Resource allocation method and device and computer equipment

Abstract

The invention relates to a resource allocation method and device and computer equipment, and the method comprises the steps: determining the required material information of all asset-level equipment based on the mapping relation between the asset-level equipment and material categories; and performing allocation processing according to the required material information of each asset-level device and the to-be-allocated material list to obtain material allocation information of each asset-level device. According to the method, the mapping relation between the asset-level equipment and the material categories is established, so that the required material is accurately positioned for each asset-level equipment. The mapping relation is obtained through deep analysis and carding, and the characteristics and functions of different asset-level devices and the actual requirements in the production or operation process can be fully considered. Therefore, when the material information required by each asset-level device is determined, subjective guessing and misjudgment can be avoided to the greatest extent, and the accuracy of the required material information is ensured.

Description

Technical Field

[0001] The present application relates to the technical field of asset equipment management of power grid enterprises, and in particular to a resource allocation method, device and computer equipment. Background Art

[0002] As a heavy asset enterprise, power grid enterprises have many high-value assets, so refined management of equipment assets is crucial. When the asset equipment reaches the predetermined usable state, it is necessary to cooperate with the finance department to carry out equipment transfer work, and allocate the value of various main materials and auxiliary materials generated during the construction process of the equipment assets to the corresponding asset-level equipment as an important part of the final value of the asset-level equipment.

[0003] Currently in power grid companies, there is a lot of manual work involved in material allocation, the allocation of materials to asset-level equipment is time-consuming, and there is a problem of inaccurate allocation results. Summary of the invention

[0004] Based on this, it is necessary to provide a resource allocation method, device and computer equipment that can improve the accuracy of allocation results in response to the above technical problems.

[0005] In a first aspect, the present application provides a resource allocation method, the method comprising:

[0006] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0007] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0008] In one embodiment, the required material information of each asset-level equipment is determined based on the mapping relationship between the asset-level equipment and the material category, including:

[0009] Based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment;

[0010] According to the target material category, the required material information of each asset-level equipment is found from the allocation template, where the allocation template includes material configurations of different material categories.

[0011] In one embodiment, the material allocation information of each asset-level equipment is obtained by performing the allocation process according to the required material information of each asset-level equipment and the list of materials to be allocated, including:

[0012] For each material to be allocated in the list of materials to be allocated, if it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among multiple asset-level devices, the material to be allocated is allocated to the target asset-level device;

[0013] When it is determined based on the mapping relationship that there is no corresponding relationship between the material to be apportioned and multiple asset-level equipment, the material to be apportioned is apportioned based on the historical apportionment records;

[0014] Determine the material allocation information for each asset-level equipment based on the allocation results of each material to be allocated.

[0015] In one embodiment, the above-mentioned materials to be allocated include main materials and auxiliary materials; when it is determined according to the mapping relationship that there is a corresponding relationship between the materials to be allocated and the target asset-level equipment among the multiple asset-level equipments, the materials to be allocated are allocated to the target asset-level equipment, including:

[0016] When it is determined according to the mapping relationship that there is a corresponding relationship between the main material and the target asset-level equipment among the multiple asset-level equipment, the main material is allocated to the target asset-level equipment;

[0017] When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and the target asset-level equipment among the multiple asset-level equipments, the auxiliary material is allocated to the target asset-level equipment.

[0018] In one embodiment, when it is determined according to the mapping relationship that there is no corresponding relationship between the material to be allocated and the multiple asset-level equipment, the material to be allocated is allocated according to the historical allocation record, including:

[0019] Perform apportionment probability statistics based on historical apportionment records to determine the recommended allocation method for the materials to be apportioned;

[0020] Allocate the materials to be allocated according to the recommended allocation method.

[0021] In one embodiment, the method further comprises:

[0022] Optimizing the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors;

[0023] The materials to be allocated are allocated according to the optimized allocation method.

[0024] In one embodiment, the method further comprises:

[0025] Determine the asset value list based on the asset-level equipment to be allocated;

[0026] Perform template retrieval processing on the asset value list to obtain retrieval results;

[0027] When the search result indicates that there is no main and auxiliary material template, a step of determining required material information of each asset-level equipment based on a mapping relationship between asset-level equipment and material categories is performed.

[0028] In one embodiment, the method further comprises:

[0029] When the search results indicate that there are main and auxiliary material templates, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material templates to obtain material allocation information.

[0030] In a second aspect, the present application also provides a resource allocation device. The device includes:

[0031] The information determination module is used to determine the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories;

[0032] The allocation module is used to perform allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated, and obtain the material allocation information of each asset-level equipment.

[0033] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0034] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0035] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0037] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0038] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0039] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0040] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0041] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0042] The above-mentioned resource allocation method, device and computer equipment determine the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories; the allocation processing is performed according to the required material information of each asset-level equipment and the list of materials to be allocated, and the material allocation information of each asset-level equipment is obtained. This application accurately locates the required materials for each asset-level equipment by establishing a mapping relationship between asset-level equipment and material categories. The above-mentioned mapping relationship is obtained after in-depth analysis and sorting, and can fully consider the characteristics, functions and actual needs of different asset-level equipment during production or operation. Therefore, when determining the required material information of each asset-level equipment, subjective speculation and misjudgment can be avoided to the greatest extent, ensuring the accuracy of the required material information. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 An application environment diagram of a resource allocation method in an embodiment;

[0044] Figure 2 A schematic diagram of a process flow of a resource allocation method in an embodiment;

[0045] Figure 3 A schematic diagram of a process for determining required material information for each asset-level device in an embodiment;

[0046] Figure 4 A schematic diagram of a process for obtaining material allocation information of each asset-level device in an embodiment;

[0047] Figure 5 It is a schematic diagram of a process of apportioning materials to be apportioned in one embodiment;

[0048] Figure 6 It is a schematic diagram of a process of allocating materials according to an optimized allocation method in one embodiment;

[0049] Figure 7 A schematic diagram of a flow chart of a resource allocation method in another embodiment;

[0050] Figure 8 It is a structural block diagram of a resource allocation device in an embodiment;

[0051] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0053] First of all, before specifically introducing the technical solution of the embodiments of the present application, the technical background based on the embodiments of the present application is introduced.

