Cross-organization material sharing method and system

Abstract

The invention provides a cross-organization material sharing method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining the idle material data of each member enterprise, and forming a material data set; according to a material allocation request of a demand member enterprise, available state information of a target material in the material data set is read, and a priority weight of the material allocation request is calculated based on an emergency degree, an approval chain length and a historical occupation frequency of the material allocation request; dynamically locking the target material, adjusting the state from an available state to a locked state, and only allowing the request with the highest priority weight to maintain locking; continuously monitoring the allocation approval progress of the locked material, and judging whether the locked state should be released in advance; when the approval process is completely completed and delivery is confirmed through logistics information, the state of the target material is adjusted from a locked state to an allocated state; according to the invention, autonomy and accuracy of cross-organization material sharing are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method and system for cross-organizational material sharing. Background Art

[0002] Existing cross-organizational material sharing platforms generally use a centralized data entry and automated matching mechanism. Member companies enter their respective idle material information into a shared pool, and demand-side companies can query and initiate applications on the platform. To prevent the same material from being applied for by multiple parties at the same time, some systems use a "material lock" mechanism. That is, once an application is submitted, the relevant material will be marked as temporarily unavailable in the subsequent process, and other companies cannot apply for it again. However, some platforms, for the sake of process simplicity, do not set up a strict locking mechanism, allowing the same material to be applied for by multiple parties at the same time, and manual screening and allocation will be carried out after the approval process is completed.

[0003] For example, if multiple subsidiaries within a group participate in emergency allocation, if the platform doesn't have a locking mechanism, multiple companies can repeatedly apply for the same batch of critical supplies in a very short period of time, only to discover that the supplies are insufficient at the end of the approval process. This can lead to some companies' needs not being met in a timely manner, and even delays in emergency response due to misjudgments. Conversely, if a strict locking mechanism is implemented, once an application is submitted, the supplies will be locked for a long time. If there are delays in subsequent approval or circulation links, the target supplies will continue to be "occupied", and other companies will be unable to submit requests again, resulting in long-term unavailable supplies and affecting actual supply efficiency. Summary of the Invention

[0004] The purpose of the present invention is to provide a cross-organization material sharing method and system, aiming to solve the problems mentioned in the background technology.

[0005] In order to solve the above technical problems, the technical solutions of the present invention are as follows: In a first aspect, a method for sharing materials across organizations is provided, the method comprising: Obtain idle material data of each member enterprise and generate unique material identification, storage location, current quantity and historical flow information to form a material data set; Based on the material transfer request from the demanding member enterprise, the availability status information of the target material in the material data set is read. Based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, the priority weight of this material transfer request is calculated to obtain the priority parameter data; Dynamically lock the target materials based on the priority parameter data, record the lock time, and adjust the status of the target materials from available to locked. Only the material allocation requests with the highest priority weight are allowed to remain locked. Other requests are rejected and a lock failure prompt is returned. Continuously monitor the progress of locked material transfer approvals to determine whether the locked status should be released early. If approval is not completed within the preset period and there is a higher priority material transfer request, trigger the release process, restore the target material status from locked to available, and update the flow information to the material data set. When the approval process is completed and delivery is confirmed through logistics information, the status of the target materials is adjusted from locked to allocated, and all parameters of this allocation are written into the historical flow information.

[0006] Preferably, based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, the priority weight of the material transfer request is calculated to obtain priority parameter data, including: Extract the required completion time from the material allocation request, compare it with the preset standard completion time, and quantify the urgency into an urgency index based on the proportion of the completion time shortened. Analyze the list of all approval nodes that material transfer requests must go through, count the total number of approval nodes, and compare it with the preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, quantify the length of the approval chain as an approval chain length indicator; Retrieve the historical flow information of the target materials, calculate the sum of the number of allocations and the number of locks within the preset period, and quantify it as the historical occupancy index; The urgency index, approval chain length index and historical occupancy times index are weighted and summed using preset weighting coefficients to calculate the priority weight, form priority parameter data, and bind it to the corresponding material allocation request.

[0007] Preferably, the target material is dynamically locked according to the priority parameter data, the locking time is recorded, and the status of the target material is adjusted from the available state to the locked state. Only the material allocation request with the highest priority weight is allowed to remain locked, and the rest of the requests are rejected and a lock failure prompt is returned, including: For all target materials in the available state, retrieve the priority parameter data of their corresponding material allocation requests and sort them from high to low according to the priority weight to obtain the material demand priority data set; Based on the material demand priority dataset, the material transfer request with the highest priority is assigned a lock qualification, the corresponding target material status is adjusted from available to locked, and the locked material transfer request number, lock start time, and priority parameters are simultaneously recorded in the lock record field of the material dataset. In the material demand priority data set, for all material allocation requests except the one with the highest priority weight, a notification indicating that the request cannot be locked will be pushed to the demanding member enterprise, and the material allocation request will not be accepted.

[0008] Preferably, the progress of the allocation approval of locked materials is continuously monitored to determine whether the locked status should be released in advance. When the approval is not completed within the preset period and there is a material allocation request with a higher priority weight, the release process is triggered to restore the target material status from the locked state to the available state, and the flow information is updated to the material data set, including: For all target materials in the locked state, the approval node progress of their related material transfer requests is collected regularly at preset time intervals, and the cumulative processing time since the locking moment is calculated; When the cumulative processing time of the approval node progress exceeds the preset maximum approval cycle, and it is detected that a newly submitted material transfer request for the target material has a higher priority weight than the currently associated material transfer request, the release process is triggered and the following steps are executed: Restore the target material's status from locked to available, and write the release execution time, reason, related approval node information, and replaced material transfer request number into the target material's historical flow information. When the status of the target material is restored to an available state, the target material in the available state is dynamically locked again according to the priority parameter data of all currently pending material allocation requests.

[0009] Preferably, based on the material allocation request, the required completion time limit is extracted and compared with the preset standard completion time limit. The urgency is quantified into an urgency index based on the proportion of the completion time limit shortened, including: Extract the required completion time from the material transfer request and subtract it from the preset standard completion time to obtain the time difference. When the time difference is negative, the time difference is matched according to the preset graded time interval to obtain the urgency value; When the time difference is negative and within the preset extreme value range, the urgency value of the material allocation request is increased to the highest level of urgency and marked as a material allocation request that requires priority response; When the time difference is non-negative, the material transfer request is assigned a preset basic urgency value; The final urgency value is used as the urgency index of the corresponding material allocation request and is bound to it.

[0010] Preferably, the list of all approval nodes that a material transfer request needs to go through is analyzed, the total number of approval nodes is counted, and the total number is compared with a preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, the length of the approval chain is quantified as an approval chain length indicator, including: Based on the material transfer request, the associated approval process is analyzed to obtain the approval nodes that need to be completed in sequence. The position weight parameters and historical approval time corresponding to each approval node are retrieved to form an approval node data set. Based on the approval node dataset, the difference between the total number of approval nodes and the preset benchmark number of approval nodes is calculated. The corresponding weight coefficient is set based on the position weight parameter and historical approval time corresponding to each approval node. The total number of approval nodes is weighted and corrected to generate an approval chain length indicator, which is then associated with the material transfer request. When there are special links in the approval chain, a first weight correction coefficient is set according to the special link to adjust the approval chain length index to obtain the initial adjusted approval chain length index. The special links include multi-level countersignature, parallel approval, and automated approval. When it is detected that the number of abnormal situations in the approval node in the historical data reaches the preset number of abnormal situations, a timeout warning is set for the approval node, and the initially adjusted approval chain length indicator is adjusted according to the preset second weight correction coefficient to obtain a second adjusted approval chain length indicator.

