods. The moving distance refers to the distance from the storage location to the warehouse entrance and exit, and the goods turnover rate refers to the distance from the storage location to the warehouse entrance and exit in unit time. The time from warehousing to outbound delivery; Generally speaking, the higher the turnover rate of goods and the shorter the moving distance of goods, the lower the cost of warehousing and outbound delivery; S(s) represents the stability of the shelf, which is related to the weight and placement height of the goods; weight refers to the quality of the goods, and placement height refers to the position of the goods on the shelf. Generally speaking, the heavier the weight of the goods and the higher the placement height, the worse the shelf stability; D(s) represents the degree of confusion in the classification of goods, which is related to the correlation between adjacent goods; correlation refers to the similarity or correlation between goods. The similarity between adjacent goods can be calculated by the cosine similarity formula. The lower the correlation between adjacent goods, the higher the confusion in the classification of goods; in the process of warehousing and outbound delivery, the degree of confusion in the classification of goods is higher. Under the condition that the warehouse cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between the goods and the warehouse location; under the condition that the cost of entering and leaving the warehouse and the degree of confusion in the classification of goods remain unchanged, the better the shelf stability, the higher the matching value between the goods and the warehouse location; under the condition that the shelf stability and the degree of confusion in the classification of goods remain unchanged, the lower the cost of entering and leaving the warehouse, the higher the matching value between the goods and the warehouse location; s is an i*j decision variable matrix, which represents the scheme of allocating the i-th goods to the j-th warehouse location, and the element sij is a binary variable, sij∈{0,1}, k∈{1, 2, 3...J}, k≠j, k represents the warehouse location adjacent to the j-th warehouse location; if sij=1, it means that the i-th goods are allocated to the j-th warehouse location; If sij=0, it means that the ith product is not allocated to the jth storage location; vi represents the volume of the ith product, Vj represents the capacity of the jth storage location, and E represents the set of incompatible product pairs; the product pair refers to the relationship between two or more products, such as compatibility, correlation, substitutability, etc.; the analysis and classification of product pairs can help warehouse managers optimize the storage location and method of products; for example, some products are incompatible, such as flammable, explosive, toxic, harmful, and corrosive products that cannot be stored together, otherwise it will cause safety hazards or quality losses; some products are related, such as products of the same category, the same attributes, and the same batch should be stored together for classification management and picking operations;

[0017] S103, seek to obtain the maximum matching value between the goods and the storage location, and remove the storage location from the storage location information set U after marking it, based on which the matching values ​​between the goods and the storage location are traversed to obtain the corresponding relationship between the goods and the storage location in the warehouse, and form a storage location matching relationship.

[0018] Furthermore, the specific method of analyzing the impact rate of misplaced goods on delivery based on the data information of the goods currently to be delivered and the storage data information of the goods in the current warehouse in S200 is as follows:

[0019] S201. Inspect the warehouse according to the cargo location matching relationship to obtain the storage location misplacement information and goods misplacement data information of the storage location that does not match the goods in the warehouse, and generate a storage location misplacement set u and a goods misplacement set c respectively. Since the storage location misplacement is caused by the wrong storage location of the goods, the number of goods misplacement and storage location misplacement is the same, and the misplaced goods and misplaced storage locations are one-to-one corresponding, u={u1, u2, u3...uJ'}, c={c1, c2, c3...cJ'}, uj' represents the j'th storage location misplacement information of the storage location that does not match the goods in the warehouse, and cj' represents the storage location that does not match the goods in the warehouse. The misplaced data information of the j'th item j'=1, 2, 3...J', because the items are stored under the matching relationship of the storage location, there may be a situation in which the storage location of the items is inconsistent with the corresponding storage location due to personnel errors and other reasons during the storage process, so the storage location information with errors cannot be greater than or equal to the number of existing storage locations, that is, J'<J; the data information of the items currently required to be delivered is obtained through the terminal background, recorded as the delivery item set a, a={a1, a2, a3...aR}, ar represents the rth item currently required to be delivered, r=1, 2, 3...R, and R represents the number of items currently required to be delivered;

[0020] S202, according to the formula:

[0021] f1=[K(c∩a) / K(a)]*100%

[0022] The impact rate of misplaced goods on the current delivery is calculated, and K() is represented by the number of subsets in the set; when the proportion of the number of misplaced goods in the number of goods that currently need to be delivered is larger, the impact rate of misplaced goods on the current delivery is also greater.

