An Internet-based enterprise consumables asset data management system

Abstract

The present invention relates to the technical field of enterprise asset data management, and specifically to an Internet-based enterprise consumables asset data management system, comprising: an asset information module, an asset verification module, an asset change module, an asset matching module, and an asset management module; by acquiring asset information of asset equipment and enterprise consumables, an asset interaction relationship corresponding to the asset information and the enterprise consumables is set; an asset equipment inventory is conducted based on the asset interaction relationship, the actual status of each asset equipment is determined, the asset location and update frequency of the asset equipment are derived, and based on the actual status of each asset equipment, the usage status of each asset equipment under asset location changes is verified to generate an asset change vector; the asset change vector is interactively matched with the update frequency to obtain an asset matching result of a multi-attention combination; the asset equipment is evaluated based on the asset matching result to determine the usage type distribution of the enterprise consumables, thereby achieving the accuracy of asset management and the operational efficiency of the enterprise consumables.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise asset data management, and in particular to an enterprise consumables asset data management system based on the Internet. Background Art

[0002] Enterprise asset management refers to the effective planning, allocation, use, maintenance, and disposal of various tangible and intangible assets within an enterprise to improve asset efficiency and value, reduce asset risks and costs, and achieve the company's strategic goals. Enterprise asset management involves multiple aspects, such as asset identification, asset location, asset movement, asset recording, and asset inspection.

[0003] As enterprises expand and their business complexity increases, asset management becomes increasingly complex. For businesses that rely heavily on consumables, effectively managing assets and their associated consumables becomes a critical issue. Traditional asset management methods often lack a deep understanding of the interplay between assets and consumables, leading to wasted resources, increased maintenance costs, and low efficiency.

[0004] For example, Chinese patent publication number CN115310952A discloses an enterprise asset management method and system based on the Internet of Things, which relates to the field of data processing technology. By constructing an enterprise asset database including enterprise asset information and asset number information, asset status monitoring information is obtained, the enterprise asset database is updated based on the asset status monitoring information, and asset health status assessment is performed on each asset coding information according to the enterprise asset database to obtain each asset health assessment information. It is judged whether each asset health assessment information reaches a preset threshold. If the threshold is reached, an early warning message is generated. If the threshold is not reached, an operation and maintenance management work order is generated.

[0005] For example, Chinese patent publication number CN117094574A discloses a method, system, device and computer-readable storage medium for efficient enterprise asset management. The method includes: binding a Bluetooth tag to a movable asset and entering asset information; generating an asset mobile pass based on the asset information and issuing it to the user; scanning the pass QR code to verify the pass, and using indoor positioning technology to locate the Bluetooth tag to determine the current location of the asset; when the asset location changes, generating a location change record and storing it as a data block. The data block includes a check code part and a location change content part. The check code is calculated using a hash algorithm to ensure the integrity and non-tamperability of the data.

[0006] The existing technology describes a method of conducting a health assessment of enterprise assets through asset classification, and a method of determining asset access rights by checking asset location; however, it is difficult to track the status of enterprise consumables under multiple asset equipment through only these two aspects, making it impossible to allocate enterprise consumables in a timely manner according to the needs of asset equipment, resulting in increased equipment management costs and reduced operational efficiency of enterprise asset data management. Summary of the Invention

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is: an Internet-based enterprise consumables asset data management system, including: an asset information module, which is used to obtain asset information of asset equipment and enterprise consumables based on basic information during asset management, and set the asset interaction relationship between asset information and enterprise consumables.

[0008] The asset verification module is used to conduct an inventory of assets and equipment based on asset interaction relationships, determine the actual status of each asset and equipment, and derive the asset location and update frequency of the asset equipment. The asset location includes static location, dynamic location and business process location.

[0009] The asset change module is used to verify the target change trend corresponding to the usage status of each asset equipment under the asset location change based on the actual status of each asset equipment, and generate an asset change vector.

[0010] The asset matching module is used to perform interactive matching using asset change vectors, determine the comparison features under asset interaction, combine the comparison features with the update frequency of asset equipment, and obtain asset matching results of multi-attention combinations.

[0011] The asset management module is used to evaluate asset equipment based on asset matching results and determine the usage type distribution of enterprise consumables.

[0012] The beneficial effects of the present invention are as follows: First, the present invention collects and processes basic information of asset equipment, including static location, dynamic location and business process location, and establishes an interactive relationship between asset information and enterprise consumables; it associates asset equipment with the use of enterprise consumables in events such as maintenance, idleness and repair to determine the use of asset equipment under normal management, and can track the status of asset equipment and verify the consumption of enterprise consumables in real time, thereby improving the control of enterprise consumable costs. At the same time, by controlling the different asset locations on asset equipment, the enterprise asset data of multiple data officers can be integrated to improve the data integration effect in complex situations, so as to reduce the problem of difficulty in data integration and difficulty in quantifying enterprise consumables due to the scattered and complicated data sources during enterprise data management.

