Work order scheduling management method, system, equipment, medium and product

Abstract

The invention discloses a work order scheduling management method, system and device, a medium and a product. The method comprises the following steps: acquiring an execution variable of a current work order in real time; the execution variable comprises task execution information, equipment condition information and resource use information; comparing the execution variable with a preset execution variable standard to obtain a current deviation set; the current deviation set comprises a variable self-deviation value and a cross-variable conduction deviation value; inputting the current deviation set into a pre-trained work order execution influence model to obtain an expected execution influence; the work order execution influence model is obtained through training according to historical execution variables and actual execution results in the historical work order execution process; and according to the expected execution influence, by taking the execution variable standard of the current work order as a target, carrying out resource re-allocation on equipment involved in the current work order. By adopting the embodiment of the invention, the real-time sensing and intelligent adjustment of the work order execution process can be realized, the work order is effectively ensured to be completed on time, and the scheduling efficiency and the resource utilization rate are improved.

Description

Technical Field

[0001] This invention relates to the field of scheduling management technology, and in particular to a work order scheduling management method, system, equipment, medium and product. Background Technology

[0002] Work order scheduling management is commonly used in multiple industries. Its main purpose is to optimize and automate the allocation and scheduling of tasks or work orders in order to improve work efficiency, reduce resource waste, and ensure timely completion of tasks.

[0003] However, in existing technologies, work order scheduling and management methods proceed according to the initially planned work order list after assigning work orders to maintenance personnel, completely ignoring the problem of mismatch between the current work order list and dynamic needs during work order execution, which makes it impossible to guarantee the timeliness of equipment maintenance. Summary of the Invention

[0004] The embodiments of the present invention aim to provide a work order scheduling management method, system, device, medium and product, which can realize real-time perception and intelligent adjustment of the work order execution process, effectively ensure the timely completion of work orders, improve scheduling efficiency and resource utilization, and reduce delays, resource waste and quality risks caused by deviations.

[0005] In a first aspect, embodiments of the present invention provide a work order scheduling management method, including: The execution variables of the current work order are obtained in real time; the execution variables include task execution information, equipment status information, and resource usage information. The executed variable is compared with a preset executed variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable transmission deviation value; The current deviation set is input into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the historical work order execution process. Based on the expected execution impact, and taking the execution variable standard of the current work order as the target, the equipment involved in the current work order is reallocated resources.

[0006] As an improvement to the above solution, the real-time acquisition of the execution variables of the current work order includes: The planned start time, planned completion time, actual start time, and actual completion time of the subtasks in the current work order are obtained in real time and used as task execution information. Real-time acquisition of equipment failure frequency, duration, and severity during the execution of the current work order, as equipment status information; Real-time acquisition of manpower and material resources invested in the current work order, as resource usage information.

[0007] As an improvement to the above scheme, the step of comparing the execution variable with a preset execution variable standard to obtain the current deviation set includes: Obtain a preset execution variable standard, compare the execution variable with its corresponding execution variable standard, and calculate the variable deviation value of each execution variable; Based on the influence transmission relationship between the executed variables and the variable's own deviation value, calculate the cross-variable transmission deviation value of each executed variable affected by other executed variables; Based on the variable's own deviation value and the intervariate transmission deviation value, the current deviation set of each execution variable is obtained.

[0008] As an improvement to the above scheme, the step of calculating the intervariate transmission deviation value of each executed variable under the influence of other executed variables based on the influence transmission relationship between executed variables and the variable's own deviation value includes: Select the first execution variable from all execution variables; If the deviation value of the first executed variable is greater than a preset first deviation value threshold, the influence transmission relationship between the first executed variable and the second executed variable is obtained; the second executed variable is any executed variable other than the first executed variable. Based on the influence transmission relationship and the variable's own deviation value of the first execution variable, the expected value of the second execution variable is obtained; Calculate the difference between the expected value and the standard of the execution variable in the corresponding stage. If the difference is greater than the preset second deviation threshold, the difference is used as the intervariate transmission deviation value of the second execution variable.

[0009] As an improvement to the above scheme, the step of inputting the current deviation set into a pre-trained work order execution impact model to obtain the expected execution impact of the current work order includes: Based on the current deviation set, we obtain the current task execution deviation set, the current device status deviation set, and the current resource usage deviation set; The current task execution deviation set, the current equipment status deviation set, and the current resource usage deviation set are input into the pre-trained work order execution impact model, so that the current deviation set is matched with the historical deviation set through the work order execution impact model to obtain the expected execution result of the current work order; The expected impact of the current work order is obtained based on the deviation between the expected execution result and the planned execution result.

[0010] As an improvement to the above scheme, the expected execution impact includes time impact, schedule impact, quality impact, and interruption scenarios; Among them, time impact refers to the deviation between the expected completion time and the planned completion time of the current work order; schedule impact refers to the deviation between the expected completion schedule of each subtask in the current work order and the preset schedule node; quality impact refers to the deviation between the expected execution quality of the current work order and the preset quality standard; and interruption status refers to the reason for interruption and the duration of interruption during the execution of the current work order.

[0011] As an improvement to the above scheme, the training method for the work order execution impact model includes: Obtain historical execution variables and actual execution results during the execution of historical work orders; The historical execution variables are compared with preset execution variable standards to obtain the historical deviation set of each historical execution variable; Based on the historical deviation set and the actual execution results, training samples are constructed; The work order execution impact model is trained using the training samples to screen key influencing factors of historical execution variables from the historical deviation set and learn the mapping relationship between the key influencing factors and the actual execution results.

[0012] As an improvement to the above scheme, the step of constructing training samples based on the historical deviation set and the actual execution results includes: Based on the historical deviation set, the deviation labels of each historical execution variable at each execution stage are obtained; Based on the actual execution results, the completion time label, completion progress label, execution quality label, and interruption status label of the historical work order at each execution stage are obtained as execution result labels; Training samples are constructed based on the deviation label and the execution result label.