[0023] Furthermore, the specific method of analyzing the subsequent goods distribution impact rate according to the storage data information of the current warehouse goods in S300 is as follows:

[0024] S301, obtaining data information of subsequent goods that need to be delivered in the terminal background, wherein the subsequent goods that need to be delivered are the goods that need to be delivered in the next batch after the current goods need to be delivered, and are recorded as the subsequent delivery goods set a', a'={a'1, a'2, a'3...a'R'}, a'r' represents the r'th goods that need to be delivered subsequently, r'=1, 2, 3...R', R' represents the number of subsequent goods that need to be delivered; comparing the impact rate of the misplaced goods on the current delivery with the preset impact threshold z, when the impact rate of the misplaced goods on the current delivery is greater than or equal to the preset impact threshold, the impact rate of the misplaced goods on the current delivery has already affected the subsequent delivery, and the misplaced goods need to be sorted out;

[0025] According to the formula:

[0026] When f1 ≥ z

[0027] f2=β*f1+K(c∩a') / K(a')*100%

[0028] When f1<z

[0029] f2=K(c∩a') / K(a')*100%

[0030] The impact rate of the storage data information of the warehouse goods on the subsequent goods delivery is calculated, z is represented as the impact threshold affecting the subsequent goods delivery, and β is the coefficient; the impact rate of the misplaced goods on the subsequent delivery is analyzed based on the storage data information of the warehouse goods and the impact rate of the misplaced goods on the current delivery. When the impact rate of the current delivery exceeds a certain threshold, it will have an impact on the subsequent delivery, such as: when the goods that need to be delivered are being delivered, the efficiency of the current delivery is reduced due to the impact of the misplaced goods, and there is a lack of human resources for the subsequent delivery of goods.

[0031] S302: When the impact rate f2 of the subsequent goods distribution exceeds a preset impact threshold z', an alarm is issued, and the misplaced goods are managed according to the cargo location matching relationship.

[0032] A goods management and monitoring system based on a cloud platform, the goods management and monitoring system comprising a data acquisition module, a data analysis module, a goods management module and an alarm prompt module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the goods management module, and the output end of the goods management module is connected to the input end of the alarm prompt module; the data acquisition module is a database of a project deployed on a server, when a client issues a goods delivery request, it connects to the database on the server, and obtains warehouse and goods data information through the database, wherein the warehouse data information includes the volume of the warehouse location, misplaced location information etc.; the data analysis module analyzes the matching values ​​between storage locations through the attribute characteristics of the goods and the data information of the storage locations, and forms a storage location matching relationship based on the matching values ​​between the storage locations; the goods management module analyzes the impact rate of misplaced goods on the current goods distribution through the warehouse data information, and when the impact rate of the current goods distribution affects the subsequent goods distribution and causes the impact rate of the subsequent goods distribution to exceed the preset impact threshold, the storage location of the misplaced goods is rearranged; the alarm prompt module makes an alarm decision on the impact rate of goods distribution through the distribution impact analysis unit, and reminds the staff to rearrange the storage location of the misplaced goods.

[0033] Furthermore, the data collection module includes a warehouse data information collection unit and a goods data information collection unit; the warehouse data information collection unit is achieved by deploying a data collector on a cloud platform. The data collector can be a software application or a device, which is responsible for capturing warehouse data information from a data source. The collector can obtain data in different ways, such as API calls, crawler technology, sensor readings, etc.; the goods data information collection unit is achieved by deploying a data collector on a cloud platform. When a client issues a goods delivery request, the data collector connects to the database on the cloud platform server to capture the goods data information from the database. Since the cloud platform server can provide the collector with more flexible, efficient and stable storage and computing resources, the collector can better complete the data collection work; the relationship between the cargo locations can be analyzed based on the data information of the goods and warehouse.

[0034] Furthermore, the data analysis module includes a matching value analysis unit and a cargo location relationship analysis unit; the matching value analysis unit determines the best placement of goods by evaluating and analyzing the degree of matching between goods and storage locations, which can help warehouse managers arrange the storage locations of goods more effectively and improve the operating efficiency of the warehouse; the cargo location relationship analysis unit traverses the matching values ​​between goods and storage locations to obtain cargo location matching relationships, which can help optimize warehouse layout and cargo placement, making operations such as storage, picking and loading of goods more efficient; reasonable cargo location matching can reduce the time it takes to find goods and reduce the moving distance of personnel and equipment, thereby improving the efficiency of warehousing operations.