[0013] 2. The present invention can ensure the accuracy and real-time nature of asset status by conducting asset inventory based on asset interaction relationships, extract relevant data on asset equipment during its normal life cycle, and judge the maintenance time, maintenance location, and maintenance cost of this data to identify whether there are abnormalities in asset equipment maintenance and the problem of large consumption of consumables in the enterprise, thereby preventing the problem of excessive consumption of consumables in the enterprise.

[0014] 3. The present invention generates asset change vectors by monitoring the status changes of assets and equipment. After matching the asset change vectors multiple times, it uses a multi-attention mechanism to calculate the matching probability between asset change vectors to identify similar asset patterns. Finally, based on the asset matching results, the usage type distribution of enterprise consumables is determined. Under asset management, the status changes corresponding to the assets and equipment are associated with the enterprise consumables to determine the accuracy of the corresponding data during asset management. At the same time, based on the matching processing of the asset change vectors, it can analyze the current changes in the demand and cost of the enterprise consumables, helping the enterprise to quickly understand the consumption and expected use of consumables. Finally, after displaying the usage trends of these situations, the relevant types of enterprise consumables are clustered and displayed, which can assist the enterprise in managing the enterprise consumables and ultimately improve the enterprise's operating efficiency of consumables. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention will be further described below with reference to the accompanying drawings and examples.

[0016] Figure 1 The system diagram of an enterprise consumables asset data management system based on the Internet.

[0017] Figure 2 The present invention is a flowchart of the asset information module of the Internet-based enterprise consumables asset data management system.

[0018] Figure 3 The invention is a flowchart of an asset verification module of an Internet-based enterprise consumables asset data management system.

[0019] Figure 4 The present invention is a flowchart of an asset change module of an Internet-based enterprise consumables asset data management system. DETAILED DESCRIPTION

[0020] The following embodiments of the present invention are described in detail. The embodiments described below are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention. Where specific techniques or conditions are not specified in the embodiments, the techniques or conditions described in the literature in the art or in the product specifications shall be followed.

[0021] See Figure 1An Internet-based enterprise consumables asset data management system includes: an asset information module, an asset verification module, an asset change module, an asset matching module and an asset management module; wherein the output end of the asset information module is connected to the asset verification module, the output end of the asset verification module is connected to the asset change module, the output end of the asset change module is connected to the asset matching module, and the output end of the asset matching module is connected to the asset management module.

[0022] The asset information module is used to obtain asset information of asset equipment and enterprise consumables based on basic information during asset management, and to set the asset interaction relationship between asset information and enterprise consumables.

[0023] The asset verification module is used to conduct an inventory of assets and equipment based on asset interaction relationships, determine the actual status of each asset and equipment, and derive the asset location and update frequency of the asset equipment. The asset location includes static location, dynamic location and business process location.

[0024] The asset change module is used to verify the target change trend corresponding to the usage status of each asset equipment under the asset location change based on the actual status of each asset equipment, and generate an asset change vector.

[0025] The asset matching module is used to perform interactive matching using asset change vectors, determine the comparison features under asset interaction, combine the comparison features with the update frequency of asset equipment, and obtain asset matching results of multi-attention combinations.

[0026] The asset management module is used to evaluate asset equipment based on asset matching results and determine the usage type distribution of enterprise consumables.

[0027] The basic information in asset management represents the status of the underlying assets, such as the total value of assets, residual value of assets, asset expenses, and maintenance costs. The asset information obtained generally needs to explain the location, quantity, model, type, and corresponding working conditions of the assets. The consumables used in asset management are then associated with their usage. For example, in terms of the dimensions of the consumable equipment being in use, idle, lost, or scrapped, the location, condition, preparation for use, and maintenance of the assets are associated as the asset interaction relationship during asset management at this time. The usage and residual value of the current equipment under the corresponding equipment quantity are verified and marked out. Finally, the asset information is compared to conduct comprehensive management of equipment of multiple types.

[0028] It should be noted that enterprise consumables refer to items that are used in conjunction with assets (such as equipment and tools) and are gradually consumed or require regular replacement during operations. These items are not usually accounted for as separate assets, but their usage, inventory, and costs are tied to the associated assets to comprehensively track asset operation and maintenance costs and resource consumption. At this point, the basic information of asset management is linked to the usage of the corresponding enterprise consumables, and the location and usage of each device in multiple dimensions corresponding to the enterprise consumables are determined. Ultimately, asset interaction between devices is completed, facilitating timely verification of the normal operation of machinery and equipment and the linkage of asset status, thereby achieving operation and maintenance cost optimization and cost refinement.