[0013] As an improvement to the above scheme, the step of training the work order execution impact model using the training samples, and then using the work order execution impact model to screen key influencing factors of historical execution variables from the historical deviation set, and learning the mapping relationship between the key influencing factors and the actual execution results, includes: The training samples are divided into a training set and a test set according to a preset ratio; The work order execution impact model is trained using the training set to screen key influencing factors of historical execution variables from the historical deviation set, and to calculate the causal weights between the key influencing factors and the actual execution results; the causal weights include time causal weights, schedule causal weights, quality causal weights, and interruption causal weights. The trained work order execution impact model is tested using the test set to obtain model performance. If the model performance is lower than a preset performance threshold, the causal weights are adjusted based on the performance.

[0014] As an improvement to the above solution, the step of reallocating resources to the equipment involved in the current work order based on the expected execution impact and targeting the execution variable standard of the current work order includes: Based on the expected impact, filter the affected target devices from the current work order; The tools and resources required to acquire the target device; Based on the pre-built personnel skill profiles and the aforementioned tool resources, and with the execution variable standards of the current work order as the target, the human and material information in the current work order is adjusted.

[0015] Secondly, embodiments of the present invention provide a work order scheduling and management system, including: The execution variable acquisition module is used to acquire the execution variables of the current work order in real time; the execution variables include task execution information, equipment status information, and resource usage information. The deviation set generation module is used to compare the executed variable with a preset executed variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable propagation deviation value; The expected execution impact generation module is used to input the current deviation set into a pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the execution of historical work orders; The resource scheduling module is used to reallocate resources to the equipment involved in the current work order based on the expected execution impact and with the execution variable standard of the current work order as the target.

[0016] Thirdly, embodiments of the present invention provide a work order scheduling management device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the work order scheduling management method as described above.

[0017] Fourthly, embodiments of the present invention provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the work order scheduling management method as described above.

[0018] Fifthly, embodiments of the present invention provide a computer program product, the computer program product including a computer program or computer instructions, wherein when the computer program or computer instructions are executed by a processor, the work order scheduling management method described above is performed.

[0019] Compared with existing technologies, this invention discloses a work order scheduling management method, system, device, medium, and product. It acquires the execution variables of the current work order in real time. These execution variables include task execution information, equipment status information, and resource usage information. The execution variables are compared with preset execution variable standards to obtain a current deviation set. This current deviation set includes the variable's own deviation value and cross-variable propagation deviation value. The current deviation set is input into a pre-trained work order execution impact model to obtain the expected execution impact of the current work order. The work order execution impact model is trained based on historical execution variables and actual execution results during historical work order execution. Based on the expected execution impact, and using the current work order's execution variable standards as the target, resources are reallocated to the equipment involved in the current work order. Using this invention, real-time perception and intelligent adjustment of the work order execution process can be achieved, effectively ensuring timely completion of work orders, improving scheduling efficiency and resource utilization, and reducing delays, resource waste, and quality risks caused by deviations. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the steps of a work order scheduling and management method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a work order scheduling and management system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a work order scheduling and management device provided in an embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] In the description and claims, it should be understood that the terms "first," "second," etc., used in the description and claims are only for the purpose of distinguishing the description of the same technical features, and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated, nor necessarily the order of description or chronological order. The terms are interchangeable where appropriate. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature.

[0023] The existing work order scheduling logic remains at the static initial planning level. It usually assigns work orders to the corresponding maintenance personnel based on a pre-defined work order list order, and then uses this list as the sole basis for progress.

[0024] However, during work order execution, there may be dynamic changes in demand. For example, the difficulty of equipment maintenance may increase or an emergency task may arise, causing the current work order to be shelved, which in turn prevents the originally allocated resources from being deployed as planned. If the static planning does not reserve sufficient resource backup mechanisms, it can only passively wait for resources to be restored or manually adjust the work order, which will slow down the overall work order execution progress.

[0025] Based on the above considerations, this invention provides a work order scheduling and management method. Please refer to... Figure 1 In this embodiment, the work order scheduling management method is specifically executed through steps S1 to S4: S1. Obtain the execution variables of the current work order in real time; the execution variables include task execution information, equipment status information, and resource usage information.

[0026] A work order is a complete task with a clear objective. During execution, a work order is broken down into several specific sub-tasks. There may be sequential dependencies between sub-tasks. The execution status of all sub-tasks is summarized into the overall status of the work order.

[0027] The work order execution process is dynamic, and the execution variables change with the progress of the work order. By obtaining the execution variables in the current work order execution process in real time, the execution status of the work order can be controlled in a timely manner, and accurate decisions can be made.

[0028] S2. Compare the executed variable with the preset executed variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable transmission deviation value.

[0029] The preset execution variable standards are the baseline values, reasonable ranges, specification requirements or target parameters set in advance when the work order is generated. They are a reference system for measuring whether the actual execution variables meet expectations. The core of them is to clarify the theoretical state of each type of execution variable.

[0030] In some preferred embodiments, there are preset standards for the completion status of each sub-task in the work order, as well as preset standards for the overall completion status of the work order. For example, the execution variable standards include task execution standards, such as the total time limit, time node requirements for each sub-task, and execution order constraints; they may also include equipment status standards, such as performance index thresholds, fault level limits, and maintenance operation specifications; furthermore, they may include resource usage standards, such as the number of personnel, material consumption limits, resource utilization efficiency thresholds, and resource budget limits.