[0035] Furthermore, the goods management module includes a distribution impact analysis unit and a goods storage and sorting unit; the distribution impact analysis unit analyzes the impact rate of goods distribution; the goods storage and sorting unit rearranges the storage location of misplaced goods when the impact rate of current goods distribution affects subsequent goods distribution and causes the impact rate of subsequent goods distribution to exceed a preset impact threshold.

[0036] Furthermore, the alarm prompt module includes an alarm prompt unit and a decision unit; the alarm prompt unit issues an alarm prompt when the impact rate of misplaced goods on subsequent goods delivery exceeds a preset impact threshold; the decision unit issues an alarm and makes decisions on the storage location of the misplaced goods based on the impact rate on subsequent goods delivery.

[0037] Compared with the prior art, the beneficial effects achieved by the present invention are: by analyzing the matching values ​​between goods and storage locations, the present invention can improve storage efficiency, reduce error rates, optimize inventory management, increase order processing speed, and support intelligentization, thereby bringing higher benefits and competitive advantages to enterprises;

[0038] When there are misplaced goods, the impact rate on subsequent goods distribution is analyzed, and the storage location of the misplaced goods is adjusted based on the impact rate on subsequent goods distribution, so as to avoid reducing the efficiency of warehousing operations and save human resources to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0040] Figure 1 It is a structural diagram of a goods management and monitoring system based on a cloud platform. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] See also Figure 1 The present invention provides a technical solution: a commodity management and monitoring method based on a cloud platform, the commodity management and monitoring method specifically comprises the following steps:

[0043] S100, collecting data information of goods in the warehouse through the cloud platform, building a matching model based on the data information of the goods and the warehouse, analyzing the matching values ​​between the goods in the warehouse and the storage locations based on the matching model, building a corresponding relationship between the goods and the storage locations in the warehouse based on the matching values ​​between the goods and the storage locations, forming a storage location matching relationship, and storing the storage location matching relationship in the data terminal to avoid an increase in required storage resources due to mismatch between goods and storage locations;

[0044] S200. Although the cloud platform has established a corresponding relationship between goods and storage locations and formed a storage location matching relationship to store goods, in actual storage, there may be a situation where the storage location of goods is inconsistent with the corresponding storage location due to personnel errors and other reasons. On the basis of not wasting human resources to relocate and store goods, the logistics impact of distribution is analyzed, and the warehouse is inspected according to the storage location matching relationship to obtain data information of goods in the warehouse whose storage location does not match the storage location; data information of goods that currently need to be distributed is obtained through the terminal background, and the impact rate of misplaced goods on current distribution is analyzed according to the data information of the goods that currently need to be distributed and the storage data information of the goods in the current warehouse;

[0045] S300. Analyze the impact rate of misplaced goods on subsequent delivery based on the real-time storage data information of warehouse goods and the impact rate of misplaced goods on current delivery. When the impact rate of misplaced goods on subsequent delivery is greater than or equal to a preset impact threshold, issue an early warning and remind staff to manage the goods, prompting management personnel to take timely action to reduce resource losses.

[0046] Furthermore, the specific method of analyzing the matching values ​​between the goods and the storage locations in the warehouse based on the matching model to construct the corresponding relationship between the goods and the storage locations to form the storage location matching relationship in S100 is as follows:

[0047] S101. Obtain the warehouse location information, and generate a set U of the warehouse location information, where U = {U1, U2, U3 ... UJ}, where UJ represents the Jth warehouse location mapped to the three-dimensional space, j = 1, 2, 3 ... J, and J represents the total number of warehouse locations in the warehouse; obtain data information of goods through the cloud platform, where the data information of the goods includes the turnover rate, attribute characteristics, volume and quality of the goods, and generate an incompatible product pair set E based on the attribute characteristics of the goods;

[0048] S102, constructing a cargo location matching model, through which a suitable storage location is allocated to each product according to the demand and characteristics of the product, thereby improving the space utilization, operation efficiency and safety of the warehouse;