[0054] As a heavy asset enterprise, power grid enterprises have many assets and high value. Therefore, refined management of equipment assets is particularly important in the management of power grid enterprises. When the asset equipment reaches the predetermined usable state, it is necessary to cooperate with the finance department to carry out equipment transfer work. The value of various main materials and auxiliary materials generated during the construction of equipment assets needs to be allocated to the corresponding asset-level equipment as an important part of the final value of the asset-level equipment.

[0055] However, in power grid companies, there are still a lot of manual operations in material allocation. The allocation amounts of main and auxiliary materials need to be calculated manually. The allocation of materials and asset-level equipment takes a long time, and there are cases where the allocation amounts are inaccurate. There are also problems such as poor collaboration and incomplete operation coverage in the collaborative transfer of business and finance, making it impossible to achieve automated asset value allocation.

[0056] At present, the closest relevant technology for power grid companies in material allocation and capital transfer business is still the traditional manual operation method. Material allocation involves a large number of manual operations, and the allocation amounts of main and auxiliary materials need to be calculated manually. This traditional manual operation method is the current situation faced by power grid companies, and it is also an aspect that needs to be improved and optimized. The more advanced technology or method in contrast is exactly what this application hopes to seek and develop, in order to solve the various drawbacks brought about by the existing manual operation method, improve the efficiency and accuracy of the refined management of equipment assets, and achieve smoother coordination between business and finance and automation of asset value allocation.

[0057] Based on this, the present application provides a resource allocation method, apparatus and computer equipment, aiming to solve the above technical problems.

[0058] The resource allocation method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The terminal determines the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories; the allocation processing is performed according to the required material information of each asset-level equipment and the list of materials to be allocated, and the material allocation information of each asset-level equipment is obtained. The present application accurately defines each asset-level equipment by establishing a mapping relationship between asset-level equipment and material categories. Among them, the terminal 102 can be but is not limited to various personal computers, laptops, smart phones and tablets. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0059] In an exemplary embodiment, Figure 2 As shown, the present application provides a resource allocation method, which is applied to Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0060] S201, based on the mapping relationship between asset-level equipment and material categories, determine the required material information of each asset-level equipment.

[0061] Among them, asset-level equipment refers to equipment that has independent value and function in the production and operation activities of an enterprise, such as machines on a production line, computers in an office, etc.

[0062] Material category: The category name for classifying various materials, such as raw materials, parts, tools, etc.

[0063] Mapping relationship: Establish a corresponding relationship between asset-level equipment and material categories, that is, determine which material categories a specific asset-level equipment needs to support its normal operation and function.

[0064] In the embodiment of the present application, first, all asset-level equipment in the enterprise is comprehensively sorted and classified to clarify the functions, uses and characteristics of each asset-level equipment. Then, according to the classification standards of material categories, a mapping relationship between asset-level equipment and material categories is established. For example, a specific model of production equipment may establish a mapping relationship with specific material categories such as parts, raw materials and tools. Through this mapping relationship, the material information required for each asset-level equipment during normal operation and maintenance can be determined.

[0065] Another implementation method of the embodiment of the present application: a data analysis method can be used to establish a mapping relationship. Collect a large amount of asset-level equipment operation data and material usage data, and automatically discover the potential relationship between asset-level equipment and material categories through data mining and machine learning algorithms. For example, use an association rule mining algorithm to find asset-level equipment and material categories that are often used together, so as to establish a mapping relationship. When determining the required material information, the historical maintenance records and fault reports of the equipment can be combined to analyze the materials required in different fault situations, and further improve the required material information.

[0066] S202, performing allocation processing according to the required material information of each asset-level equipment and the list of materials to be allocated, and obtaining the material allocation information of each asset-level equipment.

[0067] Among them, the required material information refers to the specific material type, quantity, specifications and other information required by each asset-level equipment determined according to the mapping relationship.

[0068] List of materials to be allocated: a list of all materials available for allocation, including the name, quantity, value and other information of the materials.

[0069] Material allocation information: the specific situation of the materials finally obtained by each asset-level equipment, including the type, quantity, source and other information of the allocated materials.

[0070] The embodiment of the present application compares and matches the required material information of each asset-level equipment with the list of materials to be allocated. A reasonable allocation strategy is formulated based on factors such as the quantity, value, and priority of the materials. For example, materials can be allocated according to the importance and urgency of asset-level equipment, giving priority to key equipment and equipment with urgent needs. During the allocation process, it is necessary to ensure that the distribution of materials is fair, reasonable, and efficient, and avoid material waste and uneven distribution.

[0071] Another implementation method of the present application embodiment is to introduce an intelligent optimization algorithm to perform material allocation processing. For example, a genetic algorithm or a simulated annealing algorithm is used to automatically search for the optimal material allocation plan with the objective function of minimizing the material allocation cost or maximizing the equipment operation efficiency. At the same time, it is possible to consider establishing a dynamic material allocation model to adjust the material allocation information in real time according to the changes in the enterprise's production plan and equipment operation status to ensure that the material allocation always remains in the optimal state.

[0072] The above-mentioned resource allocation method determines the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories; the allocation process is performed according to the required material information of each asset-level equipment and the list of materials to be allocated to obtain the material allocation information of each asset-level equipment. This application accurately locates the required materials for each asset-level equipment by establishing a mapping relationship between asset-level equipment and material categories. The above-mentioned mapping relationship is obtained after in-depth analysis and sorting, and can fully take into account the characteristics, functions and actual needs of different asset-level equipment during production or operation. Therefore, when determining the required material information of each asset-level equipment, subjective speculation and misjudgment can be avoided to the greatest extent, ensuring the accuracy of the required material information.