[0031] It is worth noting that, considering that deviations in work order execution are not isolated, calculating only the deviation of a single variable would underestimate the actual impact. For example, severe equipment failure not only leads to deviations in the equipment status information itself, but may also prevent timely repairs due to escalation of the failure level, thus causing deviations in task execution information. Therefore, in this embodiment of the invention, the current deviation set, including both the variable's own deviation value and the cross-variable propagation deviation value, comprehensively reflects the true degree of deviation in work order execution.

[0032] The current deviation set includes both the direct difference between the actual value of a single executed variable and the preset standard, i.e., the variable's own deviation value, and the indirect deviation caused by the deviation of a certain executed variable on other executed variables, i.e., the cross-variable transmission deviation value.

[0033] S3. Input the current deviation set into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the historical work order execution process.

[0034] It should be noted that the current deviation set reflects the deviation between the current execution of the work order and the standard situation. However, since the impact of deviation on the overall work order may be different under different work order scenarios, the current deviation set cannot directly reflect the impact.

[0035] The work order execution impact model learns the correlation between deviations and impacts in historical work orders by training with historical execution variables and actual execution results. This allows the deviation values ​​to be transformed into specific expected execution impacts, reflecting the various impacts that the current deviation set may have on the execution results.

[0036] S4. Based on the expected execution impact, and taking the execution variable standard of the current work order as the target, reallocate resources to the equipment involved in the current work order.

[0037] It should be noted that the goal is to achieve the execution variable standard, and to correct the deviations in the current work order execution process as much as possible through resource reallocation, so as to meet the current work order's requirements in terms of time, quality, and other aspects.

[0038] In the above solution, by capturing the comprehensive deviation of execution variables in real time, combining the pre-trained work order execution impact model to accurately predict the execution impact, and dynamically optimizing resource allocation, it is possible to realize real-time perception and intelligent adjustment of the work order execution process, effectively ensuring the timely completion of work orders, significantly improving scheduling efficiency and resource utilization, and reducing delays, resource waste and quality risks caused by deviations not being fully captured or the transmission impact being ignored.

[0039] As a preferred implementation, step S1, obtaining the execution variables of the current work order in real time, includes: The planned start time, planned completion time, actual start time, and actual completion time of the subtasks in the current work order are obtained in real time and used as task execution information. Real-time acquisition of equipment failure frequency, duration, and severity during the execution of the current work order, as equipment status information; Real-time acquisition of manpower and material resources invested in the current work order, as resource usage information.

[0040] In some preferred embodiments, the task execution information accurately records the planned start time, actual start time, planned completion time, and actual completion time for each work order task, enabling the determination of whether the task was executed ahead of schedule, on time, or delayed. It also records whether the actual execution order of the tasks matches the planned order, and the quality of task completion, such as whether predetermined quality standards were met and whether rework was required.

[0041] Task execution information focuses on the time progress of subtasks. By comparing the planned time with the actual time, it reflects whether subtasks started and completed on time, serving as the basis for judging whether task execution deviates from the plan. Delays in task execution time often directly lengthen the overall completion time of the work order. If multiple tasks have dependencies, errors in the task execution order may also prevent subsequent tasks from proceeding normally, thus seriously affecting the work order progress. Rework caused by substandard task quality not only increases time costs but may also consume more resources.

[0042] In some preferred embodiments, the equipment status information collects operational status data of the equipment during work order execution. This includes whether the equipment malfunctions, the frequency and duration of malfunctions, and the extent to which the malfunctions affect the equipment's performance, such as reduced equipment speed or decreased accuracy. It also records the equipment's routine maintenance status, such as whether maintenance is performed on time and the quality of maintenance work.

[0043] Equipment status information focuses on the fault condition of equipment, reflecting its ability to support task execution by quantifying the frequency, duration, and severity of faults. Frequent or prolonged equipment failures can interrupt work order execution, affecting overall progress. Degraded equipment performance may result in substandard product quality, requiring additional processing or rework. Inadequate equipment maintenance may increase the risk of equipment failure, indirectly impacting work order execution.

[0044] In some preferred embodiments, resource usage information statistics include: Regarding human resources, this involves tracking the actual number of personnel and job types used, discrepancies between the actual figures and the plan, and a comparison of personnel work efficiency with expectations. Regarding material resources, it records the actual quantity and specifications of materials, tools, and other supplies used, deviations from the plan, and whether the quality of the supplies meets requirements. Regarding financial resources, it calculates the difference between actual costs and budgeted costs, including any overspending or savings in various expenses.

[0045] Resource usage information focuses on the input of human and material resources, reflecting whether resource supply matches task requirements. Insufficient manpower may slow task progress, and a mismatch between personnel skills and tasks will also reduce work efficiency. Shortages or quality issues with material resources may lead to tasks not being completed on time or product quality problems. Budget overruns may limit subsequent resource input and affect the continued progress of work orders.

[0046] In a preferred implementation, step S2 involves comparing the execution variable with a preset execution variable standard to obtain the current deviation set, and then executing steps S21 to S23. S21. Obtain a preset execution variable standard, compare the execution variable with its corresponding execution variable standard, and calculate the variable deviation value of each execution variable. S22. Based on the influence transmission relationship between the execution variables and the deviation value of the variable itself, calculate the cross-variable transmission deviation value of each execution variable affected by other execution variables; S23. Based on the variable's own deviation value and the cross-variable transmission deviation value, obtain the current deviation set of each execution variable.

[0047] In some preferred embodiments, when performing step S21, the task execution information of the current work order is compared with a preset task execution information standard to obtain a first task execution deviation value, which is used as the variable deviation value of the task execution information; the equipment status information of the current work order is compared with a preset equipment status information standard to obtain a second equipment status deviation value, which is used as the variable deviation value of the equipment status information; and the resource usage information of the current work order is compared with a preset resource usage standard to obtain a third resource usage deviation value, which is used as the variable deviation value of the resource usage information.

