Work ticket and material collaborative scheduling method based on multi-source data fusion

Abstract

The present application relates to the field of data processing, in particular to a work ticket and material collaborative scheduling method based on multi-source data fusion, the method comprising: summarizing the planned quantity of all dispatch orders under the work ticket, obtaining the initial authorized total quantity and the dynamic remaining available quota; taking the completion of the dispatch order as the trigger, taking the difference between the total quantity of the intelligent material cabinet out of the warehouse and the on-site residual quantity uploaded by the handheld terminal as the actual consumption quantity; calculating the initial consumption deviation according to the deviation between the actual consumption quantity and the planned quantity, and obtaining the effective consumption deviation by weighted correction using the historical consumption fluctuation degree; matching the compensation coefficient according to the deviation level, the material key level and the number of remaining unfinished dispatch orders; multiplying the original planned quantity of the unfinished dispatch order by the compensation coefficient to update the authorized quantity, and re-summarizing the dynamic remaining available quota. The present application realizes the dynamic closed-loop linkage of consumption and authorization, and guarantees the continuity and balance of material supply in the sequential operation of multiple dispatch orders.

Description

Technical Field

[0001] This invention relates to the field of data processing. More specifically, this invention relates to a method for collaborative scheduling of work orders and materials based on multi-source data fusion. Background Technology

[0002] In power line inspection and minor defect elimination work, a work order usually contains multiple work orders that are executed in sequence, that is, sub-task units of the work order. Each work order corresponds to a specific work step, and the required materials are collected in batches.

[0003] However, actual consumption on site often deviates from the plan due to differences in equipment status. When a work order exceeds its quota, the remaining quota for subsequent work orders is reduced, leading to interruption of material requisition, requiring manual intervention and approval, and causing work to stop.

[0004] Therefore, the existing technology lacks a collaborative scheduling scheme that can dynamically adjust the remaining work order authorization quota based on the actual consumption of completed work orders. Summary of the Invention

[0005] To address the technical problem of existing technologies being unable to dynamically adjust the remaining work order authorization limit based on the actual consumption of completed work orders, this invention provides the following technical solution.

[0006] A work order and material collaborative scheduling method based on multi-source data fusion includes: Summarize the planned quantities of each type of material for all work orders under the work ticket, and obtain the initial authorized total quantity and dynamic remaining available quota for each type of material; In response to a single work order completion event, the total amount of materials issued for the completed work order recorded by the smart material cabinet and the remaining amount of materials on site uploaded by the handheld terminal are obtained, and the difference between the total amount of materials issued and the remaining amount of materials on site is taken as the actual consumption amount after double verification. Based on the deviation between the actual consumption and the planned consumption, the initial consumption deviation is calculated, and the initial consumption deviation is weighted and corrected using the historical consumption fluctuation of this type of material to obtain the effective consumption deviation. Based on the deviation level of the effective consumption deviation, the preset key level of the material, and the quantity level of the remaining unfinished work orders in the current work order, the compensation coefficient of this type of material is obtained from the preset mapping relationship. The original planned requisition quantity of each incomplete work order is multiplied by the compensation coefficient to obtain the corrected authorization quantity. The corrected authorization quantities of each incomplete work order are then re-aggregated to update the dynamic remaining available quota. At the same time, a reservation adjustment instruction is sent to the warehouse management subsystem based on the updated dynamic remaining available quota to synchronously update the warehouse reservation information.

[0007] Optionally, after taking the difference between the total amount of materials issued and the remaining amount of materials on site as the actual consumption after double verification, the method further includes: If the difference is negative, the actual consumption amount after double verification is set to zero.

[0008] Optionally, the method further includes a step of assessing the credibility of the double-verified actual consumption: The absolute value of the difference between the actual consumption amount after double verification and the total amount of materials issued is calculated and used as the first parameter; The larger of the total amount of materials issued from the warehouse and the average actual consumption of this type of material in all historical similar operations is used as the second parameter. The ratio of the first parameter to the second parameter is calculated as the confidence level of the actual consumption amount after double verification. When the credibility exceeds the preset allowable deviation threshold, the consumption record is marked as questionable and an alarm is triggered.

[0009] Optionally, calculating the initial consumption deviation based on the deviation between the actual consumption and the planned requisition quantity includes: Calculate the difference between the actual consumption amount and the planned requisition amount after double verification; The initial consumption deviation is obtained by dividing the difference by the sum of the planned requisition quantity and the minimum constant.