[0073] In an exemplary embodiment, based on the above embodiment, see Figure 3 The embodiment of the present application relates to a process of determining the required material information of each asset-level device based on the mapping relationship between asset-level devices and material categories, including the following steps:

[0074] S301, based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment.

[0075] The target material category is a material category corresponding to a specific asset-level device determined by a mapping relationship between asset-level equipment and material categories.

[0076] The embodiment of the present application first establishes and maintains a comprehensive database of mapping relationships between asset-level equipment and material categories. This database can be continuously improved and updated through analysis of historical enterprise data, summary of expert experience, and observation of actual production processes. For each asset-level equipment, according to its function, structure, technical parameters and other characteristics, the corresponding material category is searched in the mapping database, thereby determining the target material category corresponding to each asset-level equipment.

[0077] Another implementation method of the present application embodiment: using machine learning algorithms to automatically establish and optimize the mapping relationship between asset-level equipment and material categories. Collect a large amount of asset-level equipment operation data and material usage data, and use supervised learning algorithms, such as support vector machines, decision trees, etc., to train a model to predict the target material category corresponding to the asset-level equipment. In actual applications, new data is continuously input into the model for optimization and adjustment to improve the accuracy and reliability of the mapping relationship.

[0078] S302, searching for required material information of each asset-level equipment from an allocation template according to the target material category, wherein the allocation template includes material configurations of different material categories.

[0079] Among them, the allocation template is a pre-set template containing material configurations of different material categories, which is used to determine the specific material information required for each asset-level equipment. The material configuration includes information such as the quantity, specifications, and quality requirements of different material categories.

[0080] The embodiment of the present application first constructs a detailed allocation template, which covers all possible material categories of the enterprise and the specific material configuration information of each material category. After determining the target material category corresponding to the asset-level equipment, the material configuration of these target material categories is searched in the allocation template. The material configuration information may include the name, specification, quantity, quality requirements, supplier information, etc. of the material. Based on this configuration information, the required material information of each asset-level equipment is determined.

[0081] Another implementation method of the embodiment of the present application is to establish a dynamic allocation template to adjust the material configuration in real time according to factors such as the company's production needs, market changes, and material supply conditions. For example, when the price of a certain material rises or the supply is tight, the material configuration of the material category in the allocation template can be automatically adjusted to find a more economical and reliable alternative. At the same time, big data analysis technology can be used to monitor the price, quality, supply stability and other information of materials in the market in real time to provide data support for the dynamic adjustment of the allocation template.

[0082] The embodiment of the present application establishes a mapping relationship between asset-level equipment and material categories, and searches for required material information from the allocation template, thereby ensuring that each asset-level equipment can obtain materials that match its actual needs, avoiding material waste and mismatch, and improving the accuracy of material allocation.

[0083] In an exemplary embodiment, based on the above embodiment, see Figure 4 The embodiment of the present application involves performing allocation processing according to the required material information of each asset-level equipment and the list of materials to be allocated, and obtaining the material allocation information of each asset-level equipment, including the following steps:

[0084] S401, for each material to be apportioned in the list of materials to be apportioned, when it is determined according to the mapping relationship that there is a corresponding relationship between the material to be apportioned and the target asset-level equipment among multiple asset-level equipment, the material to be apportioned is apportioned to the target asset-level equipment; when it is determined according to the mapping relationship that there is no corresponding relationship between the material to be apportioned and the multiple asset-level equipment, the material to be apportioned is apportioned according to the historical apportionment records.

[0085] Among them, the list of materials to be allocated lists all the materials that need to be allocated, including the name, specification, quantity, value and other information of the materials.

[0086] Historical allocation records: record the past allocation of materials, including which asset-level equipment the materials were allocated to, the allocated quantity, time, and other information. This can be used as a reference to allocate materials that currently have no clear mapping relationship.

[0087] In an embodiment of the present application, first, each material to be apportioned in the list of materials to be apportioned is traversed. For each material, a judgment is made based on the pre-established mapping relationship between the asset-level equipment and the material. If it is determined that the material has a corresponding relationship with a target asset-level device among multiple asset-level devices, then the material is directly apportioned to the target asset-level device. If it is determined based on the mapping relationship that the material has no corresponding relationship with multiple asset-level devices, then the historical apportionment records are referred to to apportion the material to be apportioned. The distribution of similar materials in history can be analyzed, and the distribution object of the material can be determined based on factors such as probability distribution and the urgency of equipment demand.

[0088] Another implementation method of the embodiment of the present application: a machine learning algorithm can be used to assist in determining the allocation objects of materials without a mapping relationship. Collect historical allocation records and related equipment operation data, material attribute data, etc., and use unsupervised learning algorithms, such as clustering algorithms, to classify equipment and materials. When encountering materials without a mapping relationship, assign them to the equipment category that is most similar to them based on the properties of the materials. At the same time, the algorithm model can be continuously updated and optimized to improve the accuracy and rationality of material allocation as new data accumulates.

[0089] S402: Determine the material allocation information of each asset-level equipment according to the allocation results of each material to be allocated.

[0090] In the embodiment of the present application, after the allocation process of each material to be allocated is completed, the allocation results of each material are summarized. For each asset-level equipment, the information of all materials allocated to it is sorted out, including material type, quantity, value, etc., so as to determine the material allocation information of each asset-level equipment. This information can be recorded in the database for subsequent query, statistics and analysis.