[0048] The primary deviation in task execution stems from the difference between the actual task execution time and the preset time. When maintenance personnel receive a work order and experience a delay—meaning the current execution time is slower than the preset time—the difference in execution time is calculated and converted into the first task execution deviation. This deviation reflects the task execution error caused solely by the delay, assuming no other interfering factors.

[0049] The second equipment condition deviation value is generated by changes in the equipment's own condition. If the equipment suffers further damage during the execution of a work order by maintenance personnel, the new degree of damage is taken as the second equipment condition deviation value. It independently reflects the deterioration of the equipment's condition during maintenance and has no direct causal relationship with task execution or resource factors; it only addresses changes in the degree of damage to the equipment itself. Preferably, the deviation value of the equipment condition information is calculated by comparing it with the initial degree of equipment failure damage.

[0050] The third resource utilization deviation is generated by changes in the resource itself. When maintenance workers encounter tool damage or leave during work order tasks, the resource availability of maintenance equipment decreases. The third resource utilization deviation is formed by combining the duration of worker leave and the number of damaged tools. It is a resource utilization deviation caused by problems with the resource itself (tool damage, personnel leave).

[0051] Directly comparing the executed variable with the preset standard is the core step in determining whether a single variable has deviated. Only by first clarifying the deviation of each variable can we further analyze whether this deviation will affect other variables, which is a prerequisite for subsequent calculation of cross-variable transmission bias.

[0052] Further, preferably, step S22, calculating the intervariate transmission deviation value of each executed variable affected by other executed variables based on the influence transmission relationship between executed variables and the variable's own deviation value, includes: Select the first execution variable from all execution variables; If the deviation value of the first executed variable is greater than a preset first deviation value threshold, the influence transmission relationship between the first executed variable and the second executed variable is obtained; the second executed variable is any executed variable other than the first executed variable. Based on the influence transmission relationship and the variable's own deviation value of the first execution variable, the expected value of the second execution variable is obtained; Calculate the difference between the expected value and the standard of the execution variable in the corresponding stage. If the difference is greater than the preset second deviation threshold, the difference is used as the intervariate transmission deviation value of the second execution variable.

[0053] It should be noted that different executed variables have interactive and mutually influential relationships; the deviation of one executed variable may cause deviations in other executed variables. Based on the influence transmission relationship between executed variables, and combined with the deviation value of a certain executed variable, it is possible to calculate the indirect deviation of other executed variables caused by the deviation of that variable.

[0054] It should also be noted that the first deviation threshold is for the first execution variable, while the second deviation threshold is for the second execution variable. The specific value of the deviation threshold is related to the execution variable and the execution stage of the work order.

[0055] When the first execution variable is task execution information, the second execution variable is selected sequentially from device status information and resource usage information.

[0056] If the deviation value of the first task execution exceeds the preset first deviation value threshold, some equipment may remain in operation under fault conditions. The longer the task execution time is extended, the greater the degree of equipment failure and damage will be, leading to a serious deviation in the equipment's operating status. Based on this, the first equipment status deviation value can be obtained. The first equipment status deviation value is the result of the task execution delay affecting the equipment status, reflecting the role of task execution in the equipment's condition.

[0057] Furthermore, if the deviation value of the first task execution exceeds a preset first deviation value threshold, the existence of execution progress difference may lead to a shortage of maintenance personnel, maintenance materials, etc., as originally planned. For example, the number of missing maintenance personnel and maintenance materials are counted to obtain the first resource utilization deviation value of resource utilization information.

[0058] When the first execution variable is device status information, the second execution variable is selected sequentially from task execution information and resource usage information. If the second device status deviation value is greater than the preset first deviation value threshold, it may indicate that the equipment has been further damaged during the execution of the work order by the maintenance personnel.

[0059] This increases the difficulty of maintenance, which in turn affects the timeline for maintenance personnel to complete their tasks, causing the timeline to extend. This extended task execution time is marked as the second task execution deviation value. It should be noted that the second task execution deviation value has a different cause than the first task execution deviation value. It is a task execution deviation caused by changes in equipment condition, and there is a sequence: first, the equipment is further damaged, and then the task execution time is extended.

[0060] At the same time, more maintenance tools, maintenance personnel and / or maintenance materials may be needed due to the increased level of equipment failure. A second resource utilization deviation value can be obtained by calculating the expected increase in resource demand.

[0061] When the first execution variable is resource usage information, the second execution variable is selected sequentially from task execution information and device status information. If the third resource usage deviation value is greater than the preset first deviation value threshold, it may correspond to a damaged maintenance tool or a maintenance worker being on leave.

[0062] This will affect the time schedule of maintenance personnel's task execution. The resulting impact on the task execution time will be marked as the third task execution deviation value. The third task execution deviation value is the deviation value caused by the impact of changes in resource factors on task execution time.

[0063] Similarly, deviations in resource usage information can also lead to deviations in equipment status information. When resource changes occur, such as broken maintenance tools or maintenance personnel being on leave, the degree of equipment damage will increase, and this increased degree of equipment damage is marked as the third equipment status deviation value.

[0064] The integrated results show that the intervariate transmission deviation values ​​of task execution information include the second task execution deviation value and the third task execution deviation value; the intervariate transmission deviation values ​​of equipment status information include the first equipment status deviation value and the third equipment status deviation value; and the intervariate transmission deviation values ​​of resource usage information include the first resource usage deviation value and the second resource usage deviation value.

[0065] In the preferred embodiments of the present invention described above, for any execution variable, there are a first deviation value, a second deviation value, and a third deviation value. These three types of deviation values ​​can constitute the current deviation set of the execution variable, wherein the first deviation value is the deviation caused by task execution information, the second deviation value is the deviation caused by device status information, and the third deviation value is the deviation caused by resource usage information.