[0029] Therefore, when setting the asset interaction relationship corresponding to the asset information, such as Figure 2 As shown, the implementation method of the asset information module also includes: obtaining the scenario type of the asset information, dividing the asset information into scenarios, determining the data distribution of the asset information in each scenario, and generating the classification category of the asset information.

[0030] When segmenting the scenarios, the scenario types described can be procurement and warehousing, allocation and issuance, operation and maintenance, inventory and auditing, as well as depreciation and scrapping. These scenarios represent the usage of relevant equipment and consumables in the enterprise. Then, the record data of the corresponding asset equipment and consumables in each scenario is described to obtain the corresponding data distribution. Finally, the asset information categories are divided into three categories: static attributes, dynamic status, and business associations. These three categories represent the classification categories of current asset information; static attributes are inherent information that does not change with time or scenarios, and are centrally stored in the core database for shared reading in multiple scenarios; dynamic status information that changes in real time with business activities is distributedly stored in time series databases, IoT edge nodes, and other locations; business associations are contextual information bound to external systems or processes, and are mostly cross-system associated storage, requiring dynamic API calls to obtain related data. These data will indicate the differences in asset information storage and usage to describe the main focus of asset management.

[0031] Based on the classification of the asset information, a semantic segmentation vector of the asset information is obtained, and multiple mapping relationships of the asset information are obtained in sequence according to the semantic segmentation vector.

[0032] At this time, the semantic segmentation vector represents the classification of asset information. The data under the three categories are spliced ​​using vectors. The data corresponding to these vectors are then used as multiple mapping relationships of the asset information at this time to describe the asset interaction processes and business generated by the asset data under the corresponding categories.

[0033] The asset information is associated and combined with the data corresponding to the enterprise consumables according to the mapping relationship, and the result of the association and combination is used as the asset interaction relationship between the asset information and the enterprise consumables.

[0034] When performing an association combination, the result of the association combination is used as the implementation method for setting the asset interaction relationship corresponding to the asset information and the enterprise consumables, including: verifying the time ratio numerator of each asset equipment under the asset information mapping relationship, and the value ratio numerator of the enterprise consumables in the classification category of each asset equipment, where the time ratio numerator is the ratio of the working time of an asset equipment to the total working time of the total asset equipment, and the value ratio numerator is the ratio of the value of an asset equipment to the value of the total asset equipment; the time ratio factor of each asset equipment represents the length of the time period corresponding to each state of the asset equipment under asset interaction, and the length of this time period will indicate how long it takes for the consumables of the asset equipment to be replaced, or the length of time the consumables corresponding to the asset equipment can be used. This indicator can help identify which equipment is used frequently and may require more maintenance or updates; and which equipment has low utilization and may have idle resources.

[0035] The value ratio factor describes the proportion of the cost of a certain category of consumables to the total consumables cost when the consumables corresponding to the asset equipment interact with the asset. Analyzing the consumables ratio at this time can help understand the relative value of the currently consumed consumables and assist in subsequent adjustments to the consumables to reduce cost losses.

[0036] For example, the current asset information includes three main devices, A, B, and C. The three main devices have been used for a total of 30 days. Among them, device A has been used for 15 days, with a time proportion numerator of 50%, device B has been used for 10 days, with a time proportion numerator of 33%, and device C has been used for 5 days, with a time proportion numerator of 16.7%. By identifying the time proportion numerator at this time, the different operating frequencies of the three devices can be discovered, and the corresponding idle, working, and other states of these devices can be identified.

[0037] Then, the three main equipment A, B, and C correspond to three consumables: raw material X, component Y, and auxiliary material Z. The total value of these three consumables is 10,000 yuan. Among them, the cost of raw material X is 4,000 yuan, accounting for 40% of the value; the cost of component Y is 3,500 yuan, accounting for 35% of the value; the cost of auxiliary material Z is 2,500 yuan, accounting for 25% of the value. At this point, we can find the corresponding situation of different consumables in the current situation. Then, by correlating this data, we can find the relationship between asset information and consumable consumption, which facilitates the subsequent overall asset management and planning.

[0038] Based on the time proportion numerator of each asset device, the timeline of data changes in asset information under the mapping relationship is obtained, and each sub-event of asset interaction under the timeline is extracted.

[0039] Identify whether the time points of each sub-event overlap, and use the value ratio numerator to determine whether the asset interaction is logical. When the asset interaction is logical and there are overlapping points, divide each sub-event into the interaction layer, contract layer and standard layer, and set the asset interaction relationship between the asset information and the enterprise consumables according to the connection relationship under the corresponding layer.