[0091] Another implementation method of the present application embodiment is to establish a real-time updated material allocation information display platform. After the material allocation is completed, the material allocation information of each asset-level equipment is displayed on the platform in a visual manner, so that enterprise managers can understand the material allocation situation at any time. At the same time, an early warning mechanism can be set up. When the material allocation of a certain asset-level equipment is abnormal, such as too much or too little allocation, the allocated materials do not meet the equipment requirements, etc., an early warning is issued in time to adjust the allocation plan in time.

[0092] The embodiment of the present application distributes materials by combining mapping relationships with historical allocation records, which can fully consider the actual needs of the equipment and historical experience, improve the accuracy and rationality of material allocation, and avoid waste and mismatch of materials. For materials without clear mapping relationships, they can be flexibly processed according to historical allocation records, so that enterprises can quickly make reasonable allocation decisions when facing new materials or changing production conditions, and enhance the enterprise's resilience.

[0093] In an exemplary embodiment, based on the above embodiment, the material to be allocated in the embodiment of the present application includes a main material and an auxiliary material; when it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among multiple asset-level devices, the material to be allocated is allocated to the target asset-level device, including:

[0094] When it is determined according to the mapping relationship that a main material has a corresponding relationship with a target asset-level device among multiple asset-level devices, the main material is allocated to the target asset-level device; when it is determined according to the mapping relationship that an auxiliary material has a corresponding relationship with a target asset-level device among multiple asset-level devices, the auxiliary material is allocated to the target asset-level device.

[0095] Among them, main materials are usually materials that play a key role in the operation and function of asset-level equipment. For example, in production equipment, main materials can be core parts, key electronic components, important mechanical structural parts, etc. These main materials directly determine the main performance and functions of asset-level equipment. Without main materials, asset-level equipment may not operate normally or achieve its core functions.

[0096] Auxiliary materials: materials that play an auxiliary supporting role for asset-level equipment. For example, screws, gaskets, lubricants, wires, cable ties, etc. Although auxiliary materials are not the core elements for the realization of asset-level equipment functions, they play an indispensable role in the installation, maintenance, and stable operation of equipment. Auxiliary materials can ensure that the various components of asset-level equipment can be properly connected, reduce wear, and maintain good working conditions.

[0097] In an embodiment of the present application, when it is determined that a main material has a corresponding relationship with a target asset-level device among multiple asset-level devices according to a mapping relationship, the main material is allocated to the target asset-level device. Specifically, a mapping relationship database between asset-level devices and main materials is first established and maintained. This database can be continuously improved and updated through analysis of historical data of the enterprise, summary of expert experience, and observation of the actual production process. When it is determined that a main material has a corresponding relationship with a target asset-level device among multiple asset-level devices, the main material is reasonably allocated according to the needs of the device and the characteristics of the main material. For example, if the main material is a certain model of engine, and the target asset-level device is a vehicle that requires this model of engine to operate normally, then the engine is allocated to this vehicle.

[0098] Another implementation method of the present application embodiment: using data analysis and machine learning algorithms to automatically determine the correspondence between the main material and the target asset-level equipment. Collect a large amount of asset-level equipment operation data and main material usage data, and automatically discover the potential relationship between the main material and the asset-level equipment through data mining and machine learning algorithms, such as decision trees, random forests, etc. After determining the correspondence, use an automated allocation system to allocate the main material to the target asset-level equipment to improve the efficiency and accuracy of allocation.

[0099] In an embodiment of the present application, when it is determined based on a mapping relationship that an auxiliary material has a corresponding relationship with a target asset-level device among multiple asset-level devices, the auxiliary material is allocated to the target asset-level device. Specifically, a mapping relationship between asset-level devices and auxiliary materials is established. For auxiliary materials, although their role in asset-level equipment is relatively small, they are also an indispensable part of the normal operation of the equipment. When it is determined that an auxiliary material has a corresponding relationship with the target asset-level device, it is allocated based on the needs of the equipment and the quantity, specifications and other requirements of the auxiliary material. For example, if the auxiliary material is a screw, and the target asset-level device is a mechanical device that requires screws of specific specifications, then these screws are allocated to this mechanical device.

[0100] Another implementation method of the present application embodiment is to introduce an intelligent inventory management system to assist in the allocation of auxiliary materials. The system can monitor the inventory level of auxiliary materials and the demand for asset-level equipment in real time, and automatically trigger the allocation process when a corresponding relationship is found between auxiliary materials and target asset-level equipment. At the same time, dynamic inventory adjustment and allocation can be performed based on the frequency of equipment use and the consumption rate of auxiliary materials to ensure that the supply of auxiliary materials matches the demand of the equipment.

[0101] The embodiment of the present application divides the materials to be apportioned into main materials and auxiliary materials, and allocates them respectively according to the mapping relationship, which can more accurately meet the different needs of asset-level equipment and improve the pertinence and effectiveness of material allocation. By reasonably allocating main materials and auxiliary materials, the resources of the enterprise can be used more effectively, avoiding waste and unreasonable allocation of resources, and optimizing the resource allocation of the enterprise. The automated allocation system and intelligent inventory management system can reduce manual intervention, improve the efficiency and accuracy of material allocation, reduce management costs, and improve the management efficiency of the enterprise.

[0102] In an exemplary embodiment, based on the above embodiment, see Figure 5 The embodiment of the present application relates to a process of allocating the material to be allocated according to the historical allocation records when it is determined according to the mapping relationship that there is no corresponding relationship between the material to be allocated and multiple asset-level equipment, including the following steps:

[0103] S501, performing allocation probability statistics based on historical allocation records to determine the recommended allocation method for the materials to be allocated.

[0104] In the embodiment of the present application, historical allocation records are first collected and organized to ensure the completeness and accuracy of the records. Then, for the material to be allocated, the historical allocation records are analyzed to determine how the material is allocated to different asset-level devices. Through statistical analysis, the probability of each asset-level device obtaining the material is calculated. For example, if in the historical records, a certain material has a 30% probability of being allocated to device A, a 40% probability of being allocated to device B, and a 30% probability of being allocated to device C, then the recommended allocation method for the material can be determined based on these probabilities, which may be allocated to devices A, B, and C respectively according to this ratio.