[0011] Preferably, the historical circulation information of the target material is retrieved, and the sum of the number of allocations and the number of locks within a preset period is counted and quantified as a historical occupancy index, including: Retrieve the historical circulation information of the target material within the preset period, analyze the historical circulation information, count the total number of times the target material has been allocated and the total number of times it has been locked, and add the two values ​​together to form the historical occupation base number; Based on historical flow information, the frequency of abnormal situations is counted, and the abnormal situations are weighted according to the preset abnormal weight to obtain the abnormal correction value; Add the historical occupancy base times and the abnormal correction value to obtain the historical occupancy total times, and classify the historical occupancy total times into the corresponding historical occupancy times according to the preset classification threshold; The corresponding historical occupancy times are used as the historical occupancy times indicator of the current material allocation request of the target material and are bound to the allocation request.

[0012] Preferably, the urgency index, the approval chain length index, and the historical occupancy times index are weighted and summed using a preset weighting coefficient to calculate the priority weight and form priority parameter data, including: Set basic weight coefficients for the urgency index, approval chain length index, and historical occupancy times index respectively; Multiply the urgency index, approval chain length index, and historical occupancy times index by their corresponding basic weight coefficients to obtain their respective weighted results; The three weighted results are added together to obtain the priority weight value, which is then combined with the corresponding urgency index, approval chain length index, and historical occupancy times index as priority parameter data.

[0013] Preferably, the corresponding weight coefficient is set according to the position weight parameter and historical approval time corresponding to each approval node, including: According to the position weight parameters corresponding to each approval node, the position category information of each approval node is extracted, and the position weight value of the approval node is obtained according to the preset position weight comparison table; Calculate the average processing time based on the historical approval time corresponding to each approval node, and compare the average processing time with the preset standard approval time to obtain the approval time difference; When the approval time difference is non-negative, the job weight value of the approval node will be increased linearly in proportion. When the approval time difference is negative, the job weight value of the approval node will be reduced linearly in proportion to generate a corrected job weight value, which will be used as the weight coefficient of the approval node.

[0014] In a second aspect, a cross-organization material sharing system is provided, the system comprising: The data collection module is used to obtain the idle material data of each member enterprise and generate the material's unique identification, storage location, current quantity and historical flow information to form a material data set; The request processing module is used to read the availability status information of the target materials in the material data set based on the material allocation request of the demand member enterprise, and calculate the priority weight of this material allocation request based on the urgency of the material allocation request, the length of the approval chain and the number of historical occupancy times, and obtain the priority parameter data; The lock control module is used to dynamically lock the target material based on the priority parameter data, record the lock time, and adjust the status of the target material from available to locked. Only the material allocation request with the highest priority weight is allowed to maintain the lock, and the rest of the requests are rejected and the lock failure prompt is returned; The progress monitoring module is used to continuously monitor the progress of the allocation approval of locked materials and determine whether the locked status should be released early. When the approval is not completed within the preset period and there is a material allocation request with a higher priority weight, the release process is triggered, the target material status is restored from the locked state to the available state, and the flow information is updated in the material data set; The status change module is used to adjust the status of the target material from locked to allocated after the approval process is completed and the delivery is confirmed through logistics information, and write all parameters of this allocation into the historical flow information.

[0015] The above solution of the present invention includes at least the following beneficial effects: By uniquely identifying and standardizing the management of idle materials of each member enterprise, it is possible to achieve unified collection and dynamic updating of material information, ensuring the accuracy and traceability of the data. In the process of material allocation, a priority parameter data calculation mechanism based on multi-dimensional factors such as urgency, approval chain length, and historical occupancy times is introduced, so that the platform can scientifically judge the urgency and rationality of various allocation requests, and automatically realize intelligent sorting and resource allocation. Compared with the traditional "material locking" or no locking mechanism at all, the present invention can implement dynamic locking of target materials, monitor the approval progress of other material allocation requests in real time, and combine the priority of new requests to promptly determine whether to release the locked state in advance, effectively preventing materials from being occupied for a long time due to approval delays or waste of resources due to disorderly competition. For example, when multiple subsidiaries of a group simultaneously initiate emergency allocation applications for key materials, the remaining material allocation requests can dynamically assign the highest priority to the most urgent request with the shortest approval chain and the lowest historical occupancy rate, and lock resources first; if there is an approval delay and a new request with a higher priority, the remaining material allocation requests can actively release materials to ensure rapid response and maximum satisfaction of actual needs, thereby significantly improving the circulation efficiency, resource utilization and emergency response capabilities of the cross-organizational material sharing platform, and effectively overcoming specific problems in existing technologies such as manual approval screening prone to errors, long-term resource freezing and delayed allocation response. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flowchart of a cross-organization material sharing method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0018] like Figure 1 As shown, an embodiment of the present invention provides a method for cross-organization material sharing, the method comprising: Obtain idle material data of each member enterprise and generate unique material identification, storage location, current quantity and historical flow information to form a material data set; Based on the material transfer request from the demanding member enterprise, the availability status information of the target material in the material data set is read. Based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, the priority weight of this material transfer request is calculated to obtain the priority parameter data; Dynamically lock the target materials based on the priority parameter data, record the lock time, and adjust the status of the target materials from available to locked. Only the material allocation requests with the highest priority weight are allowed to remain locked. Other requests are rejected and a lock failure prompt is returned. Continuously monitor the progress of locked material transfer approvals to determine whether the locked status should be released early. If approval is not completed within the preset period and there is a higher priority material transfer request, trigger the release process, restore the target material status from locked to available, and update the flow information to the material data set. When the approval process is completed and delivery is confirmed through logistics information, the status of the target materials is adjusted from locked to allocated, and all parameters of this allocation are written into the historical flow information.

[0019] In this embodiment of the present invention, by acquiring and standardizing idle material data for each member enterprise, a complete material data set is formed. A unique identifier, storage location, current quantity, and historical flow information are generated for each material, significantly improving the traceability and refined management of cross-organizational materials. By dynamically calculating priority parameter data, different member enterprises can accurately assess the importance of transfer requests based on actual transfer needs, taking into account multiple factors such as urgency, approval chain length, and historical occupancy times. This enables intelligent sorting and automatic competitive allocation of material transfer requests. Furthermore, by real-time monitoring of the transfer approval progress of locked materials and determining release conditions, material resources can be released promptly based on actual business pressures, improving the efficiency of idle material transfers across organizations. Once the approval process is completed and the target materials are confirmed for delivery through logistics information, all transfer parameters are recorded in the historical flow information, facilitating subsequent business backtracking and transfer performance analysis. For example, if a member enterprise urgently transfers a batch of critical components during peak hours, the system can automatically assign a higher priority weight to these requests, giving them priority access to resources and effectively responding to sudden business demands.