[0040] At this time, the purpose of dividing each sub-event into the interaction layer, contract layer and standard layer is to illustrate the ongoing steps of the asset interaction and whether the asset interaction is proceeding normally. The interaction layer indicates the event of the current asset equipment and enterprise consumables undergoing status changes and location updates. At this time, the asset information and enterprise consumables will change from the idle label to the in-use state to indicate that the assets corresponding to the enterprise consumables are in an available state.

[0041] The contract layer indicates whether the asset interaction under the sub-event complies with the preset strategy, that is, the interaction status of the asset information under its approval process and permission control. For example, if the asset maintenance cost reported under the current asset interaction is too high, exceeding the threshold by 50%, the asset interaction event will be changed, forcibly triggering the scrapping of the relevant equipment or other processing procedures. The sub-events described in the contract layer are mostly sub-events that use sub-events to determine changes in the approval process and corresponding permission control after the asset interaction is reported.

[0042] The standard layer describes the actual operations performed on the asset interaction, explaining what operations were ultimately performed on the reported asset interaction and the information corresponding to these operations.

[0043] The asset interaction relationship between the current asset information and the corresponding enterprise consumables is formed according to the preceding and following relationships between these three levels during the asset interaction submission process. This process integrates asset interactions across multiple systems and data sources, allowing the timely traceability and identification of enterprise consumable usage during asset interactions, preventing issues such as excessive or insufficient consumption of enterprise consumables.

[0044] When identifying whether the time points of each sub-event overlap, the main focus is on obtaining certain synchronous occurrence times. If the starting and ending points of these times overlap, it means that these times may represent rapid changes in equipment or consumables. These contents need to be analyzed centrally to prevent waste of consumables and repeated purchase approvals. For the use value ratio numerator, judging whether the asset interaction is logical is to identify the cost of consumables when the asset interaction is currently taking place to prevent inconsistent consumable costs.

[0045] In one embodiment of the present invention, the asset verification module is mainly used to describe the corresponding conditions of each asset device in the asset interaction, to indicate the usage of consumables corresponding to the current asset device after multiple data updates.

[0046] The asset location of the asset equipment here can be expressed as shown in Table 1.

[0047] Table 1. Asset location diagram

[0048]

[0049] Table 1 illustrates the forms of use of the currently exported asset locations. One is the static location that has been entered. The static location represents the form of equipment storage. In this case, the equipment location is almost fixed and will not change with time or scenario. The associated consumables and other assets will be regarded as additional storage assets; the other is the dynamic location that is changing. This means that the equipment is being transported or in a dynamic working scenario. The consumables associated with this asset location will be recorded in a timely manner for consumption and distribution to determine the usage of the relevant consumables; there is also a business process location registered using the business process, which represents the current status of the equipment. In this case, the consumables associated with the equipment also need to be associated with the description of the business process to determine how the consumables are replenished and consumed. If it is in a maintenance state, the corresponding consumables that need to be used are recorded to determine the required quantity of consumables under the business process, thereby completing the scheduling related to asset location and consumables.

[0050] The update frequency indicates the time interval between asset equipment and corresponding consumables being refreshed in the system under the asset interaction relationship, which is used to determine the speed or frequency of actual use or scheduling of consumables, and to map these contents with the actual status of the asset equipment to determine whether the current equipment has problems such as excessive consumption of consumables or insufficient consumables.

[0051] like Figure 3 As shown, the implementation method of the asset verification module includes: obtaining the life cycle corresponding to the asset information, performing relational encoding on each interaction data in the asset interaction relationship according to the life cycle corresponding to the asset information, setting the relationship vector corresponding to the asset interaction relationship, and calculating the cosine similarity between each relationship vector to obtain the sequence data of the relationship vector under the current life cycle.

[0052] Perform status dimension inventory on the sequence data in the current life cycle to determine whether the asset interaction in the current life cycle is normal. If normal, extract the asset location and update frequency of the current asset equipment.

[0053] The life cycle corresponding to the asset information starts from the time each asset equipment is purchased or put into use, and the total length of time after maintenance and scrapping; the content of the asset information during maintenance and process changes during this time is described, and each asset equipment and enterprise consumables is used as a node in the inventory of asset interaction relationships. The type, frequency, intensity, etc. of the interaction in the asset interaction relationship are used as edges in the inventory of asset interaction relationships. The interaction data corresponding to the asset interaction relationship is converted into a relationship vector in digital form, and then the cosine similarity of the relationship vector under different asset interactions is calculated to evaluate the similarity between different asset equipment and enterprise consumables when interacting. Finally, the data with similarity are combined into a sequence data to describe asset equipment and enterprise consumables with similar interaction methods.

[0054] Afterward, a status-based inventory is conducted to assess whether there are any anomalies in the normal interaction and resource utilization between the asset and the company's consumables. This means determining whether the interaction patterns and frequency meet expectations. Further information related to the asset is then extracted, such as its location and data update frequency. This is crucial to ensuring the accuracy and timeliness of the asset management system.