[0105] Another implementation method of the present application embodiment: In addition to simple probability statistics, machine learning algorithms can also be introduced for more complex analysis. For example, a clustering algorithm is used to classify asset-level equipment according to their characteristics and needs, and then the allocation probability of the materials to be allocated is analyzed for different equipment categories. This can more accurately determine the recommended allocation method, taking into account the similarity and correlation of the equipment.

[0106] S502, allocate the materials to be allocated according to the recommended allocation method.

[0107] The recommended allocation method is a suggested plan for allocating materials based on the statistical results of the allocation probability, including which asset-level equipment to allocate to and the allocation ratio.

[0108] In the embodiment of the present application, the materials to be allocated are allocated to the corresponding asset-level equipment according to the determined recommended allocation method. An automated allocation system can be used to perform allocation operations according to the recommended proportions and objects. At the same time, the allocation situation is recorded so as to update the historical allocation record and provide a more accurate reference for subsequent material allocation.

[0109] Another implementation method of the present application embodiment: During the allocation process, a certain adjustment mechanism can be set. For example, if the current operating status or demand of a certain asset-level device changes, the recommended allocation method can be fine-tuned according to the actual situation. At the same time, a feedback mechanism can be introduced to allow users to evaluate and provide feedback on the allocation results in order to continuously optimize the allocation plan.

[0110] When the corresponding relationship between materials and asset-level equipment cannot be determined through the mapping relationship, the embodiment of the present application uses the historical allocation records for allocation, which increases the flexibility of material allocation and can adapt to various complex situations. By analyzing the historical allocation records, it is possible to fully draw on past successful experiences and make material allocation more reasonable and efficient.

[0111] In an exemplary embodiment, based on the above embodiment, see Figure 6 , the method of the embodiment of the present application further includes the following steps:

[0112] S601, optimizing the recommended allocation method to obtain an optimized allocation method.

[0113] The optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors.

[0114] Introduce relevant factors: Consider other factors that may affect material allocation in addition to historical allocation records and mapping relationships, such as the operating status of the equipment, changes in market demand, etc.

[0115] In the embodiment of the present application, the mapping relationship is re-analyzed: Professionals are organized to regularly review the mapping relationship between asset-level equipment and material categories. The equipment usage and required materials in the actual production process are compared to check whether there are deviations or omissions in the mapping relationship. For example, for newly-commissioned asset-level equipment, the corresponding material category is determined in a timely manner, and the mapping relationship is updated.

[0116] Adjust the weight of probability distribution: According to the actual needs and strategic goals of the enterprise, adjust the probability distribution weight of different factors in the historical allocation record. For example, if the enterprise is currently focusing on developing a certain business area, the weight of the relevant asset-level equipment in material allocation can be appropriately increased.

[0117] Introduce relevant factors: Collect relevant factors such as equipment operating status data and market demand change information. For example, if a certain asset-level equipment has frequently failed recently, you can consider increasing the allocation ratio of specific materials required for maintenance when allocating materials. Combine at least one of the above three methods to obtain an optimized allocation method.

[0118] Another implementation method of the present application embodiment: using data analysis and artificial intelligence technology for optimization processing. By establishing a data analysis model, the mapping relationship between asset-level equipment and material categories is automatically analyzed, and the weight of the probability distribution is adjusted according to historical data and real-time data. At the same time, the machine learning algorithm is used to automatically identify and introduce relevant factors to continuously optimize the allocation method.

[0119] S602, allocate the materials to be allocated according to the optimized allocation method.

[0120] In the embodiment of the present application, an automated material allocation system is used to accurately allocate the materials to be allocated to each asset-level device according to the optimized allocation method. During the allocation process, the allocation situation is monitored in real time to ensure the accuracy and efficiency of the allocation. At the same time, the allocation results are recorded to provide data support for subsequent optimization.

[0121] Another implementation method of the present application embodiment is to establish a feedback mechanism to allow equipment users and managers to evaluate and provide feedback on the allocation results. Based on the feedback information, the allocation method is adjusted and optimized in a timely manner, and the material allocation is performed again to continuously improve the satisfaction and effect of the allocation.

[0122] The embodiment of the present application can more accurately determine the material allocation plan through optimization processing, reduce allocation errors and waste, and improve resource utilization efficiency. The optimized allocation method can provide more accurate data support for the production and operation decisions of the enterprise, helping the enterprise to better plan resources and development strategies.

[0123] In an exemplary embodiment, based on the above embodiment, see Figure 7 , the method of the embodiment of the present application further includes the following steps:

[0124] S701, determine the asset value list based on the asset-level equipment to be allocated.

[0125] Among them, the asset value list is a list that records the value information and related attributes of the asset-level equipment to be allocated, which can be used to determine the materials required for the equipment and perform template retrieval and other operations.

[0126] In the embodiment of the present application, a comprehensive assessment is conducted on the asset-level equipment to be shared to determine its value information. The value information may include the purchase cost, current market value, expected service life, etc. of the equipment. At the same time, the attribute information such as the model, specification, functional characteristics, etc. of the equipment may also be recorded. This information is organized into an asset value list for subsequent operations.

[0127] Another implementation method of the present application embodiment is to use automated equipment detection and data analysis technology to quickly obtain relevant information about the asset-level equipment to be allocated and automatically generate an asset value list. For example, the operating parameters of the equipment are obtained through sensors, and the value and attribute information of the equipment are estimated in combination with market data and historical records.

[0128] S702, performing template search processing on the asset value list to obtain search results.