[0020] The historical flow information specifically includes: For each target material, the system continuously records all related transfer, locking, release, and delivery events throughout its lifecycle, forming a time-series dataset. Each time a material's status changes, the system automatically generates a transfer record entry. This entry includes at least the time of the event, the event type (e.g., transfer request, locked, released, already transferred), the associated transfer request number, the target material's unique identifier, the operating position, the actual operator's information (if any), the transfer quantity, the transfer unit, the approval node information, the approval link status, logistics information (e.g., shipping time, arrival time, logistics order number), and corresponding priority parameter data.

[0021] Within the flow information, the system also marks any anomalies that occur, such as approval timeouts, incomplete transfers, and premature releases of locks, and records the detailed cause, handling results, and impact of the anomaly. Each flow record is archived according to a pre-set data structure to facilitate subsequent query, statistics, tracing, and analysis. For example, if a target material is transferred multiple times or locked or released multiple times, the system automatically counts the historical number of transfers, locks, and related anomaly frequencies, providing data support for the dynamic adjustment of priority parameters and the assignment of historical occupancy indicators.

[0022] Among them, all parameters of this allocation include: During the archiving phase after a material transfer request is completed, the system automatically organizes and records all core data directly related to the transfer process as "all parameters for this transfer." These parameters include at least the unique identifier of the target material, the transfer request number, information about the requesting company, the transfer application time, the requested completion deadline, the transfer quantity, the transfer unit, the names of all approval nodes involved in the approval process and their results, the actual approval time for each node, the start and end times of the lock status, the lock duration, priority parameter data (including urgency, approval chain length, historical occupancy times and their weights), the transfer result (e.g., success, failure, or interruption), logistics information for delivery confirmation (e.g., logistics order number, actual delivery time, receipt confirmation), and any exceptions encountered during the transfer process and their resolution.

[0023] For content involving priority parameter data, the system automatically performs a weighted aggregation based on the transfer request's urgency, the length of the approval chain, and the number of historical occupancy times, and archives the weighted result as the priority weight for this transfer request. All of these parameters are uniformly archived by the system according to the data structure, facilitating traceability and analysis of the entire transfer business process, supporting various applications such as subsequent management, auditing, and performance evaluation. For example, if a transfer involves multiple approval nodes and a timeout occurs at one of them, the time spent at the relevant nodes and the abnormal situation will be archived as the transfer parameter for this time, and can be used to dynamically adjust the priority parameters for the next transfer.

[0024] In a preferred embodiment of the present invention, the priority weight of the material transfer request is calculated based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, and the priority parameter data is obtained, including: Extract the required completion time from the material allocation request, compare it with the preset standard completion time, and quantify the urgency into an urgency index based on the proportion of the completion time shortened. Analyze the list of all approval nodes that material transfer requests must go through, count the total number of approval nodes, and compare it with the preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, quantify the length of the approval chain as an approval chain length indicator; Retrieve the historical flow information of the target materials, calculate the sum of the number of allocations and the number of locks within the preset period, and quantify it as the historical occupancy index; The urgency index, approval chain length index and historical occupancy times index are weighted and summed using preset weighting coefficients to calculate the priority weight, form priority parameter data, and bind it to the corresponding material allocation request.

[0025] In an embodiment of the present invention, by comparing the required completion time limit of the material allocation request with the preset standard completion time limit, the urgency can be quantified and an urgency index can be formed, so that the system can automatically identify the urgency of different allocation requests. The length of the approval chain is converted into an approval chain length index by counting the difference between the total number of approval nodes and the benchmark value, and combined with the complexity of the approval chain, thereby reflecting the impact of the approval process on the allocation efficiency. The number of historical occupancy is accurately reflected by the comprehensive statistics of the number of allocations and the number of locks. The three indicators are weighted and summed to generate priority parameter data, making the allocation process more scientific and objective. For example, if a certain allocation request has an extremely high degree of urgency, but the approval process is short and the historical occupancy frequency of the materials is low, the system can still automatically give the request a higher priority based on the weighted result, realizing dynamic optimization of multi-dimensional resources.

[0026] In a preferred embodiment of the present invention, target materials are dynamically locked based on priority parameter data, the locking time is recorded, and the status of the target materials is adjusted from available to locked. Only material transfer requests with the highest priority weight are allowed to remain locked, while other requests are rejected and a lock failure prompt is returned, including: For all target materials in the available state, retrieve the priority parameter data of their corresponding material allocation requests and sort them from high to low according to the priority weight to obtain the material demand priority data set; Based on the material demand priority dataset, the material transfer request with the highest priority is assigned a lock qualification, the corresponding target material status is adjusted from available to locked, and the locked material transfer request number, lock start time, and priority parameters are simultaneously recorded in the lock record field of the material dataset. In the material demand priority data set, for all material allocation requests except the one with the highest priority weight, a notification indicating that the request cannot be locked will be pushed to the demanding member enterprise, and the material allocation request will not be accepted.

[0027] In an embodiment of the present invention, the system can automatically retrieve and sort the priority parameter data of each transfer request for all target materials in available states, and form a material demand priority data set in real time. This mechanism ensures that each locking operation has the best decision-making basis, and the material transfer request with the highest priority weight can obtain exclusive locking qualifications. At the same time, the locking operation is numbered, the start time and the priority parameters are fully recorded to facilitate subsequent tracing. For transfer requests that fail to obtain locking qualifications, the system will automatically push a prompt that it cannot be locked, effectively avoiding repeated applications and waste of resources. For example, within a large group, multiple branches apply for the same batch of equipment at the same time. The system will give priority to applicants who are in urgent need, have a short process, and have less historical occupancy. The remaining branches will receive feedback immediately, effectively improving the transparency and fairness of the cross-organizational material sharing process.

[0028] In a preferred embodiment of the present invention, the progress of the allocation approval of locked materials is continuously monitored to determine whether the locked status should be released in advance. When the approval is not completed within the preset period and there is a material allocation request with a higher priority weight, the release process is triggered to restore the target material status from the locked state to the available state, and the flow information is updated in the material data set, including: For all target materials in the locked state, the approval node progress of their related material transfer requests is collected regularly at preset time intervals, and the cumulative processing time since the locking moment is calculated; When the cumulative processing time of the approval node progress exceeds the preset maximum approval cycle, and it is detected that a newly submitted material transfer request for the target material has a higher priority weight than the currently associated material transfer request, the release process is triggered and the following steps are executed: Restore the target material's status from locked to available, and write the release execution time, reason, related approval node information, and replaced material transfer request number into the target material's historical flow information. When the status of the target material is restored to an available state, the target material in the available state is dynamically locked again according to the priority parameter data of all currently pending material allocation requests.