[0010] Optionally, the step of using the historical consumption fluctuation of this type of material to weight and correct the initial consumption deviation to obtain an effective consumption deviation includes: Obtain the historical consumption coefficient of variation for this type of material, which is the ratio of the standard deviation to the mean of the consumption of this type of material in similar historical operations. The reciprocal of the sum of 1 and the historical consumption variation coefficient is used as the confidence weight; The effective consumption deviation is obtained by multiplying the initial consumption deviation by the confidence weight.

[0011] Optionally, the step of matching the compensation coefficient for this type of material from a preset mapping relationship based on the deviation level to which the effective consumption deviation belongs, the preset key level of the material, and the quantity level to which the number of remaining uncompleted work orders in the current work order belongs includes: Based on the range of effective consumption deviation, it is divided into three levels: negative deviation, normal, or positive deviation. Count the number of unfinished work orders under the current work order, and classify the remaining tasks into levels based on the preset quantity threshold; Using the combination of the three dimensions—the deviation level, the material criticality level, and the remaining task quantity level—as search criteria, the corresponding compensation coefficient value is obtained from the pre-configured multi-level inventory adjustment factor index table.

[0012] Optionally, classifying the effective consumption deviation into three levels—negative deviation, normal, or positive deviation—based on its numerical range includes: When the effective consumption deviation is less than the first preset threshold, it is determined to be a negative deviation; When the effective consumption deviation is greater than or equal to the first preset threshold and less than or equal to the second preset threshold, it is determined to be normal; When the effective consumption deviation is greater than the second preset threshold, it is determined to be a positive deviation.

[0013] Optionally, the step of simultaneously sending a reservation adjustment instruction to the warehouse management subsystem based on the updated dynamic remaining available quota to synchronously update the warehouse reservation information includes: After receiving the instruction, the warehouse management subsystem will adjust the reserved inventory to match the updated dynamic remaining available amount. If the updated dynamic remaining available quota is greater than the reserved inventory before the adjustment, then the corresponding amount of materials will be locked in the available inventory and marked as reserved for this work order; If the updated dynamic remaining available quota is less than the reserved inventory before the adjustment, the corresponding amount of materials will be released from the reserved inventory of the work order to restore it to available inventory.

[0014] The present invention has the following beneficial effects: 1. This invention uses a single work order completion event to trigger dual verification and feedback of actual consumption data, automatically converting the consumption deviation of completed tasks into a proportional adjustment of the authorization amount for subsequent work orders, forming a closed-loop mechanism that links consumption and authorization. This effectively avoids the problem of subsequent material requisition interruption due to excessive consumption in the preceding process, reduces manual approval intervention, and ensures continuous operation.

[0015] 2. This invention integrates two data sources: intelligent material cabinet outbound records and handheld terminal on-site residual confirmation. It obtains the actual consumption amount through difference verification and sets abnormal differences to zero. At the same time, it introduces a credibility assessment and alarm mechanism, which significantly improves the accuracy and reliability of consumption data and reduces the scheduling risk caused by single-source data deviation.

[0016] 3. This invention uses the historical consumption variation coefficient of materials to perform weighted correction on the initial consumption deviation, assigning a lower confidence level to materials with drastic fluctuations, so that the effective consumption deviation can more accurately reflect the degree of abnormality of the current deviation, avoid misadjustment caused by random fluctuations, and improve the robustness of the scheduling strategy.

[0017] 4. This invention combines three dimensions: effective consumption deviation level, material criticality level, and remaining task number level. It matches differentiated compensation coefficients from a preset multi-level index table to prioritize the adjustment of highly critical materials and scenarios with a large number of remaining tasks, making the authorization quantity adjustment more targeted and reasonable.

[0018] 5. After updating the dynamic remaining available quota, the present invention simultaneously sends a reservation adjustment instruction to the warehouse management subsystem, automatically locking or releasing the corresponding amount of reserved inventory, ensuring that the system's logical authorization quantity and the physical warehouse reservation quantity are consistent in real time, and providing accurate inventory guarantee for subsequent work order material requisition. Attached Figure Description

[0019] Figure 1 This is a flowchart of steps S1-S5 in the work order and material collaborative scheduling method based on multi-source data fusion in an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0021] Reference Figure 1 The work order and material collaborative scheduling method based on multi-source data fusion includes steps S1-S5, as follows: S1: Summarize the planned quantity of each type of material for all work orders under the work ticket, and obtain the dynamic remaining available quota for each type of material.