[0055] The form of relationship coding is to use numbers to represent the interaction between assets and enterprise consumables, and then add the type, frequency, and intensity of the interaction in the asset interaction relationship. These data are combined into a relationship vector in the form of numbers. The type of interaction will be set with a digital code according to the content described under the scenario type. The frequency then represents the frequency of changes in the asset equipment under normal business processes and maintenance conditions, and the intensity represents the quantity or cost of the corresponding asset equipment, and finally the setting of the relationship vector is completed.

[0056] The status dimension generally includes time, location, frequency of use, health status, etc. These contents represent the dimensions of the actual status of the current asset equipment. Inventorying the status of the asset equipment under these dimensions can reveal the time and location of the use of consumables when the asset equipment is associated with the corresponding consumables, as well as the content of what consumables are needed to maintain its health status, so as to more comprehensively represent the actual quantity and value of consumables required for consumable management of enterprise assets, thereby laying the foundation for subsequent changes in usage trends, and finally completing the trend represented by the total consumption and consumption distribution of consumables when asset information changes.

[0057] The implementation method of status dimension inventory of sequence data in the current life cycle includes: obtaining the maintenance time, maintenance location and maintenance cost of asset equipment based on the sequence data in the current life cycle; maintenance time indicates the time when the asset equipment replaces consumables, maintenance location indicates the location where the current asset equipment is replaced or repaired when replacing consumables, and maintenance cost indicates how much consumables are used when replacing consumables, to record the normal situation of equipment using consumables.

[0058] Determine whether the maintenance time, maintenance location, and maintenance cost of the asset equipment meet the preset rules. If they meet the preset rules, it is determined that the asset interaction in the current life cycle is normal.

[0059] In the current situation, the preset rules indicate that the time interval corresponding to the maintenance time of the asset equipment and the average time interval of the normal maintenance interval of the equipment in the historical data are less than 10% different. This indicates whether the time for the equipment's own maintenance and replacement of consumables is the same as normal, so as to find out whether there is excessive consumption. Regardless of whether these data meet the preset rules, they will be recorded as data corresponding to the actual status of each asset equipment.

[0060] The preset rule for a maintenance location indicates whether the frequency of consumable replacement at the corresponding location of an asset device after the consumables are replaced exceeds the average frequency of consumable replacement at the same location of the same device in historical data. If it is less than the average, the preset rule for the maintenance location is considered to be met.

[0061] The preset rule for maintenance cost indicates the cost required to replace or repair consumables of asset equipment. This cost must not exceed 80% of the maximum repair cost of the same equipment under the same circumstances in historical data. Otherwise, the equipment maintenance cost is considered too high and constitutes abnormal asset maintenance.

[0062] In one embodiment of the present invention, when describing changes in asset locations, the target change trends in the usage status of each asset device will be processed in sequence according to the changes in static location, dynamic location, and business process location, and an asset change vector will be formed based on these processed data.

[0063] Under static position changes, the focus is on explaining the changes in usage and maintenance frequency when assets are dispatched from one location to another, describing the potential increase and consumption of consumables. For example, a manufacturing company moves a CNC machine tool from a spare warehouse to a main production line. At this point, usage increases from 10 hours per month to 8 hours per day, and maintenance logs indicate the need for more frequent lubrication and sensor calibration. At the same time, due to the high ambient temperature of the production line, the equipment's heat dissipation needs increase, leading to an increased cooling system failure rate. By presenting this maintenance consumption trend chart, the approach required under static positions can be understood.

[0064] Under dynamic position changes, the increase in consumables costs during transportation or movement along a specific route is described to describe the resulting trend. For example, a logistics company's transport truck changes its route from City A to City B. The new route includes mountain roads, which increases engine temperature and fuel consumption by 15%. Onboard sensor data indicates accelerated wear of the brake system. The maintenance team also performs emergency repairs during transportation, increasing downtime. These maintenance costs are described, and a trend chart is generated based on the labels corresponding to the dynamic position changes to illustrate the trend of consumables under this method.

[0065] When a business process position changes, the amount of consumables required for the asset's status change is indicated, and this consumable amount is used as the trend change at that time. For example, an asset's status can be in production, under maintenance, or in standby. The work order content corresponding to the asset at this time, as well as whether the consumables required for maintenance under that work order will change depending on the work order content and the asset's status, are used as the main trend to identify when the business process position changes. The consumables consumption and predicted replenishment quantity generated by normal operation at this time are used as the main trend to identify when the business process position changes.

[0066] As described above, when changes occur in the three asset locations of static, dynamic, and business process locations, it's necessary to capture the trends in consumable consumption and subsequent replenishment scheduling. Therefore, by mapping the trend quantities of consumable demand, consumable usage, and consumable cost to the corresponding asset location categories, we use these as the target trend for each asset's usage status. The trends for each category are then combined to produce the output asset change vector.