[0029] In an embodiment of the present invention, by continuously monitoring the progress of the allocation approval of locked materials and regularly collecting progress data of relevant approval nodes at preset time intervals, the real-time circulation status of locked materials can be accurately grasped. By counting the cumulative processing time since the locking moment and comparing it with the preset longest approval cycle, the system can automatically trigger the release process when it finds that the approval has timed out and there is a higher priority allocation request, restore the material status from locked to available, and record the relevant operations of this release in detail to the historical circulation information. This mechanism ensures that materials will not be occupied for a long time due to stagnation in the approval process, so that resources can be dynamically transferred according to actual priority. For example, when resources are tight, if the approval of locked materials expires and there is a more urgent new request, the system can release resources in time and reallocate them, greatly improving the efficiency of material utilization and the response speed of allocation.

[0030] The preset maximum approval period includes: Based on business management requirements and industry experience, the platform system sets a maximum allowable approval time for the material transfer approval process, acting as a preset maximum approval cycle. This cycle can be flexibly configured by the system administrator based on factors such as the type of material, the complexity of the approval process, and historical transaction data. Typically, the maximum approval cycle is set in hours or days; for example, it can be set to 24 hours for general supplies and 4 hours for emergency supplies.

[0031] When the transfer approval process starts, the system automatically records the lock start time and compares it with the actual approval time at each approval node in real time to calculate the cumulative approval time from the lock start to the current time. If the cumulative approval time for the current transfer approval process is greater than or equal to the preset maximum approval cycle, the system automatically determines that the transfer request has timed out, triggering the release process.

[0032] In practice, administrators can dynamically adjust the maximum approval cycle parameters for different material categories and approval processes based on operational conditions to adapt to platform operations and enterprise emergency needs. For example, a shorter maximum approval cycle can be set for critical production materials to ensure efficient allocation and prevent long-term material occupancy due to approval delays.

[0033] The execution time, reason, relevant approval node information, and replaced material transfer request number of this release operation are written into the historical flow information of the target material, including: When the release process is triggered automatically or manually, the system immediately generates a new flow record to archive the details of this release operation. This record includes the following: First, the system captures and records the actual execution time of the release operation, which serves as the timestamp for the transaction record. Second, based on the triggering conditions of the release process, the system automatically generates a release reason description, such as "released due to approval timeout" or "released due to detection of a higher-priority transfer request." The system then simultaneously records information about all approval nodes associated with the release, including the approval node name, the actual approval status of each node, a list of completed and uncompleted nodes, and the approval time taken for each node.

[0034] Furthermore, if a release occurs while a higher-priority transfer request is in place, the system automatically retrieves and records the original release request number (i.e., the replaced material transfer request number) to ensure traceability of the transfer process. All of this information is written to the target material's historical flow information table using a unified data structure, facilitating subsequent query, statistics, and analysis of the release process.

[0035] For example, when a transfer request is released due to an approval timeout, the system records the precise time of release, the direct cause of the release (approval timeout), the status of each node in the approval process at that time, and the transfer request's unique ID. This information not only helps optimize subsequent processes but also provides reliable data support for platform managers to analyze approval bottlenecks and transfer failures.

[0036] In a preferred embodiment of the present invention, the required completion time limit is extracted from the material allocation request, compared with the preset standard completion time limit, and the urgency is quantified into an urgency index based on the proportion of the completion time limit shortened, including: Extract the required completion time from the material transfer request and subtract it from the preset standard completion time to obtain the time difference. When the time difference is negative, the time difference is matched according to the preset graded time interval to obtain the urgency value; When the time difference is negative and within the preset extreme value range, the urgency value of the material allocation request is increased to the highest level of urgency and marked as a material allocation request that requires priority response; When the time difference is non-negative, the material transfer request is assigned a preset basic urgency value; The final urgency value is used as the urgency index of the corresponding material allocation request and is bound to it.

[0037] In an embodiment of the present invention, by calculating the difference between the required completion time limit and the standard completion time limit in the material allocation request, and mapping the time difference to different graded time intervals, the urgency value corresponding to the allocation request can be automatically quantified and assigned. For requests in extremely urgent intervals, the system can further increase their urgency value and mark them as objects requiring priority response, thereby ensuring that critical business requests can obtain the highest priority in the allocation sorting. For ordinary requests, basic urgency values ​​are assigned to achieve differentiated management of the allocation process. For example, if a production line equipment temporarily fails, and the completion time limit set for the related material allocation request is much shorter than the conventional standard, the system will identify it as a high-urgency request to ensure priority flow of materials and reduce production losses.

[0038] The preset standard completion time limit specifically includes: The system sets a standard completion timeframe for the material transfer process based on the platform's historical transfer data, material type, enterprise business needs, and industry practices. This timeframe represents the reasonable length of time required from the submission of a transfer request to its expected completion, typically measured in hours or days. For example, for standard production materials, the standard completion timeframe might be 48 hours; for emergency supplies, the standard completion timeframe might be 12 hours.

[0039] This standard completion time limit is set by the system administrator in the configuration interface and can be configured individually for different material categories. When a transfer request is initiated, the system automatically retrieves the requested completion time limit and compares it with the standard completion time limit for the corresponding category to assess the urgency and priority of the current transfer. Administrators can dynamically adjust the standard completion time limit based on actual business changes to meet the needs of different scenarios, such as production, sales, or emergency response.

[0040] The preset grading time intervals specifically include: The system divides the difference between the required completion deadline and the standard completion deadline of a transfer request into several time intervals, which are used to quantify the urgency indicator. Each time interval represents a level of urgency. For example, intervals with negative time differences can be designated as "high urgency zone," intervals with zero time differences as "normal zone," and intervals with positive time differences as "relaxed zone." Further refinement is possible: If the time difference is less than -24 hours, it is an "extremely high emergency zone". The time difference is between -24 hours and -12 hours, which is a "high emergency zone". The time difference is between -12 hours and 0 hours, which is the "medium emergency zone". If the time difference is equal to or greater than 0, it is the "basic emergency zone".

[0041] The system assigns different urgency values ​​to transfer requests based on their time intervals, enabling quantitative tiered processing of urgency. Administrators can flexibly adjust the numerical boundaries and number of tiers within the time intervals based on actual business conditions and historical data.

[0042] The preset extreme value range specifically includes: The platform system sets one or more extreme value ranges for the time difference between the required completion deadline and the standard completion deadline to identify extremely urgent transfer requests. When the time difference falls below a preset extreme lower limit (e.g., -48 hours), the system classifies the transfer request as extremely urgent. Within this range, the system assigns the highest level of urgency and automatically marks the transfer request as "requiring priority response," giving it the highest priority in subsequent sorting and allocation.

[0043] This extreme value range can be set by administrators based on actual circumstances, such as the company's emergency response processes and historical emergency response timelines, and can be dynamically adjusted based on subsequent data optimization. For example, during special periods or peak production seasons, the extreme value range can be temporarily adjusted to accommodate high-frequency emergency allocation needs.

[0044] The preset basic urgency values ​​include: The basic urgency value is the lowest urgency score assigned by the system to transfer requests that lack obvious urgency characteristics. Generally, transfer requests with a completion deadline equal to or greater than the standard completion deadline are assigned a basic urgency value to indicate the standard nature of the business need. The basic urgency value is set by the system administrator based on the transfer priority scoring system to ensure reasonable and rational transfer sequencing.

