Life tree task management system based on full life cycle of civil aviation project

Abstract

The invention is suitable for the technical field of civil aviation project management and intelligent scheduling control, and provides a civil aviation project full life cycle-based life tree task management system, which comprises a data acquisition module, a first adjustment factor determination module, a second adjustment factor determination module and a priority value correction module. According to the method, the first execution priority adjustment factor and the second execution priority adjustment factor are introduced, the initial execution priority value of the equipment debugging task is dynamically corrected, and a scheduling optimization mechanism giving consideration to the task execution state and the team cooperation trend is constructed. According to the mechanism, fatigue fluctuation and cooperative structure change generated in long-period task execution of a team can be accurately identified, the situation that high-priority tasks are continuously allocated to a high-load team is avoided, and the risks of execution quality fluctuation and resource imbalance caused by unreasonable task arrangement are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of civil aviation project management and intelligent dispatching control, and particularly relates to a life tree task management system based on the whole life cycle of civil aviation projects. Background Art

[0002] In the process of civil aviation project management, the equipment commissioning task is a key link to ensure the improvement of system functions, operation safety and project progress. Its scheduling management is directly related to the overall quality and efficiency of project execution. When facing a large number of tasks to be commissioned, the existing life tree task management systems usually generate task priorities based on static rules such as task type, preset urgency level or equipment importance level, and schedule and sort tasks accordingly. However, this type of method fails to fully consider the dynamic changes in the team state during the execution of commissioning tasks, especially ignores the problems of insufficient scheduling adaptability brought about by factors such as fatigue accumulation, uneven task load and alienation of cooperation structure under long-term execution.

[0003] Specifically, in the scheduling process of commissioning tasks, the existing technology lacks a comprehensive evaluation mechanism based on historical execution status and team cooperation trend, which is likely to cause some teams to be overloaded due to continuously undertaking high-priority tasks, thus affecting task quality, execution efficiency and even the overall rhythm of the project. In addition, the traditional method also lacks the ability to explore the evolution law of team execution ability, and it is difficult to dynamically identify the state differences shown by the team at different stages, resulting in the task allocation being formally reasonable but deviating from the actual execution ability in terms of timeliness. Summary of the Invention

[0004] The purpose of the present invention is to provide a life tree task management system based on the whole life cycle of civil aviation projects, aiming to solve the problems raised in the background art.

[0005] The present invention is implemented as follows. A life tree task management system based on the whole life cycle of civil aviation projects, the system includes: a data acquisition module, a first adjustment factor determination module, a second adjustment factor determination module, and a priority value correction module, wherein:

[0006] The data acquisition module is used to determine the specified type of the to-be-allocated device commissioning task after generating an initial execution priority value for the to-be-allocated device commissioning task of the target team for the target device, and obtain the historical operation record of the target team for the target device;

[0007] The first adjustment factor determination module is used to screen out historical device commissioning tasks consistent with the specified type from the historical operation records, determine the team state parameter values after the completion of the historical device commissioning tasks, analyze the deviation degree between the average value of several team state parameter values and the preset standard state parameter values, and determine the first execution priority adjustment factor accordingly;

[0008] A second adjustment factor determination module, configured to screen out a number of specific historical device debugging tasks with the proportion of the task load dominated by a small number of members greater than a preset threshold from a number of historical device debugging tasks, determine the trend of the proportion of the task load dominated by a small number of members in the number of specific historical device debugging tasks changing over time, and accordingly determine a second execution priority adjustment factor;

[0009] A priority value correction module, configured to correct the initial execution priority value by combining the first execution priority adjustment factor and the second execution priority adjustment factor.

[0010] As a further limitation of the technical solution of the embodiment of the present invention, the team state parameter value refers to a comprehensive index reflecting the overall fatigue state of the team after task execution, including weighted values of dimensions such as task execution duration, response delay, post-task operation error rate, and member collaboration efficiency.

[0011] As a further limitation of the technical solution of the embodiment of the present invention, the first adjustment factor determination module specifically includes:

[0012] A team state parameter value determination unit, configured to parse historical operation records, screen out a number of historical device debugging tasks consistent with a specified type therefrom, and at the same time determine the team state parameter value of the target team after completing each historical device debugging task based on the historical operation records;

[0013] An average value calculation unit, configured to determine a preset standard state parameter value corresponding to the device debugging task of the specified type completed by the target team, and calculate the average value of a number of team state parameter values;

[0014] A deviation degree quantification unit, configured to quantify the deviation degree between the average value and the preset standard state parameter value, and use the deviation degree as the basis for the first execution priority adjustment factor.