[0067] This section will further explain the existing consumption trends of enterprise consumables and comprehensively identify the associated changes between the identified consumption trends and equipment, such as changes in asset value, asset expenses, maintenance costs, etc., to determine the actual consumption of assets and equipment under different circumstances.

[0068] like Figure 4 As shown, the implementation method of the asset change module includes: extracting the consumables data corresponding to each asset equipment under the asset position change according to the actual status of each asset equipment, and the consumables data includes consumables demand, consumables usage and consumables cost.

[0069] The consumables data is associated with the asset equipment to generate a target change trend, and the trend slope of the target change trend is used as the output asset change vector.

[0070] The way to associate consumables data with asset equipment is to extract trend features of the usage status of each asset equipment at static locations, dynamic locations, and business process locations.

[0071] The usage duration and maintenance intervals of assets at static locations are used as trend features for these locations. These trends are then correlated with consumable usage to create a consumable consumption trend chart. This chart depicts changes in usage duration and maintenance intervals, with the corresponding consumable usage as the y-axis and the time corresponding to the changed maintenance interval as the x-axis. The chart then describes the usage frequency and maintenance interval as the context.

[0072] The maintenance count for assets at dynamic locations is used as a trend feature for the dynamic location. This trend feature is then correlated with the cost of consumables to generate a consumables cost trend chart. The consumables cost trend chart shows the maintenance count corresponding to the maintenance interval as the horizontal axis, and the consumables cost for maintenance as the vertical axis.

[0073] Calculate the state transition frequency at the business process location as the trend feature of the business process location, associate the trend feature of the business process location with the consumables demand, and generate a consumables demand trend chart. The state transition frequency counts the number of times the equipment switches between states such as "production → maintenance → standby" to describe the actual working conditions of the equipment, whether there are multiple repairs or other idle situations, and uses the consumables demand in this situation as the vertical coordinate, and the time point of each state transition as the horizontal coordinate. The horizontal coordinate can be further expressed in unit time to determine the increase in consumables demand as the state transition frequency increases. These related data can be directly queried from the asset information recorded in the actual status of each asset equipment and the asset interaction relationship of the enterprise consumables, and the characteristics required for the target change trend are formed according to these data.

[0074] The moving average of the slope values ​​of the consumables consumption trend chart, consumables cost trend chart, and consumables demand trend chart is used as the trend slope of the target change trend. This trend slope can then be used to directly calculate the rate of change of the target change trend. The asset change vector will contain the slope values ​​represented by the curves in these three trend charts to indicate the current usage of the corresponding consumables of the asset equipment under the three dimensions of demand, usage, and cost.

[0075] In one embodiment of the present invention, the comparison features in the asset matching module indicate the presence of data of the same dimension or representing the same type of object between asset change vectors. The data corresponding to the asset change vectors are filtered and used as comparison features for comparison. These data represent data that can be interactively matched in the asset change vectors, and can assist in the evaluation and finding candidate matching pairs that can be used for rapid asset management, thereby assisting in the centralized storage or management of assets.

[0076] Therefore, the implementation method of the asset matching module includes: obtaining the interactive matching target of the asset change vector for interactive matching. The interactive matching target includes matching the assets that need to be maintained with the maintenance team, and matching the asset change vectors with high similarity to discover the relative similarity between the asset change vectors. At this time, the interactive matching target represents the data pair of the asset change vectors corresponding to the two asset devices, or represents the two asset change vectors extracted corresponding to the interactive matching target, to indicate the processing status of the interactive matching.

[0077] Perform feature screening on the asset change vectors to determine the comparison features under each interactive matching target. Perform multi-attention calculation on the comparison features according to the normalized values ​​of the asset change vectors and update frequency to obtain the matching probability between each asset change vector. Then, sort the asset change vectors from large to small according to the matching probability as the output asset matching result.

[0078] Assume that at the time of final matching, there is asset A: ACV=[0.65, 0.8, 0.45, 0.72, 0.18], UF_score=0.9, where ACV represents the asset change vector and UF_score represents the update frequency.

[0079] There is also a maintenance team B: ACV = [0.63, 0.79, 0.44, 0.71, 0.17], UF_score = 0.85; then the matching probability between asset A and team B is 0.92.