[0066] As a preferred implementation, step S3, inputting the current deviation set into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order, includes: Based on the current deviation set, we obtain the current task execution deviation set, the current device status deviation set, and the current resource usage deviation set; The current task execution deviation set, the current equipment status deviation set, and the current resource usage deviation set are input into the pre-trained work order execution impact model, so that the current deviation set is matched with the historical deviation set through the work order execution impact model to obtain the expected execution result of the current work order; The expected impact of the current work order is obtained based on the deviation between the expected execution result and the planned execution result.

[0067] Because the impact paths of each execution variable on the work order result differ, the current deviation set is divided according to the dimensions of the execution variables. For example, the current task execution deviation set includes the first task execution deviation value, the second task execution deviation value, and the third task execution deviation value; the current equipment status deviation set includes the first equipment status deviation value, the second equipment status deviation value, and the third equipment status deviation value; the current resource usage deviation set includes the first resource usage deviation value, the second resource usage deviation value, and the third resource usage deviation value.

[0068] During task execution, time delays, sequence errors, and quality issues not only independently affect work order completion but also interact with each other. For example, rework caused by quality issues may lead to time delays, thus affecting the overall schedule. Regarding equipment condition, high failure frequency may lead to more severe equipment performance degradation, while inadequate equipment maintenance increases the likelihood of failures. In terms of resource utilization, insufficient manpower may lead to idle or underutilized material resources, and budget overruns may affect the subsequent replenishment of manpower and material resources.

[0069] The historical deviation set and the correlation between the actual execution results obtained by training the work order execution impact model in this embodiment of the invention are used to map the current deviation value to the expected execution result. The expected execution result can reflect the execution status of the current work order in different aspects, so as to make accurate adjustments when there is a need for resource reallocation.

[0070] In some preferred embodiments, the anticipated performance impact includes time impact, schedule impact, quality impact, and disruption. Among them, time impact refers to the deviation between the expected completion time and the planned completion time of the current work order; schedule impact refers to the deviation between the expected completion schedule of each subtask in the current work order and the preset schedule node; quality impact refers to the deviation between the expected execution quality of the current work order and the preset quality standard; and interruption status refers to the reason for interruption and the duration of interruption during the execution of the current work order.

[0071] In terms of time, the impact includes the comparison between the actual completion time and the planned completion time of the work order, such as whether it was completed on time and the specific duration of the delay. Factors such as deviations in task execution time and interruptions caused by equipment failures will be reflected in the impact of the work order completion time through model calculations.

[0072] In terms of schedule, the impact on schedule reflects whether the overall task progresses according to the predetermined process and sequence. Issues such as incorrect task execution order or execution interruptions caused by equipment failure will affect the overall schedule, and the model will assess the impact on schedule based on the input deviation set data.

[0073] In terms of quality, the impact refers to the quality status related to the product or service. Factors such as degraded equipment performance and substandard task execution quality can be used to calculate the impact on the quality of the final deliverables of the work order.

[0074] Work order execution may be interrupted due to factors such as equipment failure, and the duration of the interruption is also one of the factors that measure the completion status of the work order. In terms of interruption, the model will consider whether the work order execution is interrupted due to factors such as equipment failure or resource shortage, and the duration of the interruption.

[0075] The impact of the current deviation set on the current work order is measured through four dimensions: time, schedule, quality, and interruption. The expected execution impact can comprehensively and accurately reflect the possible consequences of the deviation.

[0076] As a preferred embodiment, the training method for the work order execution impact model is performed through steps A1-A4: A1. Obtain historical execution variables and actual execution results during the execution of historical work orders; A2. Compare the historical execution variables with the preset execution variable standards to obtain the historical deviation set of each historical execution variable; A3. Construct training samples based on the historical deviation set and the actual execution results; A4. The work order execution impact model is trained using the training samples to select key influencing factors of historical execution variables from the historical deviation set through the work order execution impact model, and to learn the mapping relationship between the key influencing factors and the actual execution results.

[0077] It should be noted that the variable dimensions of the historical execution variables are selected in the same way as the variable dimensions of the current work order execution variables. Similarly, the historical deviation set and the current deviation set both include the variable's own deviation value and the cross-variable transmission deviation value. The specific acquisition method will not be described in detail here.

[0078] In some preferred embodiments, the historical deviation set obtained in step A2 is further subjected to feature extraction and selection. Through correlation analysis, key features that have a significant impact on work order completion are screened out, reducing data dimensionality and improving model training efficiency. For example, equipment stability features are extracted from raw data such as equipment failure frequency and duration.

[0079] Preferably, for task execution time delays, the specific percentage increase in work order completion time for each certain delay duration is determined; for task sequence errors, the overall delay time is assessed based on the dependencies between tasks. Regarding equipment status, the relationship between failure frequency and duration and work order interruption duration is clarified, as well as the connection between the degree of equipment performance degradation and the incidence of product quality problems. In terms of resource utilization, the percentage increase in task execution time due to insufficient manpower, the time range of task pauses caused by material shortages, and the degree of limitation on resource replenishment due to budget overruns and their comprehensive impact on work order completion time and quality are calculated.

[0080] The above approach enables the accurate identification of key influencing factors based on real historical experience and the understanding of their correlation with execution results. This provides a reliable model foundation for predicting the expected execution impact of current work orders, ensuring that the prediction results are supported by historical data and are logically consistent.

[0081] Further, preferably, step A3, constructing training samples based on the historical deviation set and the actual execution results, includes: Based on the historical deviation set, the deviation labels of each historical execution variable at each execution stage are obtained; Based on the actual execution results, the completion time label, completion progress label, execution quality label, and interruption status label of the historical work order at each execution stage are obtained as execution result labels; Training samples are constructed based on the deviation label and the execution result label.