[0015] As a further limitation of the technical solution of the embodiment of the present invention, the "dominated by a small number of members" means that during the execution of the device debugging task, the number of members actually completing the task operation is lower than the first preset proportion threshold of the total number of team members, and the task operation amount undertaken by the small number of members exceeds the second preset proportion threshold of the total task amount.

[0016] As a further limitation of the technical solution of the embodiment of the present invention, the second adjustment factor determination module specifically includes:

[0017] A load ratio calculation unit, configured to calculate, based on historical operation records, the load ratio of the task amount completed by a small number of members to the total task amount of each historical device debugging task after completion;

[0018] An evolution curve plotting unit is configured to screen out a number of specific historical equipment debugging tasks from a number of historical equipment debugging tasks where the proportion of the task load dominated by a small number of members is greater than a preset threshold, and plot the proportion of the task load dominated by a small number of members of the specific tasks into an evolution curve in the order of the occurrence time of the tasks;

[0019] An average slope calculation unit is configured to calculate the average slope of the evolution curve and use the average slope as a second execution priority adjustment factor.

[0020] As a further limitation of the technical solution of the embodiment of the present invention, the priority value correction module specifically includes:

[0021] An initial priority value correction unit is configured to retrieve a preset execution priority value correction formula, and combine the first execution priority adjustment factor and the second execution priority adjustment factor to correct the initial execution priority value to obtain an optimized execution priority value;

[0022] An optimized priority value application unit is configured to apply the optimized execution priority value to the scheduling sorting and resource allocation strategy of the equipment debugging tasks of the target team for the target equipment, and determine the final issuance order and the corresponding scheduling execution window of the equipment debugging tasks of the target equipment.

[0023] As a further limitation of the technical solution of the embodiment of the present invention, the execution priority value correction formula is: ;

[0024] Where refers to the optimized execution priority value, refers to the initial execution priority value, refers to the average value of a number of team status parameter values, refers to a preset standard status parameter value, refers to the first execution priority adjustment factor, that is, the deviation degree between the average value of a number of team status parameter values and the preset standard status parameter value, refers to the adjustment weight coefficient corresponding to the first execution priority adjustment factor, refers to the second execution priority adjustment factor, that is, the average slope of the evolution curve, refers to the adjustment weight coefficient corresponding to the second execution priority adjustment factor.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The present invention constructs a scheduling optimization mechanism that takes into account both the task execution status and the team collaboration trend by introducing a first execution priority adjustment factor and a second execution priority adjustment factor to dynamically correct the initial execution priority value of device debugging tasks. This mechanism can accurately identify the fatigue fluctuations and collaboration structure changes generated by the team during the execution of long-term tasks, avoid continuously assigning high-priority tasks to high-load teams, and reduce the risks of execution quality fluctuations and resource imbalance caused by unreasonable task arrangements. Compared with the traditional scheduling method that only relies on static rules, the present invention introduces historical status data and load trend analysis in the priority sorting, improving the judgment accuracy of the system for the actual execution ability and realizing the dynamic adaptability and stability control of the scheduling strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is an application architecture diagram of the system provided by an embodiment of the present invention;

[0028] Figure 2 It is a structural block diagram of the first adjustment factor determination module in the system provided by an embodiment of the present invention;

[0029] Figure 3 It is a structural block diagram of the second adjustment factor determination module in the system provided by an embodiment of the present invention;

[0030] Figure 4 It is a structural block diagram of the priority value correction module in the system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] Furthermore, Figure 1 It shows the application architecture diagram of the system provided by an embodiment of the present invention.

[0033] Among them, in another preferred embodiment provided by the present invention, a life tree task management system based on the entire life cycle of a civil aviation project includes:

[0034] A data acquisition module 100, which is used to determine the specified type of the to-be-allocated debugging task after generating an initial execution priority value for the to-be-allocated device debugging task of the target team for the target device, and acquire the historical operation records of the target team for the target device.