[0129] In the embodiment of the present application, the information in the asset value list is compared with the existing main and auxiliary material template library. The search process can match according to the value, model, function and other attributes of the equipment. If a main and auxiliary material template matching the asset value list is found, the search result is that the template exists; if no matching template is found, the search result is that the main and auxiliary material template does not exist.

[0130] Another implementation method of the present application embodiment is to use artificial intelligence algorithms to perform template retrieval. A machine learning model is trained to automatically identify suitable main and auxiliary material templates based on the characteristics of the asset value list. This can improve the accuracy and efficiency of retrieval.

[0131] S703, when the search result indicates that there is no main and auxiliary material template, a step of determining required material information of each asset-level equipment based on a mapping relationship between asset-level equipment and material categories is performed.

[0132] In the embodiment of the present application, if the search result shows that there is no suitable main and auxiliary material template, the required material information of each asset-level equipment is determined according to the mapping relationship between asset-level equipment and material categories. The specific steps can refer to the method for determining material information about the mapping relationship in the previous embodiment.

[0133] Another implementation method of the present application embodiment: In the absence of a main and auxiliary material template, the asset-level equipment can be classified by combining expert experience and data analysis, and then the required material information of each device can be inferred based on the classification results and historical material usage records. At the same time, a feedback mechanism can be established to continuously adjust and improve the method of determining material information during actual use.

[0134] The embodiment of the present application can quickly find suitable templates for main and auxiliary materials through asset value lists and template retrieval, thereby improving the accuracy of material allocation. In the absence of templates, the rationality of allocation can also be ensured by using mapping relationships to determine material information. Automated asset value list generation and template retrieval processing reduce the time and workload of manual operations and improve the efficiency of material allocation.

[0135] In an exemplary embodiment, based on the above embodiment, the method of the embodiment of the present application further includes:

[0136] When the search results indicate that there are main and auxiliary material templates, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material templates to obtain material allocation information.

[0137] Among them, the search results are the results obtained after the template search of the asset value list, which are used to determine whether there are main and auxiliary material templates.

[0138] In the embodiment of the present application, when the search result shows that there is a main and auxiliary material template, the detailed information of the template is obtained. The template usually contains the configuration information such as the type, quantity, and specification of the main and auxiliary materials corresponding to different asset-level equipment.

[0139] For asset-level equipment to be allocated, the allocation of main and auxiliary materials is processed according to its corresponding configuration in the template. For example, if an asset-level equipment requires a specific type of main material and a certain number of auxiliary materials in the template, the corresponding materials are allocated to the equipment according to these regulations.

[0140] During the allocation process, to ensure that materials are allocated accurately, an automated allocation system can be used to quickly allocate materials based on template information, record the allocation results, and generate material allocation information.

[0141] Another implementation method of the present application embodiment: optimize the main and auxiliary material templates using data analysis and machine learning technology. Collect a large amount of asset-level equipment operation data and material usage data, analyze the actual needs of different equipment for main and auxiliary materials in different situations, and adjust and optimize the configuration in the template.

[0142] When allocating materials, dynamically adjust the allocation plan in the template based on the real-time equipment operation status and business needs. For example, if a certain equipment is currently in a high-load operation state, additional auxiliary materials may be required to ensure stable operation. At this time, the auxiliary material allocation amount of the equipment can be increased according to the actual situation.

[0143] The main and auxiliary materials template of the embodiment of the present application provides clear guidance for material allocation, and can quickly and accurately allocate the main and auxiliary materials to the asset-level equipment to be apportioned, thereby improving the efficiency and accuracy of material allocation. By using templates, the standardization of material allocation can be achieved, the interference of human factors can be reduced, and the consistency and rationality of material allocation between different equipment can be ensured. Combined with data analysis and dynamic adjustment, material allocation can better adapt to changes in equipment operating status and business needs, and improve the company's resilience.

[0144] In an exemplary embodiment, based on the above embodiment, the method of the embodiment of the present application further includes:

[0145] Step 1: Determine the asset value list based on the asset-level equipment to be allocated; perform template search processing on the asset value list to obtain the search result; if the search result indicates that there is no main and auxiliary material template, execute step 2; if the search result indicates that there is a main and auxiliary material template, perform main and auxiliary material allocation processing on the asset-level equipment to be allocated based on the main and auxiliary material template to obtain material allocation information;

[0146] Step 2: Based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment; search for the required material information of each asset-level equipment from the allocation template according to the target material category;

[0147] Step 3: When it is determined according to the mapping relationship that there is a corresponding relationship between the main material in the materials to be allocated and the target asset-level equipment in the multiple asset-level equipments, the main material is allocated to the target asset-level equipment;

[0148] Step 4: When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary materials in the materials to be allocated and the target asset-level equipment in the multiple asset-level equipments, the auxiliary materials are allocated to the target asset-level equipment;

[0149] Step 5: When it is determined according to the mapping relationship that there is no corresponding relationship between the material to be apportioned and the plurality of asset-level equipment, perform apportionment probability statistics according to the historical apportionment records to determine a recommended allocation method for the material to be apportioned; optimize the recommended allocation method to obtain an optimized allocation method; and apportion the material to be apportioned according to the optimized allocation method.

[0150] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0151] Based on the same inventive concept, the embodiment of the present application also provides a resource sharing device for implementing the resource sharing method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more resource sharing device embodiments provided below can refer to the limitations on the resource sharing method above, and will not be repeated here.

[0152] In one embodiment, Figure 8 As shown, a resource allocation device 800 is provided, comprising:

[0153] The information determination module 801 is used to determine the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories;

[0154] The allocation module 802 is used to perform allocation processing according to the required material information of each asset-level equipment and the list of materials to be allocated, so as to obtain the material allocation information of each asset-level equipment.