[0082] It should be noted that the execution phase refers to the phased stages in the historical work order execution process, divided by time or workflow. For example, the execution phase includes the subtask initiation phase, the equipment operation phase, and the resource input phase. The execution result label is a structured description of the actual execution result of each execution phase.

[0083] In the above scheme, the work order execution impact model is a supervised learning model, trained using labeled training samples. In the work order execution scenario, there are clear inputs (such as task execution information, equipment status information, resource usage information, and other relevant data) and outputs (work order completion status, such as whether it was completed on time, whether the quality met, etc.). Through historical work order data, the correspondence between various influencing factors and work order completion status is already known, thus making it suitable for the application of supervised learning models.

[0084] For example, decision trees, support vector machines, random forests, or multilayer perceptrons can be used to construct work order execution impact models.

[0085] In some preferred embodiments, step A4, training the work order execution impact model using the training samples, to screen key influencing factors of historical execution variables from the historical deviation set through the work order execution impact model, and learning the mapping relationship between the key influencing factors and the actual execution results, includes: The training samples are divided into a training set and a test set according to a preset ratio; The work order execution impact model is trained using the training set to screen key influencing factors of historical execution variables from the historical deviation set, and to calculate the causal weights between the key influencing factors and the actual execution results; the causal weights include time causal weights, schedule causal weights, quality causal weights, and interruption causal weights. The trained work order execution impact model is tested using the test set to obtain model performance. If the model performance is lower than a preset performance threshold, the causal weights are adjusted based on the performance.

[0086] Preferably, when conducting model performance testing, accuracy, recall, and F1 score are used for evaluation; more preferably, when predicting work order completion time, mean absolute percentage error is used to measure the relative error between the predicted value and the actual value.

[0087] In other preferred embodiments, model parameters can be adjusted when the model performance falls below a preset performance threshold. For example, in decision tree models, overfitting is avoided through pruning operations; for neural network models, this is achieved by adjusting the network structure (e.g., increasing or decreasing the number of hidden layers or neurons) and optimizing training parameters (e.g., learning rate, number of iterations).

[0088] In this embodiment of the invention, the causal path between the historical deviation set and the actual execution result is measured by four dimensions: time causal weight, schedule causal weight, quality causal weight, and interruption causal weight.

[0089] As a preferred implementation, step S4, based on the expected execution impact and with the goal of timely completion of the current work order, involves reallocating resources to the equipment involved in the current work order, including: Based on the expected impact, filter the affected target devices from the current work order; The tools and resources required to acquire the target device; Based on the pre-built personnel skill profiles and the aforementioned tool resources, the human and material information in the current work order is adjusted with the goal of timely completion of the current work order.

[0090] Obtaining the necessary tools and resources is a prerequisite for material resource adjustments. The normal operation of equipment depends on the availability of supporting tools and resources (such as specific testing tools for equipment maintenance and consumables for equipment operation). If the required tools and resources are not clearly defined, there may be omissions in subsequent material resource adjustments, resulting in the equipment still being unable to support the timely execution of work orders.

[0091] It should be noted that the personnel skill profile is constructed based on the assessment results of maintenance personnel skills. Through the personnel skill profile, maintenance personnel with corresponding skills can be selected to form a special maintenance team according to the type of equipment failure and the difficulty of maintenance, so as to adjust the human resources information.

[0092] The above solution fundamentally solves the problem of work order failure caused by changes in resource demand through the coordination of equipment, personnel and materials. It also enables early warning and resource deployment, providing reliable resource guarantees for the timely execution and quality of current work orders.

[0093] The work order scheduling and management method provided in this invention captures the comprehensive deviation of execution variables in real time, accurately predicts the execution impact by combining a pre-trained work order execution impact model, and dynamically optimizes resource allocation. This enables real-time perception and intelligent adjustment of the work order execution process, effectively ensuring the timely completion of work orders, significantly improving scheduling efficiency and resource utilization, and reducing delays, resource waste, and quality risks caused by deviations not being fully captured or their transmission effects being ignored.

[0094] This invention provides a work order scheduling and management system. Please refer to [link / reference]. Figure 2 The work order scheduling management system includes an execution variable acquisition module 11, a deviation set generation module 12, an expected execution impact generation module 13, and a resource scheduling module 14, wherein: The execution variable acquisition module 11 is used to acquire the execution variables of the current work order in real time; the execution variables include task execution information, equipment status information, and resource usage information. The deviation set generation module 12 is used to compare the execution variable with a preset execution variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable propagation deviation value; The expected execution impact generation module 13 is used to input the current deviation set into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the execution of historical work orders; The resource scheduling module 14 is used to reallocate resources to the equipment involved in the current work order based on the expected execution impact and with the execution variable standard of the current work order as the target.

[0095] In a preferred embodiment, the execution variable acquisition module 11 is specifically used for: The planned start time, planned completion time, actual start time, and actual completion time of the subtasks in the current work order are obtained in real time and used as task execution information. Real-time acquisition of equipment failure frequency, duration, and severity during the execution of the current work order, as equipment status information; Real-time acquisition of manpower and material resources invested in the current work order, as resource usage information.

[0096] In a preferred embodiment, the deviation set generation module 12 includes: The variable self-deviation value calculation unit is used to obtain a preset execution variable standard, compare the execution variable with its corresponding execution variable standard, and calculate the variable self-deviation value of each execution variable; The intervariate transmission deviation calculation unit is used to calculate the intervariate transmission deviation value of each executed variable affected by other executed variables based on the influence transmission relationship between executed variables and the variable's own deviation value; The current deviation set integration unit is used to obtain the current deviation set of each execution variable based on the variable's own deviation value and the cross-variable transmission deviation value.