[0022] When the scheduling subsystem generates a new work order, it iterates through all work orders under that work order and reads the planned material requisition quantity for each type of material item by item.

[0023] For example, regarding supplies Let the total number of work orders included in the work order be... Work order For supplies The planned requisition quantity is The system then sums the planned requisition quantities for all work orders, and the sum is determined as the material quantity. The initial authorized total quantity at the work order level has the same unit of measurement as the inventory unit of measurement maintained in the material master data, such as piece, unit, meter, etc. Once this value is written into the work order data record, it remains unchanged throughout the entire lifecycle of the work order from activation to completion.

[0024] Along with the initial authorized total amount, there are also supplies. The dynamic remaining available quota under the current work order is not the physical inventory in the warehouse, but rather the authorized requisition limit reserved at the system logic level for all unexecuted work orders within the work order. In the initial stage when the work order is first generated and before the correction cycle is triggered, the system directly assigns the dynamic remaining available quota a value equal to the initial authorized total. When a subsequent work order completion event triggers the correction process, its value will be recalculated and updated based on the corrected authorized quantity of the work order.

[0025] The initial authorized total and dynamic remaining available quota mentioned above are both used as extended fields of the work order master data and are persistently stored in the database. This step completes the initial authorized total and dynamic remaining available quota settings for each type of material under the work order.

[0026] S2: Triggered by a single work order completion event, obtain the actual consumption data of materials after double verification.

[0027] Once a work order enters the execution phase, its subordinate work orders are dispatched to the field teams in a predetermined order. In the background process of the scheduling subsystem, the event monitoring module continuously monitors the status changes of each work order within the workflow engine.

[0028] The event triggering rule is configured as follows: when all material requisition batch records associated with a certain work order have been transferred to the completed state, and the on-site operation data uploaded by the smart material cabinet and handheld terminal for the work order have been successfully imported into the database and are in a fully ready state, the system determines that the work order has met the single work order completion event triggering condition.

[0029] Among them, the intelligent material cabinet is an intelligent storage device deployed on the warehouse site to record every material outbound operation and the quantity outbound; the handheld terminal is a mobile terminal device carried by the operators to enter operational data such as material usage and confirming on-site remaining materials at the work site.

[0030] Due to the non-ideal communication conditions in the field operation environment, the outbound records of the smart material cabinet may experience upload delays or data packet loss due to temporary network outages. Simultaneously, the on-site residual quantities manually confirmed by operators using handheld terminals may be inaccurate due to manual counting errors or omissions. If only a single data source is relied upon for direct estimation, the obtained material consumption figures may deviate significantly from the actual on-site consumption.

[0031] Therefore, after capturing a single work order completion event, the system initiates a dual verification of the actual material consumption for that completed work order.

[0032] Specifically, the completed work orders will be numbered as follows: The system reads the work order from the database. The quantity of materials to be requisitioned is filled in during the preparation stage, including the materials... The planned requisition quantity is recorded as At the same time, the smart material locker reads work orders. The total amount of each material issued is recorded as follows: It also reads the remaining quantity of materials on site, uploaded via handheld terminal and confirmed by the operator's electronic signature, and records it as... The remaining quantity on site refers to the amount of unused materials expected to be returned to the warehouse after the operation is completed. This quantity is entered by the operators on their handheld terminals based on the actual remaining material count.

[0033] Furthermore, regarding the aforementioned materials ,Will and Subtracting the two, we get the supplies. The actual consumption amount after double verification is denoted as .like and If the difference is negative, then automatically... Setting it to zero means that the outbound quantity is less than the remaining confirmed quantity, which usually indicates that there is a material return operation on site, and the system processes it with zero consumption.

[0034] To assess the reliability of the dual verification results and identify anomalous data, the verified actual consumption was further compared with single-source data collected solely based on the smart material locker's outbound records. This essentially treated the total outbound volume as the actual consumption.

[0035] Then calculate the actual consumption of a single material and The absolute value of the difference is used as the first parameter for calculation. The greater of the first parameter and the average actual consumption of the corresponding material in all historical similar tasks is used as the second parameter. The ratio of the first parameter to the second parameter is then calculated to obtain the reliability of the above double verification result.