[0155] In one embodiment, the information determination module includes:

[0156] A category determination unit, used to determine the target material category corresponding to each asset-level equipment based on the mapping relationship between the asset-level equipment and the material category;

[0157] The information search unit is used to search for required material information of each asset-level equipment from the allocation template according to the target material category, wherein the allocation template includes material configurations of different material categories.

[0158] In one embodiment, the above-mentioned apportionment module includes:

[0159] The first material allocation subunit is used for allocating each material to be allocated in the list of materials to be allocated to the target asset-level equipment when it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with the target asset-level equipment among the multiple asset-level equipments;

[0160] The second material allocation subunit is used for, when it is determined according to the mapping relationship that there is no corresponding relationship between the material to be allocated and the multiple asset-level equipment, to allocate the material to be allocated according to the historical allocation record;

[0161] Determine the material allocation information for each asset-level equipment based on the allocation results of each material to be allocated.

[0162] In one embodiment, the materials to be allocated include main materials and auxiliary materials; the first material allocation subunit is specifically used for:

[0163] When it is determined according to the mapping relationship that there is a corresponding relationship between the main material and the target asset-level equipment among the multiple asset-level equipment, the main material is allocated to the target asset-level equipment;

[0164] When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and the target asset-level equipment among the multiple asset-level equipments, the auxiliary material is allocated to the target asset-level equipment.

[0165] In one embodiment, the second material allocation subunit is specifically used for:

[0166] Perform apportionment probability statistics based on historical apportionment records to determine the recommended allocation method for the materials to be apportioned;

[0167] Allocate the materials to be allocated according to the recommended allocation method.

[0168] In one embodiment, the above device further comprises:

[0169] An optimization module, used to optimize the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors;

[0170] The allocation optimization module is used to allocate materials to be allocated according to the optimized allocation method.

[0171] In one embodiment, the above device further comprises:

[0172] The list determination module is used to determine the asset value list based on the asset-level equipment to be allocated;

[0173] A search module is used to perform template search processing on the asset value list to obtain search results;

[0174] The execution module is used to execute the steps of determining the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories when the search result indicates that there is no main and auxiliary material template.

[0175] In one embodiment, the above device further comprises:

[0176] The material allocation module is used to perform main and auxiliary material allocation processing on the asset-level equipment to be allocated according to the main and auxiliary material templates when the search results indicate that there are main and auxiliary material templates, and obtain material allocation information.

[0177] Each module in the resource sharing device can be implemented in whole or in part by software, hardware or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.

[0178] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a resource sharing method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0179] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0180] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0181] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0182] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0183] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0184] Based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment;

[0185] According to the target material category, the required material information of each asset-level equipment is found from the allocation template, where the allocation template includes material configurations of different material categories.

[0186] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0187] For each material to be allocated in the list of materials to be allocated, if it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among multiple asset-level devices, the material to be allocated is allocated to the target asset-level device;

[0188] When it is determined based on the mapping relationship that there is no corresponding relationship between the material to be apportioned and multiple asset-level equipment, the material to be apportioned is apportioned based on the historical apportionment records;

[0189] Determine the material allocation information for each asset-level equipment based on the allocation results of each material to be allocated.

[0190] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0191] When it is determined according to the mapping relationship that there is a corresponding relationship between the main material and the target asset-level equipment among the multiple asset-level equipment, the main material is allocated to the target asset-level equipment;

[0192] When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and the target asset-level equipment among the multiple asset-level equipments, the auxiliary material is allocated to the target asset-level equipment.

[0193] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0194] Perform apportionment probability statistics based on historical apportionment records to determine the recommended allocation method for the materials to be apportioned;

[0195] Allocate the materials to be allocated according to the recommended allocation method.

[0196] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0197] Optimizing the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors;

[0198] The materials to be allocated are allocated according to the optimized allocation method.

[0199] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0200] Determine the asset value list based on the asset-level equipment to be allocated;

[0201] Perform template retrieval processing on the asset value list to obtain retrieval results;

[0202] When the search result indicates that there is no main and auxiliary material template, a step of determining required material information of each asset-level equipment based on a mapping relationship between asset-level equipment and material categories is performed.

[0203] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0204] When the search results indicate that there are main and auxiliary material templates, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material templates to obtain material allocation information.

[0205] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0206] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0207] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0208] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0209] Based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment;

[0210] According to the target material category, the required material information of each asset-level equipment is found from the allocation template, where the allocation template includes material configurations of different material categories.

[0211] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0212] For each material to be allocated in the list of materials to be allocated, if it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among multiple asset-level devices, the material to be allocated is allocated to the target asset-level device;

[0213] When it is determined based on the mapping relationship that there is no corresponding relationship between the material to be apportioned and multiple asset-level equipment, the material to be apportioned is apportioned based on the historical apportionment records;

[0214] Determine the material allocation information for each asset-level equipment based on the allocation results of each material to be allocated.

[0215] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0216] When it is determined according to the mapping relationship that there is a corresponding relationship between the main material and the target asset-level equipment among the multiple asset-level equipment, the main material is allocated to the target asset-level equipment;

[0217] When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and the target asset-level equipment among the multiple asset-level equipments, the auxiliary material is allocated to the target asset-level equipment.

[0218] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0219] Perform apportionment probability statistics based on historical apportionment records to determine the recommended allocation method for the materials to be apportioned;

[0220] Allocate the materials to be allocated according to the recommended allocation method.

[0221] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0222] Optimizing the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors;

[0223] The materials to be allocated are allocated according to the optimized allocation method.

[0224] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0225] Determine the asset value list based on the asset-level equipment to be allocated;

[0226] Perform template retrieval processing on the asset value list to obtain retrieval results;

[0227] When the search result indicates that there is no main and auxiliary material template, a step of determining required material information of each asset-level equipment based on a mapping relationship between asset-level equipment and material categories is performed.