[0097] Further, preferably, the intervariate transmission deviation value calculation unit is specifically used for: Select the first execution variable from all execution variables; If the deviation value of the first executed variable is greater than a preset first deviation value threshold, the influence transmission relationship between the first executed variable and the second executed variable is obtained; the second executed variable is any executed variable other than the first executed variable. Based on the influence transmission relationship and the variable's own deviation value of the first execution variable, the expected value of the second execution variable is obtained; Calculate the difference between the expected value and the standard of the execution variable in the corresponding stage. If the difference is greater than the preset second deviation threshold, the difference is used as the intervariate transmission deviation value of the second execution variable.

[0098] In a preferred embodiment, the expected execution effect generation module 13 is specifically used for: Based on the current deviation set, we obtain the current task execution deviation set, the current device status deviation set, and the current resource usage deviation set; The current task execution deviation set, the current equipment status deviation set, and the current resource usage deviation set are input into the pre-trained work order execution impact model, so that the current deviation set is matched with the historical deviation set through the work order execution impact model to obtain the expected execution result of the current work order; The expected impact of the current work order is obtained based on the deviation between the expected execution result and the planned execution result.

[0099] Further, preferably, the expected execution impact includes time impact, schedule impact, quality impact, and interruption; Among them, time impact refers to the deviation between the expected completion time and the planned completion time of the current work order; schedule impact refers to the deviation between the expected completion schedule of each subtask in the current work order and the preset schedule node; quality impact refers to the deviation between the expected execution quality of the current work order and the preset quality standard; and interruption status refers to the reason for interruption and the duration of interruption during the execution of the current work order.

[0100] As a preferred embodiment, the training method for the work order execution impact model includes: Obtain historical execution variables and actual execution results during the execution of historical work orders; The historical execution variables are compared with preset execution variable standards to obtain the historical deviation set of each historical execution variable; Based on the historical deviation set and the actual execution results, training samples are constructed; The work order execution impact model is trained using the training samples to screen key influencing factors of historical execution variables from the historical deviation set and learn the mapping relationship between the key influencing factors and the actual execution results.

[0101] Further, preferably, the step of constructing training samples based on the historical deviation set and the actual execution results includes: Based on the historical deviation set, the deviation labels of each historical execution variable at each execution stage are obtained; Based on the actual execution results, the completion time label, completion progress label, execution quality label, and interruption status label of the historical work order at each execution stage are obtained as execution result labels; Training samples are constructed based on the deviation label and the execution result label.

[0102] Preferably, the step of training the work order execution impact model using the training samples, so as to screen key influencing factors of historical execution variables from the historical deviation set through the work order execution impact model, and learn the mapping relationship between the key influencing factors and the actual execution results, includes: The training samples are divided into a training set and a test set according to a preset ratio; The work order execution impact model is trained using the training set to screen key influencing factors of historical execution variables from the historical deviation set, and to calculate the causal weights between the key influencing factors and the actual execution results; the causal weights include time causal weights, schedule causal weights, quality causal weights, and interruption causal weights. The trained work order execution impact model is tested using the test set to obtain model performance. If the model performance is lower than a preset performance threshold, the causal weights are adjusted based on the performance.

[0103] In a preferred embodiment, the resource scheduling module 14 is specifically used for: Based on the expected impact, filter the affected target devices from the current work order; The tools and resources required to acquire the target device; Based on the pre-built personnel skill profiles and the aforementioned tool resources, and with the execution variable standards of the current work order as the target, the human and material information in the current work order is adjusted.

[0104] The work order scheduling and management system provided in this invention captures the comprehensive deviations of execution variables in real time, accurately predicts the execution impact by combining a pre-trained work order execution impact model, and dynamically optimizes resource allocation. This enables real-time perception and intelligent adjustment of the work order execution process, effectively ensuring the timely completion of work orders, significantly improving scheduling efficiency and resource utilization, and reducing delays, resource waste, and quality risks caused by deviations not being fully captured or their transmission effects being ignored.

[0105] Please see Figure 3 , Figure 3 This is a structural block diagram of a work order scheduling and management device provided in an embodiment of the present invention. The work order scheduling and management device includes a processor 31, a memory 32, and a computer program stored in the memory 32 and executable on the processor 31. When the processor 31 executes the computer program, it implements the steps in the above-described embodiments of the work order scheduling and management methods, such as steps S1 to S4.

[0106] For example, the computer program can be divided into one or more modules / units, which are stored in the memory 32 and executed by the processor 31 to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the work order scheduling and management device.

[0107] The work order scheduling and management device may include, but is not limited to, a processor 31 and a memory 32. Those skilled in the art will understand that the schematic diagram is merely an example of a work order scheduling and management device and does not constitute a limitation on the device. It may include more or fewer components than illustrated, or combine certain components, or use different components. For example, the work order scheduling and management device may also include input / output devices, network access devices, buses, etc.

[0108] The processor 31 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor 31 is the control center of the work order scheduling management equipment, connecting all parts of the equipment via various interfaces and lines.

[0109] The memory 32 can be used to store the computer program and / or modules. The processor 31 implements various functions of the work order scheduling and management device by running or executing the computer program and / or modules stored in the memory 32 and calling the data stored in the memory 32. The memory 32 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 32 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0110] If the modules / units integrated into the work order scheduling and management equipment are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 31, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0111] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A work order scheduling and management method, characterized in that, include: The execution variables of the current work order are obtained in real time; the execution variables include task execution information, equipment status information, and resource usage information. The executed variable is compared with a preset executed variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable transmission deviation value; The current deviation set is input into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the historical work order execution process. Based on the expected execution impact, and taking the execution variable standard of the current work order as the target, the equipment involved in the current work order is reallocated resources.

2. The work order scheduling and management method as described in claim 1, characterized in that, The real-time acquisition of execution variables for the current work order includes: The planned start time, planned completion time, actual start time, and actual completion time of the subtasks in the current work order are obtained in real time and used as task execution information. Real-time acquisition of equipment failure frequency, duration, and severity during the execution of the current work order, as equipment status information; Real-time acquisition of manpower and material resources invested in the current work order, as resource usage information.