[0036] Furthermore, a preset tolerance threshold is established, typically an empirical value of 0.15, which can be adjusted by the implementer based on the quality and tolerance of the on-site data. If the aforementioned reliability exceeds this tolerance threshold, it is determined that there is a significant inconsistency in the double-checked data for the material. The consumption record is automatically marked as questionable, and a deviation alarm log is triggered. The log content includes the work order number, material category identifier, and... , , The reliability of the double-checked results is assessed. This alert is pushed to the administrator's task list for subsequent manual review. If the reliability is less than or equal to the allowable deviation threshold, the data is considered to have passed the consistency check.

[0037] Regardless of supplies Actual consumption after double verification Whether it is marked as questionable, the system uses the actual consumption obtained through double verification. As this work order is for materials The final actual consumption value is recorded and associated with the work order completion event, then persistently written to the consumption details table in the database. This questionable flag serves only as a data quality indicator, for managers to review during offline tracing.

[0038] At this point, the actual consumption of materials for the completed work orders is obtained.

[0039] S3: Based on the deviation between the actual consumption of materials in the completed work order and the planned quantity of each type of material in the work order, obtain the effective consumption deviation of each type of material in the work order.

[0040] For completed work orders Various supplies in the game, reading various supplies and Because the planned quantities of different materials vary significantly, directly using the absolute difference between actual consumption and planned quantity cannot make horizontal comparisons between different materials. Therefore, the system first calculates a relative initial consumption deviation.

[0041] First, calculate the resources. Actual consumption after double verification With work order For supplies Planned requisition quantity The difference is used as the third parameter, and then the third parameter is divided by... Normalizing the result with a sum of extremely small constants yields the work order. For supplies The initial consumption deviation.

[0042] Meanwhile, the degree of fluctuation in historical material consumption affects the reliability of current deviation data: the more drastic the fluctuation in a material, the greater the likelihood that a single consumption deviation is due to random fluctuation, and the lower the data confidence level should be. Therefore, the system introduces a confidence weight based on the historical consumption coefficient of variation to correct the initial deviation. The system extracts the historical consumption coefficient of variation for this type of material from the historical consumption statistics module, which is the ratio of the standard deviation to the mean of the consumption of this type of material in similar historical operations, and is used to measure the degree of consumption fluctuation.

[0043] The confidence weight is calculated by taking the reciprocal of 1 and the sum of the historical consumption variation coefficients mentioned above. This confidence weight is then multiplied by the initial consumption deviation to obtain the work order. For supplies Effective consumption deviation.

[0044] Based on the above operations, the effective consumption deviation of each type of material for each work order can be obtained.

[0045] S4: Calculate the compensation coefficient for each type of material based on the effective consumption deviation of each work order for each type of material, the preset criticality level of each type of material, and the number of remaining uncompleted work orders.

[0046] After obtaining the effective consumption deviation of each type of material for each work order, the system needs to determine the compensation intensity for the remaining uncompleted work order authorization within the work order. Since different materials have different criticalities in power grid maintenance, and the amount of remaining tasks in the work order also affects the urgency of compensation, the compensation strategy must be differentiated. Therefore, the system determines the compensation coefficient for each type of material in the following manner.

[0047] Specifically, the system first divides the effective consumption deviation of this type of material into three levels: when the deviation is less than -0.2, it is a negative deviation; when the deviation is between -0.2 and 0.2, it is normal; and when the deviation is greater than 0.2, it is a positive deviation.

[0048] The above-mentioned scope can be adjusted according to the actual business tolerance level.

[0049] Meanwhile, the system reads the preset criticality level of this type of material from the material master data, and divides it into Level 1 (high critical), Level 2 (medium critical) and Level 3 (general); and counts the number of uncompleted work orders under the current work order, and divides the remaining task number into levels according to preset quantity thresholds: less than two remaining work orders is considered as few, three to five is considered as medium, and more than five is considered as many.

[0050] The system has a pre-configured multi-level inventory adjustment factor index table. This table uses combinations of three dimensions—deviation level, material criticality level, and remaining task quantity level—as search criteria, with each combination uniquely corresponding to a compensation coefficient value. For example, when the combination is positive deviation, level 1, and many, the corresponding compensation coefficient is 1.5; when the combination is negative deviation, level 3, and few, the corresponding compensation coefficient is 0.5; when the deviation level is normal, the compensation coefficient is always one, regardless of the criticality level or the remaining task quantity level.