[0049] F(s)=w1 / C(s)+w2*S(s)+w3 / D(s)

[0050]

[0051]

[0052] g3(s)=sij+sik≤1,(i,k)∈E

[0053] F(s) is the matching value between goods and storage locations, which is the weighted sum of storage cost, shelf stability and product classification disorder. The weighted sum means that different goals have different importance, so it is multiplied by a weight coefficient. Among them, g1(s), g2(s) and g3(s) are constraints, which represent shelf capacity, single allocation and compatibility respectively. Constraints refer to the restrictions that must be met when obtaining the matching value between goods and storage locations. If the constraints are not met, the solution is infeasible or invalid. C(s) is the storage cost, which is related to the moving distance and turnover rate of the goods. The moving distance refers to the distance from the storage location to the warehouse entrance and exit, and the goods turnover rate refers to the distance from the storage location to the warehouse entrance and exit in unit time. The time from warehousing to outbound delivery; Generally speaking, the higher the turnover rate of goods and the shorter the moving distance of goods, the lower the cost of warehousing and outbound delivery; S(s) represents the stability of the shelf, which is related to the weight and placement height of the goods; weight refers to the quality of the goods, and placement height refers to the position of the goods on the shelf. Generally speaking, the heavier the weight of the goods and the higher the placement height, the worse the shelf stability; D(s) represents the degree of confusion in the classification of goods, which is related to the correlation between adjacent goods; correlation refers to the similarity or correlation between goods. The similarity between adjacent goods can be calculated by the cosine similarity formula. The lower the correlation between adjacent goods, the higher the confusion in the classification of goods; in the process of warehousing and outbound delivery, the degree of confusion in the classification of goods is higher. Under the condition that the warehouse cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between the goods and the warehouse location; under the condition that the cost of entering and leaving the warehouse and the degree of confusion in the classification of goods remain unchanged, the better the shelf stability, the higher the matching value between the goods and the warehouse location; under the condition that the shelf stability and the degree of confusion in the classification of goods remain unchanged, the lower the cost of entering and leaving the warehouse, the higher the matching value between the goods and the warehouse location; s is an i*j decision variable matrix, which represents the scheme of allocating the i-th goods to the j-th warehouse location, and the element sij is a binary variable, sij∈{0,1}, k∈{1, 2, 3...J}, k≠j, k represents the warehouse location adjacent to the j-th warehouse location; if sij=1, it means that the i-th goods are allocated to the j-th warehouse location; If sij=0, it means that the ith product is not allocated to the jth storage location; vi represents the volume of the ith product, Vj represents the capacity of the jth storage location, and E represents the set of incompatible product pairs; the product pair refers to the relationship between two or more products, such as compatibility, correlation, substitutability, etc.; the analysis and classification of product pairs can help warehouse managers optimize the storage location and method of products; for example, some products are incompatible, such as flammable, explosive, toxic, harmful, and corrosive products that cannot be stored together, otherwise it will cause safety hazards or quality losses; some products are related, such as products of the same category, the same attributes, and the same batch should be stored together for classification management and picking operations;

[0054] S103, seek to obtain the maximum matching value between the goods and the storage location, and remove the storage location from the storage location information set U after marking it, based on which the matching values ​​between the goods and the storage location are traversed to obtain the corresponding relationship between the goods and the storage location in the warehouse, and form a storage location matching relationship.

[0055] Furthermore, the specific method of analyzing the impact rate of misplaced goods on delivery based on the data information of the goods currently to be delivered and the storage data information of the goods in the current warehouse in S200 is as follows:

[0056] S201. Inspect the warehouse according to the cargo location matching relationship to obtain the storage location misplacement information and goods misplacement data information of the storage location that does not match the goods in the warehouse, and generate a storage location misplacement set u and a goods misplacement set c respectively. Since the storage location misplacement is caused by the wrong storage location of the goods, the number of goods misplacement and storage location misplacement is the same, and the misplaced goods and misplaced storage locations are one-to-one corresponding, u={u1, u2, u3...uJ'}, c={c1, c2, c3...cJ'}, uj' represents the j'th storage location misplacement information of the storage location that does not match the goods in the warehouse, and cj' represents the storage location that does not match the goods in the warehouse. The misplaced data information of the j'th item j'=1, 2, 3...J', because the items are stored under the matching relationship of the storage location, there may be a situation in which the storage location of the items is inconsistent with the corresponding storage location due to personnel errors and other reasons during the storage process, so the storage location information with errors cannot be greater than or equal to the number of existing storage locations, that is, J'<J; the data information of the items currently required to be delivered is obtained through the terminal background, recorded as the delivery item set a, a={a1, a2, a3...aR}, ar represents the rth item currently required to be delivered, r=1, 2, 3...R, and R represents the number of items currently required to be delivered;