[0045] The basic urgency value is used as an urgency indicator in subsequent priority weight calculations, ensuring that regular allocation requests don't take priority over resources due to misjudgment. This also provides a stable ranking baseline for the allocation system. Administrators can regularly adjust the basic urgency value based on actual allocation results and feedback to better align it with the company's resource allocation strategy and production operations.

[0046] In a preferred embodiment of the present invention, a list of all approval nodes that a material transfer request must pass through is analyzed, the total number of approval nodes is counted, and the total number is compared with a preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, the length of the approval chain is quantified as an approval chain length indicator, including: Based on the material transfer request, the associated approval process is analyzed to obtain the approval nodes that need to be completed in sequence. The position weight parameters and historical approval time corresponding to each approval node are retrieved to form an approval node data set. Based on the approval node dataset, the difference between the total number of approval nodes and the preset benchmark number of approval nodes is calculated. The corresponding weight coefficient is set based on the position weight parameter and historical approval time corresponding to each approval node. The total number of approval nodes is weighted and corrected to generate an approval chain length indicator, which is then associated with the material transfer request. When there are special links in the approval chain, a first weight correction coefficient is set according to the special link to adjust the approval chain length index to obtain the initial adjusted approval chain length index. The special links include multi-level countersignature, parallel approval, and automated approval. When it is detected that the number of abnormal situations in the approval node in the historical data reaches the preset number of abnormal situations, a timeout warning is set for the approval node, and the initially adjusted approval chain length indicator is adjusted according to the preset second weight correction coefficient to obtain a second adjusted approval chain length indicator.

[0047] In this embodiment of the present invention, an in-depth analysis of the approval process associated with material transfer requests is performed. By extracting the job weight parameters and historical approval times for each approval node, an approval node dataset is established. Based on the difference between the total number of approval nodes and a baseline number, as well as the weight parameters and time taken for each node, the system dynamically adjusts the approval chain length indicator to fully reflect the complexity of the approval process. When special links in the approval chain exist (such as multi-level countersignatures, parallel approvals, or automated approvals), the approval chain length indicator is further adjusted using a weight correction coefficient. In the event of abnormalities or delays in the approval node history, the system automatically sets a timeout warning and implements a secondary weight adjustment. This dynamic adjustment mechanism accurately reflects actual approval efficiency and process bottlenecks, promoting more efficient and scientific resource allocation. For example, when the approval chain is lengthy or a link is frequently delayed, the transfer system automatically lowers the priority of related requests, effectively preventing long-term material occupancy and material flow congestion.

[0048] Among them, the position weight parameters include: Based on the company's internal management system and material transfer approval process, the system assigns a preset weight to each position category (such as employee, supervisor, department manager, and senior management) corresponding to each approval node. This score reflects the decision-making influence and process complexity of each position in the approval chain. For example, the weight for an employee might be set to 1, for a department manager to 2, and for a senior management to 3.

[0049] During transfer process analysis, the system automatically identifies the job category for each approval node and finds its corresponding job weight parameter. The system then uses each node's job weight parameter in a weighted calculation of the approval chain length indicator. A higher weight parameter indicates a greater impact on the overall approval chain complexity. Administrators can adjust job categories and their weight parameters based on the organizational structure to dynamically reflect changes in enterprise management practices and business processes.

[0050] Among them, the first weight correction coefficient is set according to the special link to adjust the approval chain length indicator, specifically including: During the approval process, the system automatically identifies special process steps such as multi-level countersignatures, parallel approvals, and automated approvals. For each special step, the system pre-configures a first weight correction factor. For example, multi-level countersignatures are typically more complex than sequential, single-node approvals, so the first weight correction factor might be set to 1.5; parallel approvals might be set to 1.3, and automated approvals might be set to 0.7 to reflect their simplified nature.

[0051] When an approval chain includes a special link, the system multiplies the first weight correction coefficient for that link by the current approval chain length indicator or adjusts it using a preset weighting method to obtain the initial adjusted approval chain length indicator. This truly reflects the complexity and time consumption of the actual process, making subsequent priority calculations more reasonable. Administrators can regularly optimize and adjust the correction coefficient settings for various special links based on actual business experience and process analysis.

[0052] The preset number of exceptions includes: When monitoring and analyzing the historical operation of approval nodes, the system sets a threshold for the number of anomalies. This threshold determines the cumulative number of anomalies (such as approval delays, process interruptions, and missed completion times) that occur at a particular approval node within a specified statistical period. This threshold is set by the administrator based on historical process data, business sensitivity, and actual enterprise needs. For example, the preset number of anomalies might be set to 3. This means that if an approval node experiences three or more anomalies within a consecutive statistical period, the system automatically identifies the node as high-risk or prone to delays.

[0053] When the number of exceptions detected at a particular approval node reaches a preset threshold, the system automatically triggers subsequent weight adjustments or early warning mechanisms to prevent process bottlenecks from impacting overall allocation efficiency. Administrators can dynamically adjust the preset exception threshold based on system performance and allocation business feedback to better align with enterprise management objectives.

[0054] The second weight correction coefficient is preset, specifically including: When the number of exceptions at a particular approval node reaches or exceeds the preset exception threshold, the system automatically applies the corresponding secondary weight correction factor to further adjust the initially adjusted approval chain length indicator. This factor is typically greater than 1, significantly increasing the impact of abnormal nodes on the complexity of the approval chain. For example, a secondary weight correction factor of 1.2 could indicate that when a high-risk node is present, the overall approval chain length indicator would be further increased, thereby reducing the overall priority of the associated transfer request.

[0055] During the weight adjustment process, the system first calculates preliminary indicators based on position weight parameters and the first weight adjustment coefficient. Then, based on abnormal node occurrences, the system applies the second weight adjustment coefficient for secondary adjustments. This dynamically reflects the substantial impact of historical abnormalities on the allocation process priority. Administrators can regularly evaluate and adjust the second weight adjustment coefficient based on actual process analysis and abnormal node data to improve system adaptability and risk prevention capabilities.

[0056] In a preferred embodiment of the present invention, historical circulation information of the target material is retrieved, and the sum of the number of transfers and the number of locks within a preset period is counted and quantified as a historical occupancy index, including: Retrieve the historical circulation information of the target material within the preset period, analyze the historical circulation information, count the total number of times the target material has been allocated and the total number of times it has been locked, and add the two values ​​together to form the historical occupation base number; Based on historical flow information, the frequency of abnormal situations is counted, and the abnormal situations are weighted according to the preset abnormal weight to obtain the abnormal correction value; Add the historical occupancy base times and the abnormal correction value to obtain the historical occupancy total times, and classify the historical occupancy total times into the corresponding historical occupancy times according to the preset classification threshold; The corresponding historical occupancy times are used as the historical occupancy times indicator of the current material allocation request of the target material and are bound to the allocation request.