[0051] The system retrieves the corresponding values ​​from the index table based on the deviation level, criticality level, and remaining task count level of the material in the current period. These values ​​are then used directly as the final compensation coefficient for that type of material. The system records these values ​​along with the correction event, material identifier, and correction timestamp to complete the calculation of the compensation coefficient for that type of material.

[0052] S5: Adjust the original planned requisition quantity of each incomplete work order based on the compensation coefficient of each type of material, obtain the revised authorized quantity, and update the dynamic remaining available quota and warehouse reservation information accordingly.

[0053] After the compensation coefficient is determined, the scheduling subsystem adjusts the original planned requisition quantity of all incomplete work orders within this work order proportionally. The system iterates through the work orders currently incomplete, and for each type of material involved in this correction, reads the originally reported planned requisition quantity of each incomplete work order as the original planned authorization quantity. This original planned authorization quantity is then multiplied by the corresponding compensation coefficient to obtain the corrected authorization quantity.

[0054] When the compensation coefficient is greater than 1, the revised authorized quantity is higher than the planned quantity; when the compensation coefficient is less than 1, the revised authorized quantity is lower than the planned quantity.

[0055] The system will uniformly overwrite the original planned requisition quantity of each incomplete work order with the corresponding corrected authorized quantity for that material, thus completing the batch update of the authorization record at the work order level.

[0056] Since the authorized quantities of each incomplete work order have been changed in batches, the dynamic remaining available quota for the material on the work order needs to be re-aggregated. The system sums the corrected authorized quantities of all incomplete work orders under the current work order, and the result is used as the updated dynamic remaining available quota. This result is written into the work order master data record to overwrite the original value, thus completing the update of the available quota at the work order level.

[0057] Changes in the dynamic remaining available quota directly affect the quantity of materials reserved in the warehouse for work orders. Based on this, the scheduling subsystem generates a material reservation adjustment instruction and sends it to the warehouse management subsystem. This instruction includes the work order identifier, material category, and the updated dynamic remaining available quota value. Upon receiving the instruction, the warehouse management subsystem adjusts the reserved inventory to match the updated dynamic remaining available quota: if the new quota is greater than the original quota, the corresponding quantity of materials is additionally locked in the available inventory and marked as reserved for the work order; if the new quota is less than the original quota, the corresponding quantity of materials is released from the reserved inventory of the work order, restoring it to available inventory. Through this reservation adjustment, the inventory locked by the warehouse for the work order remains consistent with the corrected dynamic remaining available quota, and the warehouse reservation information is updated synchronously.

[0058] In this embodiment of the invention, the system also performs a compliance inquiry operation: before adjusting the planned requisition quantity according to the compensation coefficient, or in parallel with the adjustment step, it determines whether the effective consumption deviation of the materials associated with the current work order is greater than a preset positive deviation threshold, and whether the critical level of the material is the highest preset level. The preset positive deviation threshold is preferably 0.8 in this embodiment; that is, a compliance inquiry is triggered when the effective consumption deviation exceeds 0.8 and the material is of the highest critical level. This threshold can be adjusted according to the management sensitivity of different regional power grids. When both conditions are met simultaneously, the system automatically generates a compliance inquiry work order, which includes the work order identifier, material category, deviation value, and trigger timestamp, and sends it to the management personnel terminal via a message push interface. The generation and push of this inquiry work order do not interrupt the material requisition process, that is, they do not affect the execution of subsequent authorized quantity adjustments and warehouse reservation update operations.

[0059] In summary, this method obtains and provides feedback on actual consumption data triggered by a single work order completion event, automatically converting the consumption deviation of previous tasks into adjustments to the authorization amount of subsequent work orders, forming a closed-loop mechanism in which consumption and authorization are linked, thereby ensuring the dynamic balance of material supply in scenarios where multiple work orders are executed sequentially.