[0057] S202, according to the formula:

[0058] f1=[K(c∩a) / K(a)]*100%

[0059] The impact rate of misplaced goods on the current delivery is calculated, and K() is represented by the number of subsets in the set; when the proportion of the number of misplaced goods in the number of goods that currently need to be delivered is larger, the impact rate of misplaced goods on the current delivery is also greater.

[0060] Furthermore, the specific method of analyzing the subsequent goods distribution impact rate according to the storage data information of the current warehouse goods in S300 is as follows:

[0061] S301, obtaining data information of subsequent goods that need to be delivered in the terminal background, wherein the subsequent goods that need to be delivered are the goods that need to be delivered in the next batch after the current goods need to be delivered, and are recorded as the subsequent delivery goods set a', a'={a'1, a'2, a'3...a'R'}, a'r' represents the r'th goods that need to be delivered subsequently, r'=1, 2, 3...R', R' represents the number of subsequent goods that need to be delivered; comparing the impact rate of the misplaced goods on the current delivery with the preset impact threshold z, when the impact rate of the misplaced goods on the current delivery is greater than or equal to the preset impact threshold, the impact rate of the misplaced goods on the current delivery has already affected the subsequent delivery, and the misplaced goods need to be sorted out;

[0062] According to the formula:

[0063] When f1 ≥ z

[0064] f2=β*f1+K(c∩a') / K(a')*100%

[0065] When f1<z

[0066] f2=K(c∩a') / K(a')*100%

[0067] The impact rate of the storage data information of the warehouse goods on the subsequent goods delivery is calculated, z is represented as the impact threshold affecting the subsequent goods delivery, and β is the coefficient; the impact rate of the misplaced goods on the subsequent delivery is analyzed based on the storage data information of the warehouse goods and the impact rate of the misplaced goods on the current delivery. When the impact rate of the current delivery exceeds a certain threshold, it will have an impact on the subsequent delivery, such as: when the goods that need to be delivered are being delivered, the efficiency of the current delivery is reduced due to the impact of the misplaced goods, and there is a lack of human resources for the subsequent delivery of goods.

[0068] S302: When the impact rate f2 of the subsequent goods distribution exceeds a preset impact threshold z', an alarm is issued, and the misplaced goods are managed according to the cargo location matching relationship.

[0069] A goods management and monitoring system based on a cloud platform, the goods management and monitoring system comprising a data acquisition module, a data analysis module, a goods management module and an alarm prompt module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the goods management module, and the output end of the goods management module is connected to the input end of the alarm prompt module; the data acquisition module is a database of a project deployed on a server, when a client issues a goods delivery request, it connects to the database on the server, and obtains warehouse and goods data information through the database, wherein the warehouse data information includes the volume of the warehouse location, misplaced location information etc.; the data analysis module analyzes the matching values ​​between storage locations through the attribute characteristics of the goods and the data information of the storage locations, and forms a storage location matching relationship based on the matching values ​​between the storage locations; the goods management module analyzes the impact rate of misplaced goods on the current goods distribution through the warehouse data information, and when the impact rate of the current goods distribution affects the subsequent goods distribution and causes the impact rate of the subsequent goods distribution to exceed the preset impact threshold, the storage location of the misplaced goods is rearranged; the alarm prompt module makes an alarm decision on the impact rate of goods distribution through the distribution impact analysis unit, and reminds the staff to rearrange the storage location of the misplaced goods.

[0070] Furthermore, the data collection module includes a warehouse data information collection unit and a goods data information collection unit; the warehouse data information collection unit is achieved by deploying a data collector on a cloud platform. The data collector can be a software application or a device, which is responsible for capturing warehouse data information from a data source. The collector can obtain data in different ways, such as API calls, crawler technology, sensor readings, etc.; the goods data information collection unit is achieved by deploying a data collector on a cloud platform. When a client issues a goods delivery request, the data collector connects to the database on the cloud platform server to capture the goods data information from the database. Since the cloud platform server can provide the collector with more flexible, efficient and stable storage and computing resources, the collector can better complete the data collection work; the relationship between the cargo locations can be analyzed based on the data information of the goods and warehouse.