[0057] In an embodiment of the present invention, by searching and analyzing the historical flow information of the target material within a preset period, it is possible to comprehensively count the total number of times the target material was allocated and the total number of times it was locked within that period, and add these two values ​​to form the historical occupancy base number. Furthermore, the system can also identify abnormal situations that appear in the historical flow information, such as abnormal termination of the allocation process, abnormal release of the locked state, etc., and weight these abnormal situations according to the preset abnormality weight to obtain the abnormality correction value. By adding the historical occupancy base number and the abnormality correction value, the system can obtain the historical occupancy total number that reflects the actual flow risk and activity. Subsequently, the system classifies the historical occupancy total number according to the preset grading threshold, converts it into the corresponding historical occupancy number, and binds it as the historical occupancy number indicator for the current material allocation request of the target material. After this processing, the historical flow and abnormal conditions can objectively influence the priority of the allocation request, improving the scientific nature of resource allocation and the rationality of dynamic scheduling. For example, for a certain type of material that is frequently allocated and has multiple abnormal releases, the system will automatically increase its historical occupancy index, thereby lowering the priority of subsequent allocation requests, preventing repeated and ineffective occupation of resources, and improving the overall efficiency and stability of cross-organizational material sharing.

[0058] Among them, based on historical flow information, the frequency of abnormal situations is counted, and the abnormal situations are weighted according to the preset abnormal weight to obtain the abnormal correction value, which specifically includes: During a specified historical statistical period, the system automatically retrieves historical transfer information for the target material, traverses and categorizes all transfer records, and identifies abnormal situations, including incomplete transfers, premature release of locks, and interrupted approvals. For each abnormal situation, the system categorizes and counts it by type, accumulating the frequency of each type of abnormal situation. For example, within a certain period, the system may count three cases of incomplete transfers, two cases of premature release of locks, and one case of interrupted approvals.

[0059] The system then pre-assigns corresponding exception weights for different types of exceptions, reflecting the actual impact of each exception type on resource utilization or allocation efficiency. For example, an incomplete allocation has a weight of 2, a lock released early has a weight of 1.5, and an approval interruption has a weight of 2.5.

[0060] During weighted calculation, the system multiplies the frequency of occurrence of each type of abnormal situation by the corresponding abnormal weight one by one. After accumulating all weighted results, the abnormal correction value of the target material in the historical statistical period is obtained.

[0061] This approach allows high-risk, high-impact exceptions to be given greater weight in priority assessments, reflecting the availability risk of the target material in actual allocation. For example, if a material has multiple uncompleted allocations, the final exception correction value will be higher, resulting in an increase in its historical occupancy index, which will lower the priority of subsequent allocations for that material.

[0062] Among them, according to the preset classification threshold, the total number of historical occupancy times is classified into corresponding historical occupancy times, specifically including: System administrators can set several thresholds for the total number of historical occupancy based on the platform's actual operational data and management needs, dividing the total number into different occupancy levels. For example, the thresholds can be set as follows: 0-5 for low occupancy, 6-10 for medium occupancy, 11-20 for high occupancy, and 20 or above for extremely high occupancy.

[0063] When the system calculates the total number of historical occupancy times for a target material during a statistical period (i.e., the sum of the number of transfers and lockouts, after adding an anomaly correction value), it automatically compares this number with the tier threshold range and categorizes it into the corresponding historical occupancy level. Each level corresponds to a specific historical occupancy index value, which is used in subsequent priority parameter calculations.

[0064] This classification process helps quantify historical occupancy levels, enabling the scientific differentiation of materials with different activity and risk levels. For example, if a material has a total historical occupancy count of 13, the system automatically classifies it as high occupancy and assigns a higher historical occupancy count indicator in priority calculations, improving the rationality and accuracy of allocation sorting.

[0065] Administrators can dynamically optimize tier thresholds based on changes in business operations and resource utilization feedback to ensure that tier standards adapt to actual business development needs.

[0066] In a preferred embodiment of the present invention, the urgency index, the approval chain length index, and the historical occupancy times index are weighted and summed using a preset weighting coefficient to calculate the priority weight, thereby forming priority parameter data, including: Set basic weight coefficients for the urgency index, approval chain length index, and historical occupancy times index respectively; Multiply the urgency index, approval chain length index, and historical occupancy times index by their corresponding basic weight coefficients to obtain their respective weighted results; The three weighted results are added together to obtain the priority weight value, which is then combined with the corresponding urgency index, approval chain length index, and historical occupancy times index as priority parameter data.

[0067] In an embodiment of the present invention, the system sets basic weight coefficients for the urgency index, the approval chain length index, and the historical occupancy index respectively, and multiplies these three indicators with their respective weight coefficients and adds them together to obtain the final priority weight value. In this way, the allocation system can automatically realize the quantitative integration of multi-dimensional indicators and form unique and comparable priority parameter data for each material allocation request. The allocation request with a higher priority weight value can be given priority in the subsequent material allocation, dynamic locking and resource sorting links. This weighted summation method fully considers the business urgency, process complexity and historical occupancy, making allocation decisions more scientific and targeted. For example, when faced with multiple different allocation requests, the system gives priority to requests that are urgent, have simple processes, and whose materials are not frequently occupied through weight allocation, thereby achieving optimal resource allocation.

[0068] Among them, basic weight coefficients are set for the urgency index, approval chain length index, and historical occupancy times index, including: When calculating priority weights, the system comprehensively considers the urgency of the transfer request, the complexity of the approval process, and the historical occupancy of the target material. To ensure that the contribution of these three indicators to the final priority weighting meets actual business needs, the system pre-assigns a basic weight coefficient for each indicator. For example, the basic weight coefficient for the urgency indicator can be set to 0.5, the approval chain length indicator to 0.3, and the historical occupancy index to 0.2. These weight coefficients are set by the system administrator on the backend configuration page and can be dynamically adjusted based on historical operation data, transfer results, and enterprise scheduling preferences.

[0069] When calculating priority parameter data, the system automatically multiplies each indicator by its corresponding basic weight coefficient, aggregates the weighted results, and forms the final priority weight. This approach ensures that the influence of each indicator on allocation decisions can be flexibly adjusted, improving the system's controllability and adaptability. For example, if a company's operations prioritize efficient response, the weight coefficient of the urgency indicator can be increased; if a company is more concerned with the fairness of resource flow, the weight of the historical occupancy number indicator can be appropriately increased.

[0070] In a preferred embodiment of the present invention, the corresponding weight coefficient of each approval node is set according to the position weight parameter and historical approval time corresponding to each approval node, including: According to the position weight parameters corresponding to each approval node, the position category information of each approval node is extracted, and the position weight value of the approval node is obtained according to the preset position weight comparison table; Calculate the average processing time based on the historical approval time corresponding to each approval node, and compare the average processing time with the preset standard approval time to obtain the approval time difference; When the approval time difference is non-negative, the job weight value of the approval node will be increased linearly in proportion. When the approval time difference is negative, the job weight value of the approval node will be reduced linearly in proportion to generate a corrected job weight value, which will be used as the weight coefficient of the approval node.