[0080] Maintenance Team B extracts asset change vectors by extracting relevant data about the assets handled by the maintenance team. The value of the asset change vector is extracted from the trend slope of the asset change vector, which is used as the data content for interpretation. The update frequency score is set based on the average update frequency of the asset equipment data relative to the historical data. For example, if it is close to 90% of the historical data average, it can be set to 0.9 to indicate that it is frequently updated. At this time, the corresponding data between the asset change vectors are matched. After inserting the asset change vector into the update frequency, the corresponding cosine similarity is calculated to obtain the matching degree between the asset change vectors. When performing multi-attention combination, four attention heads are set based on the asset change vectors and update frequency corresponding to asset A and maintenance team B. Then, calculations are performed on each attention head. After concatenating the data of each attention head, all data are weighted and summed along the concatenated dimension to obtain the weighted features processed by the multi-attention combination. Finally, the weighted features are input into the neural network, and the sigmoid function is used to output the matching probability. The asset change vectors are sorted from large to small according to the matching probability. The final sorted list is the asset matching result. The output matching probability will represent the Gaussian distribution probability of the corresponding feature. This probability will indicate whether the values ​​between the two matching asset change vectors are highly similar under the features of the current multi-attention combination processing. The final asset matching result can show the relationship between the respective asset change vectors under different matching probabilities.

[0081] In one embodiment of the present invention, the implementation method of the asset management module includes: based on the asset matching results, performing association rule mining on the asset matching results, identifying multiple consumables usage patterns corresponding to the asset matching results, grouping the asset equipment according to the consumables usage patterns, and setting the usage type distribution of the enterprise consumables according to the enterprise consumables corresponding to the asset equipment in each group. The method of evaluating the asset equipment represents grouping the relevant equipment according to the consumables usage patterns and matching probability values ​​of the data under the corresponding matching values ​​of the asset matching results. That is, when it is determined that the asset equipment is low-maintenance, the data that meets this requirement is selected as part of the equipment grouping at this time, or the data of each matched asset equipment in the asset matching results is treated as a node in the form of discrete distribution, and the edges between the nodes are represented by matching probabilities, and the nodes are clustered, and the clustered data is used as the equipment group corresponding to the consumables usage pattern.

[0082] During clustering, any node is used as the central node, and the central node is connected to other nodes to form multiple clusters. Each cluster is iterated continuously until the average value of the matching probability calculation within each cluster reaches a stable state. When there is no change, the corresponding cluster is output as the data after the asset equipment is grouped according to the consumables usage pattern.

[0083] The implementation method for the consumables usage pattern is as follows: identify the high-frequency consumables combination of the enterprise consumables corresponding to the asset matching results, use the Apriori algorithm to identify the frequent item sets in the enterprise consumables corresponding to the asset matching results, combine the frequent item sets according to the preset association rules, and output the data that meets the preset conditions in the combined frequent item sets as the consumables usage pattern.

[0084] The preset condition indicates that the support and confidence values ​​of the combined frequent itemsets meet at least one of the following conditions: the support of the combined frequent itemsets is greater than the minimum support threshold, and the confidence of the combined frequent itemsets is greater than the minimum confidence threshold; at this time, the minimum support threshold is required to be 0.3, and the minimum confidence threshold is 0.6. Since the types and data corresponding to asset equipment may be complicated and scattered, the main enterprise consumables under asset equipment maintenance and processing will be classified to find out the obvious consumption combinations in the enterprise consumables. The data display of these combinations can further describe how the current enterprise consumables are used and distributed.

[0085] Preset association rules are pre-set based on the associations between enterprise consumables, such as filters, lubricants, and other products. These products represent consumables that need to be replaced during equipment maintenance, and serve as the preset association rules for enterprise consumables at this time.

[0086] When grouping equipment, the assets and equipment are grouped according to the matching probability values ​​calculated in the assets and equipment, and are divided into groups under various consumable usage modes, such as high-energy consumption group and low-maintenance group. Then, the corresponding data of the enterprise consumables under each group is displayed to obtain the usage type distribution of the enterprise consumables, and the distribution of enterprise consumables under multiple data combination relationships such as asset equipment-consumable type-consumption scenario-consumption amount is displayed to describe the consumption intensity of consumables. After the data are displayed intuitively, the enterprise can timely view the relevant data of enterprise consumables and asset equipment obtained from multiple data sources to formulate resource management strategies for consumables management, and ultimately achieve the core goal of reducing costs and increasing efficiency.

[0087] Although the embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered by the scope of protection of the present invention.