[0071] Furthermore, the data analysis module includes a matching value analysis unit and a cargo location relationship analysis unit; the matching value analysis unit determines the best placement of goods by evaluating and analyzing the degree of matching between goods and storage locations, which can help warehouse managers arrange the storage locations of goods more effectively and improve the operating efficiency of the warehouse; the cargo location relationship analysis unit traverses the matching values ​​between goods and storage locations to obtain cargo location matching relationships, which can help optimize warehouse layout and cargo placement, making operations such as storage, picking and loading of goods more efficient; reasonable cargo location matching can reduce the time it takes to find goods and reduce the moving distance of personnel and equipment, thereby improving the efficiency of warehousing operations.

[0072] Furthermore, the goods management module includes a distribution impact analysis unit and a goods storage and sorting unit; the distribution impact analysis unit analyzes the impact rate of goods distribution; the goods storage and sorting unit rearranges the storage location of misplaced goods when the impact rate of current goods distribution affects subsequent goods distribution and causes the impact rate of subsequent goods distribution to exceed a preset impact threshold.

[0073] Furthermore, the alarm prompt module includes an alarm prompt unit and a decision unit; the alarm prompt unit issues an alarm prompt when the impact rate of misplaced goods on subsequent goods delivery exceeds a preset impact threshold; the decision unit issues an alarm and makes decisions on the storage location of the misplaced goods based on the impact rate on subsequent goods delivery.

[0074] In this embodiment:

[0075] Obtain the warehouse location information, and generate a set U of the location information, where U = {U1, U2, U3...UJ}, where UJ represents the Jth location mapped from the warehouse to the three-dimensional space, j = 1, 2, 3...J, and J represents the total number of locations in the warehouse; obtain the data information of the goods through the cloud platform, where the data information of the goods includes the turnover rate, attribute characteristics, volume and quality of the goods, and generate an incompatible set of goods pairs E according to the attribute characteristics of the goods;

[0076] Build a cargo location matching model:

[0077] F(s)=w1 / C(s)+w2*S(s)+w3 / D(s)

[0078]

[0079]

[0080] g3(s)=sij+sik≤1,(i,k)∈E

[0081] F(s) represents the matching value between goods and storage locations, where g1(s), g2(s), and g3(s) are constraints that represent shelf capacity, single allocation, and compatibility, respectively. Constraints refer to the restrictions that must be met when obtaining the matching value between goods and storage locations. If the constraints are not met, the solution is infeasible or invalid. C(s) represents the in-and-out cost, S(s) represents the shelf stability, and D(s) represents the degree of confusion in the classification of goods. When the in-and-out cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between goods and storage locations. When the in-and-out cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between goods and storage locations. Under the condition that the degree of classification disorder remains unchanged, the better the shelf stability, the higher the matching value between the goods and the storage location; under the condition that the shelf stability and the degree of classification disorder of the goods remain unchanged, the lower the in-and-out cost, the higher the matching value between the goods and the storage location; s is an i*j decision variable matrix, which represents the scheme of allocating the i-th goods to the j-th storage location. The element sij is a binary variable, sij∈{0,1}, k∈{1, 2, 3...J}, k≠j, k represents the storage location adjacent to the j-th storage location; vi represents the volume of the i-th goods, Vj represents the capacity of the j-th storage location, and E represents the set of incompatible pairs of goods;;

[0082] The matching values ​​of different goods in different storage locations can be obtained as {1, 15, 12, 9, 6, 7, 2....}, {6, 8, 12, 15, 3, 8, 1....}, {14, 10, 2, 6, 9, 15, 3....}.... According to the matching values ​​of different goods in different storage locations, the maximum matching value between the goods and the storage locations is sought, and the storage locations are marked and removed from the storage location information set U. Based on this, the matching values ​​between the goods and the storage locations are traversed to obtain the corresponding relationship between the goods and the storage locations in the warehouse, and form a cargo location matching relationship.