[0071] In an embodiment of the present invention, by setting the corresponding weight coefficients of the job weight parameters and historical approval time corresponding to each approval node, the actual impact of each node in the approval process on the overall flow efficiency can be effectively reflected. The system first obtains the job weight value based on the job category information of the approval node and the preset job weight control, and then dynamically corrects the job weight value based on the comparison results of the historical approval time and the standard approval time of each node, and finally generates a corrected job weight coefficient. The impact of nodes with longer time consumption or higher job weight in the approval process is automatically amplified in the priority parameter data, reflecting the approval bottleneck or key link. After such processing, when the allocation request encounters a complex approval process or a certain node is often delayed, the system will automatically lower the priority of the relevant request, effectively preventing the decline in resource flow efficiency. For example, a certain allocation process involves multiple high-weight positions and the approval link has a history of frequent timeouts. The process will appear more complex and have a lower priority in the system calculation, thereby avoiding materials being occupied by inefficient processes for a long time.

[0072] Among them, the preset position weight comparison table specifically includes: Based on the company's organizational structure and actual approval processes, the system creates a position weighting table to reflect the decision-making influence and responsibility levels of different positions in the approval process. The table uses position categories as indexes, assigning each position a unique weighting score. For example, a general employee's position weight is 1, a section chief or supervisor's is 2, a department manager's is 3, and a vice president or general manager's is 4.

[0073] The position weight comparison table is set by administrators in the backend based on management levels, approval permissions, and historical process analysis experience, and can be adjusted based on actual business operations. When processing transfer requests, the system automatically identifies the position category corresponding to each approval node and searches the comparison table for the corresponding weight value, providing basic data for subsequent assessment of approval chain length and node complexity.

[0074] This ensures the objectivity and consistency of the approval chain length indicator and node weight correction process, and also facilitates flexible management after future job changes and organizational structure adjustments.

[0075] The preset standard approval time includes: The system sets a standard approval time for each approval node based on different job categories, material types, or historical business data. This standard approval time refers to the time the system deems reasonable for a job to handle an approval task under normal circumstances, typically measured in hours.

[0076] For example, the standard approval time for an ordinary employee is 2 hours, for a supervisor it is 4 hours, for a manager it is 8 hours, etc. The standard approval time is set by the administrator based on the actual operating efficiency of the enterprise and historical approval time, and can be updated regularly.

[0077] In the material transfer approval process, the system automatically compares the average processing time of actual approval nodes with the standard approval time for corresponding positions to assess node approval efficiency and adjust position weights accordingly. Setting standard approval times helps quantify the normal workload of each node in the process and provides a basis for identifying abnormal nodes and dynamically optimizing the process.

[0078] Among them, when the approval time difference is non-negative, the position weight value of the approval node is linearly increased according to the proportion. When the approval time difference is negative, the position weight value of the approval node is linearly reduced according to the proportion. The corrected position weight value is generated and used as the weight coefficient of the approval node, specifically including: When analyzing the historical approval times for each approval node, the system first calculates the difference between the actual average approval time and the standard approval time for the position at that node (the approval time difference). If the approval time difference is non-negative, it indicates that the actual processing efficiency of the node is low or there are delays. The system will then increase the original position weight in a linear manner. For example, for every hour exceeding the standard time, the weight value will increase by a certain percentage. On the contrary, if the approval time difference is negative, it means that the node approval efficiency is better than the standard, and the system will reduce the original job weight value in a linear manner. For example, for every hour the approval is completed in advance, the job weight value will be reduced by the corresponding proportion.

[0079] After these dynamic adjustments, the system uses the revised position weight as the final weight coefficient for that node, factoring it into subsequent calculations of the approval chain length indicator and overall transfer priority. This not only reflects changes in process node efficiency in real time, but also guides companies to focus on approval bottlenecks and efficiency improvement areas. For example, if a node has a history of frequent timeouts, its position weight will be continuously adjusted upwards, and the system will lower the ranking of transfer requests involving processes at that node when calculating priority, promoting process optimization.

[0080] An embodiment of the present invention further provides a cross-organization material sharing system, the system comprising: The data collection module is used to obtain the idle material data of each member enterprise and generate the material's unique identification, storage location, current quantity and historical flow information to form a material data set; The request processing module is used to read the availability status information of the target materials in the material data set based on the material allocation request of the demand member enterprise, and calculate the priority weight of this material allocation request based on the urgency of the material allocation request, the length of the approval chain and the number of historical occupancy times, and obtain the priority parameter data; The lock control module is used to dynamically lock the target material based on the priority parameter data, record the lock time, and adjust the status of the target material from available to locked. Only the material allocation request with the highest priority weight is allowed to maintain the lock, and the rest of the requests are rejected and the lock failure prompt is returned; The progress monitoring module is used to continuously monitor the progress of the allocation approval of locked materials and determine whether the locked status should be released early. When the approval is not completed within the preset period and there is a material allocation request with a higher priority weight, the release process is triggered, the target material status is restored from the locked state to the available state, and the flow information is updated in the material data set; The status change module is used to adjust the status of the target material from locked to allocated after the approval process is completed and the delivery is confirmed through logistics information, and write all parameters of this allocation into the historical flow information; It should be noted that this system is a system corresponding to the above method, and all implementation methods in the above method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0081] An embodiment of the present invention further provides a computing device comprising: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the above-described method. All implementations in the above-described method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0082] The embodiment of the present invention further provides a computer-readable storage medium storing instructions, which, when executed on a computer, causes the computer to execute the above-described method. All implementations in the above-described method embodiment are applicable to this embodiment and can achieve the same technical effects.

[0083] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A cross-organization material sharing method, characterized in that: The method comprises: Obtain idle material data of each member enterprise and generate unique material identification, storage location, current quantity and historical flow information to form a material data set; Based on the material transfer request from the demanding member enterprise, the availability status information of the target material in the material data set is read. Based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, the priority weight of this material transfer request is calculated to obtain the priority parameter data; Dynamically lock the target materials based on the priority parameter data, record the lock time, and adjust the status of the target materials from available to locked. Only the material allocation requests with the highest priority weight are allowed to remain locked. Other requests are rejected and a lock failure prompt is returned. Continuously monitor the progress of locked material transfer approvals to determine whether the locked status should be released early. If approval is not completed within the preset period and there is a higher priority material transfer request, trigger the release process, restore the target material status from locked to available, and update the flow information to the material data set. When the approval process is completed and delivery is confirmed through logistics information, the status of the target materials is adjusted from locked to allocated, and all parameters of this allocation are written into the historical flow information.

2. The cross-organization material sharing method according to claim 1, characterized in that: Based on the urgency of the material transfer request, the length of the approval chain, and the number of historical occupancy times, the priority weight of this material transfer request is calculated to obtain priority parameter data, including: Extract the required completion time from the material allocation request, compare it with the preset standard completion time, and quantify the urgency into an urgency index based on the proportion of the completion time shortened. Analyze the list of all approval nodes that material transfer requests must go through, count the total number of approval nodes, and compare it with the preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, quantify the length of the approval chain as an approval chain length indicator; Retrieve the historical flow information of the target materials, calculate the sum of the number of allocations and the number of locks within the preset period, and quantify it as the historical occupancy index; The urgency index, approval chain length index and historical occupancy times index are weighted and summed using preset weighting coefficients to calculate the priority weight, form priority parameter data, and bind it to the corresponding material allocation request.