3. The work order scheduling and management method as described in claim 1, characterized in that, The step of comparing the execution variable with a preset execution variable standard to obtain the current deviation set includes: Obtain a preset execution variable standard, compare the execution variable with its corresponding execution variable standard, and calculate the variable deviation value of each execution variable; Based on the influence transmission relationship between the executed variables and the variable's own deviation value, calculate the cross-variable transmission deviation value of each executed variable affected by other executed variables; Based on the variable's own deviation value and the intervariate transmission deviation value, the current deviation set of each execution variable is obtained.

4. The work order scheduling and management method as described in claim 3, characterized in that, The step of calculating the intervariate transmission deviation value of each executed variable under the influence of other executed variables based on the influence transmission relationship between executed variables and the variable's own deviation value includes: Select the first execution variable from all execution variables; If the deviation value of the first executed variable is greater than a preset first deviation value threshold, the influence transmission relationship between the first executed variable and the second executed variable is obtained; the second executed variable is any executed variable other than the first executed variable. Based on the influence transmission relationship and the variable's own deviation value of the first execution variable, the expected value of the second execution variable is obtained; Calculate the difference between the expected value and the standard of the execution variable in the corresponding stage. If the difference is greater than the preset second deviation threshold, the difference is used as the intervariate transmission deviation value of the second execution variable.

5. The work order scheduling and management method as described in claim 1, characterized in that, The step of inputting the current deviation set into the pre-trained work order execution impact model to obtain the expected execution impact of the current work order includes: Based on the current deviation set, we obtain the current task execution deviation set, the current device status deviation set, and the current resource usage deviation set; The current task execution deviation set, the current equipment status deviation set, and the current resource usage deviation set are input into the pre-trained work order execution impact model, so that the current deviation set is matched with the historical deviation set through the work order execution impact model to obtain the expected execution result of the current work order; The expected impact of the current work order is obtained based on the deviation between the expected execution result and the planned execution result.

6. A work order scheduling and management method as described in claim 1 or 5, characterized in that, The anticipated impacts on execution include time impacts, schedule impacts, quality impacts, and disruptions. Among them, time impact refers to the deviation between the expected completion time and the planned completion time of the current work order; schedule impact refers to the deviation between the expected completion schedule of each subtask in the current work order and the preset schedule node; quality impact refers to the deviation between the expected execution quality of the current work order and the preset quality standard; and interruption status refers to the reason for interruption and the duration of interruption during the execution of the current work order.

7. The work order scheduling and management method as described in claim 1, characterized in that, The training method for the work order execution impact model includes: Obtain historical execution variables and actual execution results during the execution of historical work orders; The historical execution variables are compared with preset execution variable standards to obtain the historical deviation set of each historical execution variable; Based on the historical deviation set and the actual execution results, training samples are constructed; The work order execution impact model is trained using the training samples to screen key influencing factors of historical execution variables from the historical deviation set and learn the mapping relationship between the key influencing factors and the actual execution results.

8. The work order scheduling and management method as described in claim 7, characterized in that, The step of constructing training samples based on the historical deviation set and the actual execution results includes: Based on the historical deviation set, the deviation labels of each historical execution variable at each execution stage are obtained; Based on the actual execution results, the completion time label, completion progress label, execution quality label, and interruption status label of the historical work order at each execution stage are obtained as execution result labels; Training samples are constructed based on the deviation label and the execution result label.

9. The work order scheduling and management method as described in claim 7, characterized in that, The step of training the work order execution impact model using the training samples, and then using the work order execution impact model to screen key influencing factors of historical execution variables from the historical deviation set, and learning the mapping relationship between the key influencing factors and the actual execution results, includes: The training samples are divided into a training set and a test set according to a preset ratio; The work order execution impact model is trained using the training set to screen key influencing factors of historical execution variables from the historical deviation set, and to calculate the causal weights between the key influencing factors and the actual execution results; the causal weights include time causal weights, schedule causal weights, quality causal weights, and interruption causal weights. The trained work order execution impact model is tested using the test set to obtain model performance. If the model performance is lower than a preset performance threshold, the causal weights are adjusted based on the performance.

10. The work order scheduling and management method as described in claim 1, characterized in that, The step of reallocating resources to the equipment involved in the current work order based on the expected execution impact and targeting the execution variable standards of the current work order includes: Based on the expected impact, filter the affected target devices from the current work order; The tools and resources required to acquire the target device; Based on the pre-built personnel skill profiles and the aforementioned tool resources, and with the execution variable standards of the current work order as the target, the human and material information in the current work order is adjusted.

11. A work order scheduling and management system, characterized in that, include: The execution variable acquisition module is used to acquire the execution variables of the current work order in real time; the execution variables include task execution information, equipment status information, and resource usage information. The deviation set generation module is used to compare the executed variable with a preset executed variable standard to obtain the current deviation set; the current deviation set includes the variable's own deviation value and the cross-variable propagation deviation value; The expected execution impact generation module is used to input the current deviation set into a pre-trained work order execution impact model to obtain the expected execution impact of the current work order; the work order execution impact model is trained based on historical execution variables and actual execution results during the execution of historical work orders; The resource scheduling module is used to reallocate resources to the equipment involved in the current work order based on the expected execution impact and with the execution variable standard of the current work order as the target.

12. A work order scheduling and management device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the work order scheduling management method as described in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the work order scheduling management method as described in any one of claims 1 to 10.

14. A computer program product, characterized in that, The computer program product includes a computer program or computer instructions, which, when executed by a processor, perform the work order scheduling management method as described in any one of claims 1 to 10.

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