[0083] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0084] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A commodity management and monitoring method based on a cloud platform, characterized in that: The goods management and monitoring method specifically comprises the following steps: S100, collecting data information of goods in the warehouse through the cloud platform, building a matching model based on the data information of the goods and the warehouse, analyzing the matching values ​​between the goods in the warehouse and the storage locations based on the matching model, building a corresponding relationship between the goods in the warehouse and the storage locations based on the matching values ​​between the goods and the storage locations, and forming a storage location matching relationship; S200, inspecting the warehouse according to the cargo location matching relationship, obtaining data information of goods whose storage locations in the warehouse do not match the storage locations; obtaining data information of goods that currently need to be delivered through the terminal background, and analyzing the impact rate of misplaced goods on current delivery based on the data information of goods that currently need to be delivered and the storage data information of goods in the current warehouse; S300, analyzing the impact rate of misplaced goods on subsequent delivery based on the real-time storage data information of warehouse goods and the impact rate of misplaced goods on current delivery, and when the impact rate of misplaced goods on subsequent delivery is greater than or equal to a preset impact threshold, issuing an early warning and reminding staff to manage the goods; The specific method of analyzing the matching values ​​between the goods and the storage locations in the warehouse based on the matching model to construct the corresponding relationship between the goods and the storage locations to form the storage location matching relationship in S100 is as follows: S101. Obtain the warehouse location information, and generate a set U of the warehouse location information, where U = {U1, U2, U3 ... UJ}, where UJ represents the Jth warehouse location mapped to the three-dimensional space, j = 1, 2, 3 ... J, and J represents the total number of warehouse locations in the warehouse; obtain data information of goods through the cloud platform, where the data information of the goods includes the turnover rate, attribute characteristics, volume and quality of the goods, and generate an incompatible product pair set E based on the attribute characteristics of the goods; S102. Build a cargo location matching model F(s)=w1 / C(s)+w2*S(s)+w3 / D(s) g3(s)=sij+sik≤1,(i,k)∈E F(s) represents the matching value between goods and storage locations, where g1(s), g2(s), and g3(s) are constraints that represent shelf capacity, single allocation, and compatibility, respectively. Constraints refer to the restrictions that must be met when obtaining the matching value between goods and storage locations. If the constraints are not met, the solution is infeasible or invalid. C(s) represents the in-and-out cost, S(s) represents the shelf stability, and D(s) represents the degree of confusion in the classification of goods. When the in-and-out cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between goods and storage locations. When the in-and-out cost and shelf stability remain unchanged, the smaller the degree of confusion in the classification of goods, the higher the matching value between goods and storage locations. Under the condition that the degree of disorder in product classification remains unchanged, the better the shelf stability, the higher the matching value between the product and the storage location; under the condition that the shelf stability and the degree of disorder in product classification remain unchanged, the lower the in-and-out cost, the higher the matching value between the product and the storage location; s is an i*j decision variable matrix, which represents the scheme of allocating the i-th product to the j-th storage location, and the element sij is a binary variable, sij∈{0,1}, k∈{1, 2, 3...J}, k≠j, k represents the storage location adjacent to the j-th storage location; vi represents the volume of the i-th product, Vj represents the capacity of the j-th storage location, and E represents the set of incompatible product pairs; S103, seeking to obtain the maximum matching value between the goods and the storage location, and removing the storage location from the storage location information set U after marking it, and based on this, traversing the matching values ​​between the goods and the storage location, obtaining the corresponding relationship between the goods and the storage location in the warehouse, and forming a storage location matching relationship; The specific method of analyzing the impact rate of misplaced goods on delivery based on the data information of the goods that need to be delivered and the storage data information of the goods in the current warehouse in S200 is as follows: S201. Inspect the warehouse according to the cargo location matching relationship, obtain the warehouse location misplacement information and cargo misplacement data information of the storage location that does not match the cargo in the warehouse, and generate a warehouse location misplacement set u and a cargo misplacement set c respectively, u={u1, u2, u3...uJ'}, c={c1, c2, c3...cJ'}, uj' represents the j'th warehouse location misplacement information of the storage location that does not match the cargo in the warehouse, cj' represents the j'th cargo misplacement data information of the storage location that does not match the cargo in the warehouse, j'=1, 2, 3...J', J'<J; obtain the cargo data information that needs to be delivered currently through the terminal background, recorded as the delivery cargo set a, a={a1, a2, a3...aR}, ar represents the rth cargo that needs to be delivered currently, r=1, 2, 3...R, R represents the number of cargo that needs to be delivered currently; S202, according to the formula: f1=[K(c∩a) / K(a)]*100% The impact rate of misplaced goods on the current delivery is calculated, and K() is represented by the number of subsets in the set.