[0035] In the embodiments of the present invention, the target team refers to the group of personnel assigned or pre-assigned to perform specific equipment commissioning tasks in a civil aviation project. This team is usually composed of technicians with equipment commissioning qualifications, experience, and the ability to cooperate and coordinate, and is the direct executor of the equipment commissioning tasks. The target equipment refers to the specific equipment associated with the equipment commissioning tasks to be assigned. This equipment needs to be commissioned during the implementation of the civil aviation project. The target equipment can include key equipment in various civil aviation projects such as flight control equipment, communication and navigation equipment, power system equipment, and environmental control system equipment.

[0036] The equipment commissioning tasks to be assigned refer to the commissioning-type operation tasks for the target equipment that have not been officially issued or actually executed. This task usually includes content such as commissioning objectives, commissioning scope, commissioning steps, and commissioning completion standards, and is the specific work unit that the task scheduling system is prepared to deliver to the target team for execution.

[0037] The initial execution priority value refers to the original priority weight value generated for the equipment commissioning tasks to be assigned based on the task sorting rules or priority evaluation model set in the scheduling system during the task scheduling stage. This value is used to reflect the default execution urgency or priority level of this task within the current scheduling cycle. The generation of this initial execution priority value belongs to the category of existing technologies and is usually calculated through a priority scoring model or rule engine based on factors such as the technical difficulty of the task, the system importance of the associated equipment, project progress requirements, dependencies of previous tasks, and resource occupancy.

[0038] The specified type refers to the pre-classification of the equipment commissioning tasks to be assigned according to the technical characteristics of the task itself, the type of target equipment, the category of operation procedures, or the historical task classification system. The determination of this type is usually achieved through standard template settings at the time of task creation, manual classification and annotation, or an automatic classification algorithm based on task attribute tags, and is used to screen historical equipment commissioning tasks of the same type for feature comparison in the future.

[0039] The historical operation records of the target team for the target equipment can be obtained through the task execution log module integrated in the project management system or the scheduling execution system. This record is usually automatically generated and archived by the system, and the record content covers the execution process and results of the equipment commissioning tasks. The historical operation records should at least include the following information: task execution time period, composition of task execution members, detailed data on the amount of tasks completed by each member, execution results of the equipment commissioning tasks, operating status information of the equipment after commissioning, key operation steps and their time points during the task execution process, task exception information recorded by the system or personnel, etc.

[0040] Furthermore, the life tree task management system based on the entire life cycle of the civil aviation project further includes:

[0041] The first adjustment factor determination module 200 is configured to screen out historical device debugging tasks that are consistent with the specified type from historical operation records, determine the value of the team status parameter after the completion of the historical device debugging tasks, analyze the deviation degree between the average value of several team status parameter values and the preset standard status parameter value, and determine the first execution priority adjustment factor accordingly.

[0042] The team status parameter value refers to a comprehensive index reflecting the overall fatigue state of the team after task execution, including the weighted values of dimensions such as task execution duration, response delay, post-task operation error rate, and member collaboration efficiency.

[0043] Specifically, Figure 2 Fig. shows the structural block diagram of the first adjustment factor determination module 200 in the system provided by the embodiment of the present invention.

[0044] Among them, in the preferred embodiment provided by the present invention, the first adjustment factor determination module 200 specifically includes:

[0045] The team status parameter value determination unit 201 is configured to parse the historical operation records, screen out several historical device debugging tasks that are consistent with the specified type therefrom, and determine the team status parameter value of the target team after completing each historical device debugging task based on the historical operation records;

[0046] The average value calculation unit 202 is configured to determine the preset standard status parameter value corresponding to the device debugging task of the specified type for the target team, and calculate the average value of several team status parameter values;

[0047] The deviation degree quantification unit 203 is configured to quantify the deviation degree between the average value and the preset standard status parameter value, and use the deviation degree as the basis for the first execution priority adjustment factor.

[0048] In the embodiment of the present invention, the team status parameter value is a comprehensive numerical index obtained by multi-dimensional evaluation of the execution status shown by the target team after completing the device debugging task, and is used to reflect the overall fatigue degree and collaboration load of the team after task completion. The team status parameter value has applicability in the prior art. In existing fields such as enterprise management systems, human factors engineering evaluation systems, and job safety monitoring systems, there are already methods for quantifying and scoring indicators such as task duration, operation error rate, and response efficiency to evaluate the team status. Therefore, the present invention can be implemented on the basis of the prior art in terms of acquisition method and quantification logic, and has engineering implementation feasibility.