Claims

1. An Internet-based enterprise consumables asset data management system, characterized by: include: The asset information module is used to obtain asset information of asset equipment and enterprise consumables based on basic information during asset management, and to set the asset interaction relationship between asset information and enterprise consumables; The asset verification module is used to conduct an inventory of assets and equipment based on asset interaction relationships, determine the actual status of each asset and equipment, and derive the asset location and update frequency of the asset equipment. The asset location includes static location, dynamic location, and business process location; An asset change module is used to verify the target change trend corresponding to the usage status of each asset equipment under the change of asset position according to the actual status of each asset equipment, and generate an asset change vector; wherein, the asset change module specifically includes: extracting trend features of the usage status of each asset equipment at the static position, dynamic position and business process position; using the usage time and maintenance interval corresponding to the asset equipment at the static position as the trend features of the static position, and associating them with the consumable usage to obtain a consumable consumption trend graph; using the maintenance times corresponding to the asset equipment at the dynamic position as the trend features of the dynamic position, and associating them with the consumable cost to generate a consumable cost trend graph; calculating the state transition frequency at the business process position as the trend feature of the business process position, and associating them with the consumable demand to generate a consumable demand trend graph; using the moving average of the slope values ​​of the consumable consumption trend graph, the consumable cost trend graph and the consumable demand trend graph as the trend slope of the target change trend, and using the trend slope as the asset change vector; The asset matching module is used to perform interactive matching using asset change vectors, determine the comparison features under asset interaction, combine the comparison features with the update frequency of asset devices, calculate the matching probability between each asset change vector through a multi-attention mechanism, and obtain the asset matching results of the multi-attention combination; The asset management module is used to evaluate asset equipment based on asset matching results and determine the usage type distribution of enterprise consumables.

2. The Internet-based enterprise consumables asset data management system according to claim 1, characterized in that: The implementation of the asset information module also includes: Obtain the scenario type of asset information, segment the asset information into scenarios, determine the data distribution of asset information in each scenario, and generate classification categories for asset information; Based on the classification of the asset information, a semantic segmentation vector of the asset information is obtained, and multiple mapping relationships of the asset information are obtained in sequence according to the semantic segmentation vector; The asset information is associated and combined with the data corresponding to the enterprise consumables according to the mapping relationship, and the result of the association and combination is used as the asset interaction relationship between the asset information and the enterprise consumables.

3. The Internet-based enterprise consumables asset data management system according to claim 2, characterized in that: The implementation methods for associating and combining asset information with data corresponding to enterprise consumables according to the mapping relationship include: Verify the time percentage of each asset equipment under the asset information mapping relationship, as well as the value percentage of enterprise consumables in each asset equipment category; Based on the time proportion numerator of each asset device, obtain the timeline of data changes in asset information under the mapping relationship, and extract each sub-event of asset interaction under this timeline; Identify whether the time points of each sub-event overlap, and use the value ratio numerator to determine whether the asset interaction is logical. When the asset interaction is logical and there are overlapping points, divide each sub-event into the interaction layer, contract layer and standard layer, and set the asset interaction relationship between the asset information and the enterprise consumables according to the connection relationship under the corresponding layer.

4. The Internet-based enterprise consumables asset data management system according to claim 1, characterized in that: The implementation methods of the asset verification module include: Obtain the life cycle corresponding to the asset information, perform relational encoding on each interaction data in the asset interaction relationship according to the life cycle corresponding to the asset information, set the relationship vector corresponding to the asset interaction relationship, and calculate the cosine similarity between each relationship vector to obtain the sequence data of the relationship vector under the current life cycle; Perform status dimension inventory on the sequence data in the current life cycle to determine whether the asset interaction in the current life cycle is normal. If normal, extract the asset location and update frequency of the current asset equipment.

5. The Internet-based enterprise consumables asset data management system according to claim 4, characterized in that: The implementation methods for status dimension inventory of sequence data in the current life cycle include: Obtain maintenance time, location, and cost of asset equipment based on sequence data during the current life cycle; Determine whether the maintenance time, maintenance location, and maintenance cost of the asset equipment meet the preset rules. If they meet the preset rules, it is determined that the asset interaction in the current life cycle is normal.

6. The Internet-based enterprise consumables asset data management system according to claim 1, characterized in that: The implementation of the asset matching module includes: Obtain the interactive matching target for the asset change vector for interactive matching, perform feature screening on the asset change vector, determine the comparison features under each interactive matching target, perform multi-attention calculation on the comparison features according to the normalized values ​​of the asset change vector and update frequency, obtain the matching probability between each asset change vector, and sort the asset change vectors from large to small according to the size of the matching probability as the output asset matching result.

7. The Internet-based enterprise consumables asset data management system according to claim 1, characterized in that: The implementation methods of the asset management module include: Based on the asset matching results, association rule mining is performed on the asset matching results to identify multiple consumable usage patterns corresponding to the asset matching results. Assets and equipment are grouped according to the consumable usage patterns. Based on the enterprise consumables corresponding to the asset equipment in each group, the usage type distribution of enterprise consumables is set.

8. The Internet-based enterprise consumables asset data management system according to claim 7, characterized in that: The consumables usage mode is implemented as follows: Identify the frequent item sets in the enterprise consumables corresponding to the asset matching results, combine the frequent item sets according to the preset association rules, and output the data in the combined frequent item sets that meet the preset conditions as the consumables usage pattern.

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