[0060] It should be noted that those skilled in the art can make various modifications and improvements without departing from the inventive concept, and these all fall within the scope of protection of this invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A work order and material collaborative scheduling method based on multi-source data fusion, characterized in that, include: Summarize the planned quantities of each type of material for all work orders under the work ticket, and obtain the initial authorized total quantity and dynamic remaining available quota for each type of material; In response to a single work order completion event, the total amount of materials issued for the completed work order recorded by the smart material cabinet and the remaining amount of materials on site uploaded by the handheld terminal are obtained, and the difference between the total amount of materials issued and the remaining amount of materials on site is taken as the actual consumption amount after double verification. Based on the deviation between the actual consumption and the planned consumption, the initial consumption deviation is calculated, and the initial consumption deviation is weighted and corrected using the historical consumption fluctuation of this type of material to obtain the effective consumption deviation. Based on the deviation level of the effective consumption deviation, the preset key level of the material, and the quantity level of the remaining unfinished work orders in the current work order, the compensation coefficient of this type of material is obtained from the preset mapping relationship. The original planned requisition quantity of each incomplete work order is multiplied by the compensation coefficient to obtain the corrected authorization quantity. The corrected authorization quantities of each incomplete work order are then re-aggregated to update the dynamic remaining available quota. At the same time, a reservation adjustment instruction is sent to the warehouse management subsystem based on the updated dynamic remaining available quota to synchronously update the warehouse reservation information.

2. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, After using the difference between the total amount of materials issued and the remaining amount of materials on site as the actual consumption after double verification, the method further includes: If the difference is negative, the actual consumption amount after double verification is set to zero.

3. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, It also includes a step of assessing the credibility of the double-checked actual consumption: The absolute value of the difference between the actual consumption amount after double verification and the total amount of materials issued is calculated and used as the first parameter; The larger of the total amount of materials issued from the warehouse and the average actual consumption of this type of material in all historical similar operations is used as the second parameter. The ratio of the first parameter to the second parameter is calculated as the confidence level of the actual consumption amount after double verification. When the credibility exceeds the preset allowable deviation threshold, the consumption record is marked as questionable and an alarm is triggered.

4. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, The calculation of the initial consumption deviation based on the deviation between the actual consumption and the planned requisition quantity includes: Calculate the difference between the actual consumption amount and the planned requisition amount after double verification; The initial consumption deviation is obtained by dividing the difference by the sum of the planned requisition quantity and the minimum constant.

5. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, The method of using the historical consumption fluctuation of this type of material to perform weighted correction on the initial consumption deviation to obtain the effective consumption deviation includes: Obtain the historical consumption coefficient of variation for this type of material, which is the ratio of the standard deviation to the mean of the consumption of this type of material in similar historical operations. The reciprocal of the sum of 1 and the historical consumption variation coefficient is used as the confidence weight; The effective consumption deviation is obtained by multiplying the initial consumption deviation by the confidence weight.

6. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, The compensation coefficient for this type of material is obtained by matching it from a preset mapping relationship based on the deviation level of the effective consumption deviation, the preset key level of the material, and the quantity level of the remaining uncompleted work orders in the current work order. Based on the range of effective consumption deviation, it is divided into three levels: negative deviation, normal, or positive deviation. Count the number of unfinished work orders under the current work order, and classify the remaining tasks into levels based on the preset quantity threshold; Using the combination of the three dimensions—the deviation level, the material criticality level, and the remaining task quantity level—as search criteria, the corresponding compensation coefficient value is obtained from the pre-configured multi-level inventory adjustment factor index table.

7. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 6, characterized in that, The classification of the effective consumption deviation into three levels—negative deviation, normal, or positive deviation—based on the numerical range of the effective consumption deviation includes: When the effective consumption deviation is less than the first preset threshold, it is determined to be a negative deviation; When the effective consumption deviation is greater than or equal to the first preset threshold and less than or equal to the second preset threshold, it is determined to be normal; When the effective consumption deviation is greater than the second preset threshold, it is determined to be a positive deviation.

8. The work order and material collaborative scheduling method based on multi-source data fusion according to claim 1, characterized in that, The simultaneous sending of a reservation adjustment instruction to the warehouse management subsystem based on the updated dynamic remaining available quota, in order to synchronously update the warehouse reservation information, includes: After receiving the instruction, the warehouse management subsystem will adjust the reserved inventory to match the updated dynamic remaining available amount. If the updated dynamic remaining available quota is greater than the reserved inventory before the adjustment, then the corresponding amount of materials will be locked in the available inventory and marked as reserved for this work order; If the updated dynamic remaining available quota is less than the reserved inventory before the adjustment, the corresponding amount of materials will be released from the reserved inventory of the work order to restore it to available inventory.

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