3. The cross-organization material sharing method according to claim 1, characterized in that: Based on the priority parameter data, the target material is dynamically locked, the locking time is recorded, and the status of the target material is adjusted from available to locked. Only the material allocation request with the highest priority weight is allowed to remain locked. The rest of the requests are rejected and a lock failure prompt is returned, including: For all target materials in the available state, retrieve the priority parameter data of their corresponding material allocation requests and sort them from high to low according to the priority weight to obtain the material demand priority data set; Based on the material demand priority dataset, the material transfer request with the highest priority is assigned a lock qualification, the corresponding target material status is adjusted from available to locked, and the locked material transfer request number, lock start time, and priority parameters are simultaneously recorded in the lock record field of the material dataset. In the material demand priority data set, for all material allocation requests except the one with the highest priority weight, a notification indicating that the request cannot be locked will be pushed to the demanding member enterprise, and the material allocation request will not be accepted.

4. The cross-organization material sharing method according to claim 1, characterized in that: Continuously monitor the progress of the allocation approval of locked materials to determine whether the locked status should be released early. When the approval is not completed within the preset period and there is a material allocation request with a higher priority, trigger the release process, restore the target material status from locked to available, and update the flow information to the material data set, including: For all target materials in the locked state, the approval node progress of their related material transfer requests is collected regularly at preset time intervals, and the cumulative processing time since the locking moment is calculated; When the cumulative processing time of the approval node progress exceeds the preset maximum approval cycle, and it is detected that a newly submitted material transfer request for the target material has a higher priority weight than the currently associated material transfer request, the release process is triggered and the following steps are executed: Restore the target material's status from locked to available, and write the release execution time, reason, related approval node information, and replaced material transfer request number into the target material's historical flow information. When the status of the target material is restored to an available state, the target material in the available state is dynamically locked again according to the priority parameter data of all currently pending material allocation requests.

5. The cross-organization material sharing method according to claim 2, characterized in that: Based on the material allocation request, extract the required completion time limit and compare it with the preset standard completion time limit. Based on the shortened completion time limit ratio, quantify the urgency into an urgency index, including: Extract the required completion time from the material transfer request and subtract it from the preset standard completion time to obtain the time difference. When the time difference is negative, the time difference is matched according to the preset graded time interval to obtain the urgency value; When the time difference is negative and within the preset extreme value range, the urgency value of the material allocation request is increased to the highest level of urgency and marked as a material allocation request that requires priority response; When the time difference is non-negative, the material transfer request is assigned a preset basic urgency value; The final urgency value is used as the urgency index of the corresponding material allocation request and is bound to it.

6. The cross-organization material sharing method according to claim 2, characterized in that: Analyze the list of all approval nodes that a material transfer request must go through, count the total number of approval nodes, and compare it with the preset baseline number of approval nodes. Based on the increase or decrease in the number of approval nodes, quantify the length of the approval chain into an approval chain length indicator, including: Based on the material transfer request, the associated approval process is analyzed to obtain the approval nodes that need to be completed in sequence. The position weight parameters and historical approval time corresponding to each approval node are retrieved to form an approval node data set. Based on the approval node dataset, the difference between the total number of approval nodes and the preset benchmark number of approval nodes is calculated. The corresponding weight coefficient is set based on the position weight parameter and historical approval time corresponding to each approval node. The total number of approval nodes is weighted and corrected to generate an approval chain length indicator, which is then associated with the material transfer request. When there are special links in the approval chain, a first weight correction coefficient is set according to the special link to adjust the approval chain length index to obtain the initial adjusted approval chain length index. The special links include multi-level countersignature, parallel approval, and automated approval. When it is detected that the number of abnormal situations in the approval node in the historical data reaches the preset number of abnormal situations, a timeout warning is set for the approval node, and the initially adjusted approval chain length indicator is adjusted according to the preset second weight correction coefficient to obtain a second adjusted approval chain length indicator.

7. The cross-organization material sharing method according to claim 2, characterized in that: Retrieve the historical flow information of the target material, count the sum of the number of transfers and the number of locks within the preset period, and quantify it as the historical occupancy index, including: Retrieve the historical circulation information of the target material within the preset period, analyze the historical circulation information, count the total number of times the target material has been allocated and the total number of times it has been locked, and add the two values ​​together to form the historical occupation base number; Based on historical flow information, the frequency of abnormal situations is counted, and the abnormal situations are weighted according to the preset abnormal weight to obtain the abnormal correction value; Add the historical occupancy base times and the abnormal correction value to obtain the historical occupancy total times, and classify the historical occupancy total times into the corresponding historical occupancy times according to the preset classification threshold; The corresponding historical occupancy times are used as the historical occupancy times indicator of the current material allocation request of the target material and are bound to the allocation request.

8. The cross-organization material sharing method according to claim 2, characterized in that: The urgency index, approval chain length index, and historical occupancy times index are weighted and summed using a preset weighting coefficient to calculate the priority weight and form priority parameter data, including: Set basic weight coefficients for the urgency index, approval chain length index, and historical occupancy times index respectively; Multiply the urgency index, approval chain length index, and historical occupancy times index by their corresponding basic weight coefficients to obtain their respective weighted results; The three weighted results are added together to obtain the priority weight value, which is then combined with the corresponding urgency index, approval chain length index, and historical occupancy times index as priority parameter data.

9. The cross-organization material sharing method according to claim 6, characterized in that: The corresponding weight coefficients are set based on the job weight parameters and historical approval time of each approval node, including: According to the position weight parameters corresponding to each approval node, the position category information of each approval node is extracted, and the position weight value of the approval node is obtained according to the preset position weight comparison table; Calculate the average processing time based on the historical approval time corresponding to each approval node, and compare the average processing time with the preset standard approval time to obtain the approval time difference; When the approval time difference is non-negative, the job weight value of the approval node will be increased linearly in proportion. When the approval time difference is negative, the job weight value of the approval node will be reduced linearly in proportion to generate a corrected job weight value, which will be used as the weight coefficient of the approval node.

10. A cross-organizational material sharing system, characterized in that: Applied to the method according to any one of claims 1 to 9, the system comprises: The data collection module is used to obtain the idle material data of each member enterprise and generate the material's unique identification, storage location, current quantity and historical flow information to form a material data set; The request processing module is used to read the availability status information of the target materials in the material data set based on the material allocation request of the demand member enterprise, and calculate the priority weight of this material allocation request based on the urgency of the material allocation request, the length of the approval chain and the number of historical occupancy times, and obtain the priority parameter data; The lock control module is used to dynamically lock the target material based on the priority parameter data, record the lock time, and adjust the status of the target material from available to locked. Only the material allocation request with the highest priority weight is allowed to maintain the lock, and the rest of the requests are rejected and the lock failure prompt is returned; The progress monitoring module is used to continuously monitor the progress of the allocation approval of locked materials and determine whether the locked status should be released early. When the approval is not completed within the preset period and there is a material allocation request with a higher priority weight, the release process is triggered, the target material status is restored from the locked state to the available state, and the flow information is updated in the material data set; The status change module is used to adjust the status of the target material from locked to allocated after the approval process is completed and the delivery is confirmed through logistics information, and write all parameters of this allocation into the historical flow information.

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