2. The method for managing and monitoring goods based on a cloud platform according to claim 1, characterized in that: The specific method of analyzing the subsequent goods distribution impact rate based on the storage data information of the current warehouse goods in S300 is as follows: S301, obtain the data information of the subsequent delivery items from the terminal background, record it as the subsequent delivery item set a', a' = {a'1, a'2, a'3 ... a'R'}, a'r' represents the r'th item that needs to be delivered, r' = 1, 2, 3 ... R', R' represents the number of items that need to be delivered; according to the formula: When f1 ≥ z f2=β*f1+K(c∩a') / K(a')*100% When f1<z f2=K(c∩a') / K(a')*100% The influence rate of the storage data information of the warehouse goods on the subsequent goods delivery is calculated, z is represented as the influence threshold affecting the subsequent goods delivery, and β is the coefficient; S302: When the impact rate f2 of the subsequent goods distribution exceeds a preset impact threshold z', an alarm is issued, and the misplaced goods are managed according to the cargo location matching relationship.

3. A goods management and monitoring system using the cloud platform-based goods management and monitoring method according to any one of claims 1 to 2, characterized in that: The goods management and monitoring system includes a data acquisition module, a data analysis module, a goods management module and an alarm prompt module; the output end of the data acquisition module is connected to the input end of the data analysis module, the output end of the data analysis module is connected to the input end of the goods management module, and the output end of the goods management module is connected to the input end of the alarm prompt module; the data acquisition module is a database of the project deployed on the server, and when the client issues a goods delivery request, it connects to the database on the server and obtains data information of the warehouse and the goods through the database; the data analysis module analyzes the matching values ​​between the cargo locations through the attribute characteristics of the goods and the data information of the warehouse location, and forms a cargo location matching relationship based on the matching values ​​between the cargo locations; the goods management module analyzes the impact rate of misplaced goods on the current goods delivery through the warehouse data information, and when the impact rate of the current goods delivery affects the subsequent goods delivery and causes the impact rate of the subsequent goods delivery to exceed the preset impact threshold, the storage location of the misplaced goods is rearranged; the alarm prompt module makes an alarm decision on the impact rate of goods delivery through the delivery impact analysis unit, and reminds the staff to rearrange the storage location of the misplaced goods.

4. The product management and monitoring system according to claim 3, characterized in that: The data acquisition module includes a warehouse data information acquisition unit and a goods data information acquisition unit; the warehouse data information acquisition unit is achieved by deploying a data collector on the cloud platform, and the data collector is responsible for capturing warehouse data information from the data source; the goods data information acquisition unit is achieved by deploying a data collector on the cloud platform, and when the client sends a goods delivery request, the data collector connects to the database on the cloud platform server to capture the goods data information from the database, and the relationship between the cargo locations can be analyzed based on the goods and warehouse data information.

5. The product management and monitoring system according to claim 4, characterized in that: The data analysis module includes a matching value analysis unit and a cargo location relationship analysis unit; the matching value analysis unit determines the best placement of goods by evaluating and analyzing the matching degree between goods and storage locations; the cargo location relationship analysis unit traverses the matching values ​​between goods and storage locations to obtain cargo location matching relationships.

6. The product management and monitoring system according to claim 5, characterized in that: The goods management module includes a distribution impact analysis unit and a goods storage and sorting unit; the distribution impact analysis unit analyzes the impact rate of goods distribution; the goods storage and sorting unit rearranges the storage location of misplaced goods when the impact rate of current goods distribution affects subsequent goods distribution and causes the impact rate of subsequent goods distribution to exceed a preset impact threshold.

7. The product management and monitoring system according to claim 6, characterized in that: The alarm prompt module includes an alarm prompt unit and a decision unit; the alarm prompt unit is used to issue an alarm prompt when the impact rate of misplaced goods on subsequent goods delivery exceeds a preset impact threshold; The decision-making unit makes warnings and makes decisions on the storage location of misplaced goods based on the impact rate on subsequent goods distribution.

Images