[0228] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0229] When the search results indicate that there are main and auxiliary material templates, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material templates to obtain material allocation information.

[0230] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0231] Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment;

[0232] The material allocation information of each asset-level equipment is obtained by performing allocation processing based on the required material information of each asset-level equipment and the list of materials to be allocated.

[0233] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0234] Based on the mapping relationship between asset-level equipment and material categories, determine the target material category corresponding to each asset-level equipment;

[0235] According to the target material category, the required material information of each asset-level equipment is found from the allocation template, where the allocation template includes material configurations of different material categories.

[0236] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0237] For each material to be allocated in the list of materials to be allocated, if it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among multiple asset-level devices, the material to be allocated is allocated to the target asset-level device;

[0238] When it is determined based on the mapping relationship that there is no corresponding relationship between the material to be apportioned and multiple asset-level equipment, the material to be apportioned is apportioned based on the historical apportionment records;

[0239] Determine the material allocation information for each asset-level equipment based on the allocation results of each material to be allocated.

[0240] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0241] When it is determined according to the mapping relationship that there is a corresponding relationship between the main material and the target asset-level equipment among the multiple asset-level equipment, the main material is allocated to the target asset-level equipment;

[0242] When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and the target asset-level equipment among the multiple asset-level equipments, the auxiliary material is allocated to the target asset-level equipment.

[0243] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0244] Perform apportionment probability statistics based on historical apportionment records to determine the recommended allocation method for the materials to be apportioned;

[0245] Allocate the materials to be allocated according to the recommended allocation method.

[0246] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0247] Optimizing the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors;

[0248] The materials to be allocated are allocated according to the optimized allocation method.

[0249] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0250] Determine the asset value list based on the asset-level equipment to be allocated;

[0251] Perform template retrieval processing on the asset value list to obtain retrieval results;

[0252] When the search result indicates that there is no main and auxiliary material template, a step of determining required material information of each asset-level equipment based on a mapping relationship between asset-level equipment and material categories is performed.

[0253] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0254] When the search results indicate that there are main and auxiliary material templates, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material templates to obtain material allocation information.

[0255] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0256] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0257] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0258] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A resource allocation method, characterized in that: The method comprises: Based on the mapping relationship between asset-level equipment and material categories, determine the required material information for each asset-level equipment; Apportionment processing is performed according to the required material information of each asset-level equipment and the list of materials to be apportioned, so as to obtain the material allocation information of each asset-level equipment.

2. The method according to claim 1, characterized in that The required material information of each asset-level equipment is determined based on the mapping relationship between asset-level equipment and material categories, including: Based on the mapping relationship between the asset-level equipment and the material category, determine the target material category corresponding to each of the asset-level equipment; The required material information of each of the asset-level equipment is searched from the allocation template according to the target material category, wherein the allocation template includes material configurations of different material categories.

3. The method according to claim 1, characterized in that The allocation process is performed according to the required material information of each asset-level equipment and the list of materials to be allocated to obtain the material allocation information of each asset-level equipment, including: For each material to be allocated in the list of materials to be allocated, if it is determined according to the mapping relationship that the material to be allocated has a corresponding relationship with a target asset-level device among the plurality of asset-level devices, the material to be allocated is allocated to the target asset-level device; When it is determined according to the mapping relationship that there is no corresponding relationship between the material to be apportioned and the plurality of asset-level equipments, the material to be apportioned is apportioned according to the historical apportionment records; According to the allocation results of each of the materials to be allocated, the material allocation information of each of the asset-level equipment is determined.

4. The method according to claim 3, characterized in that The to-be-allocated materials include main materials and auxiliary materials; and when it is determined according to the mapping relationship that the to-be-allocated materials correspond to target asset-level equipment among the plurality of asset-level equipments, allocating the to-be-allocated materials to the target asset-level equipment includes: In the case where it is determined according to the mapping relationship that there is a corresponding relationship between the main material and a target asset-level device among the plurality of asset-level devices, the main material is allocated to the target asset-level device; When it is determined according to the mapping relationship that there is a corresponding relationship between the auxiliary material and a target asset-level device among the plurality of asset-level devices, the auxiliary material is allocated to the target asset-level device.

5. The method according to claim 4, characterized in that When it is determined according to the mapping relationship that there is no corresponding relationship between the material to be apportioned and the plurality of asset-level equipments, the material to be apportioned is apportioned according to the historical apportionment records, including: Performing apportionment probability statistics based on the historical apportionment records to determine a recommended allocation method for the materials to be apportioned; The materials to be allocated are allocated according to the recommended allocation method.

6. The method according to claim 5, characterized in that The method further comprises: Optimizing the recommended allocation method to obtain an optimized allocation method; the optimization process includes at least one of re-analyzing the mapping relationship, adjusting the weight of the probability distribution, and introducing relevant factors; The materials to be allocated are allocated according to the optimized allocation method.

7. The method according to claim 1, characterized in that The method further comprises: Determine the asset value list based on the asset-level equipment to be apportioned; Performing template retrieval processing on the asset value list to obtain retrieval results; When the search result indicates that there is no main and auxiliary material template, the step of determining the required material information of each asset-level equipment based on the mapping relationship between the asset-level equipment and the material category is performed.

8. The method according to claim 7, characterized in that The method further comprises: In the case where the search result indicates that there is a main and auxiliary material template, main and auxiliary material allocation processing is performed on the asset-level equipment to be allocated according to the main and auxiliary material template to obtain the material allocation information.

9. A resource allocation device, characterized in that: The device comprises: The information determination module is used to determine the required material information of each asset-level equipment based on the mapping relationship between asset-level equipment and material categories; The allocation module is used to perform allocation processing according to the required material information of each asset-level equipment and the list of materials to be allocated, so as to obtain the material allocation information of each asset-level equipment.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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