[0049] Specifically, based on historical operation records, determine the team status parameter values of the target team after completing each historical equipment debugging task. This is mainly achieved by extracting basic information such as the task execution log, member division of labor record, task completion time period, and task quality data corresponding to the task, and combining with a preset weighted calculation model. Convert multiple data such as task execution duration, member response delay, frequency of equipment anomalies after the task, and task collaboration distribution among members into standardized scoring indicators, and then calculate a status parameter value corresponding to the completion of this task through the set weighted rules, which is used to reflect the overall status performance of the team during the execution of this task.

[0050] Calculate the average value of several team status parameter values, aiming to evaluate the overall performance trend of the target team when performing equipment debugging tasks of the same type through statistical analysis. This average value can effectively reduce the accidental impact of individual task execution status, improve the stability and representativeness of the evaluation indicators, and provide a more universal basis for subsequent priority correction.

[0051] The preset standard status parameter value is used as a reference benchmark to measure whether the status of the target team after completing the equipment debugging task is within a reasonable range. Its setting basis is the average status parameter level shown by equipment debugging tasks of the same type under the conditions of the early stage of the project, good personnel status, and stable task execution. This reference value can be obtained by selecting typical sample tasks with good status performance, qualified execution quality, and balanced collaboration in multiple historical tasks as the benchmark task set, and calculating the average value of the status parameter values after completion, excluding outliers. This value reflects the system's recognition standard for the ideal task execution status, can be used as a baseline parameter in team status deviation analysis, and has objectivity and engineering reference. In practical applications, this value can be dynamically adjusted and optimized according to different task types, team sizes, and work cycles.

[0052] Quantify the deviation degree between the average value and the preset standard status parameter value to clarify the difference degree between the current overall status of the team and the ideal execution status set by the system, and form a first execution priority adjustment factor based on this. When the deviation degree is large, it indicates that the target team has shown a strong fatigue trend or a decline in collaboration efficiency under the current task load, and the system should appropriately reduce the execution priority of the new tasks it is about to receive to ensure team load balance and task quality stability; when the deviation degree is small, it means that the team is in good condition and can undertake more key tasks, so the system can correspondingly increase its priority. This adjustment mechanism helps the system achieve a dynamic and highly adaptable task sorting strategy, improving scheduling rationality and the practical feasibility of task execution.

[0053] Furthermore, the life tree task management system based on the entire life cycle of the civil aviation project further includes:

[0054] The second adjustment factor determination module 300 is configured to screen out a number of specific historical device debugging tasks with the proportion of the task load dominated by a small number of members being greater than a preset threshold from a number of historical device debugging tasks, determine the trend of the proportion of the task load dominated by a small number of members in the number of specific historical device debugging tasks changing over time, and accordingly determine the second execution priority adjustment factor.

[0055] The "dominated by a small number of members" means that during the execution of a device debugging task, the number of members actually completing the task operations is lower than the first preset proportional threshold of the total number of team members, and the task operation amount borne by these few members exceeds the second preset proportional threshold of the total task amount.

[0056] Specifically, Figure 3 Fig. shows the structural block diagram of the second adjustment factor determination module 300 in the system provided by the embodiment of the present invention.

[0057] Among them, in the preferred embodiment provided by the present invention, the second adjustment factor determination module 300 specifically includes:

[0058] The load ratio calculation unit 301 is configured to calculate, based on historical operation records, the load ratio of the task amount completed by a small number of members to the total task amount of each historical device debugging task after completion;

[0059] The evolution curve drawing unit 302 is configured to screen out a number of specific historical device debugging tasks with the proportion of the task load dominated by a small number of members being greater than a preset threshold from a number of historical device debugging tasks, and draw an evolution curve of the proportion of the task load dominated by a small number of members in the specific tasks in the order of the occurrence time of the tasks;

[0060] The average slope calculation unit 303 is configured to calculate the average slope of the evolution curve and use the average slope as the second execution priority adjustment factor.

[0061] In the embodiment of the present invention, the situation of the task dominated by a small number of members usually reflects that during the actual execution of some device debugging tasks, only a small number of members in the team undertake most of the core operations or main workload. This phenomenon may be due to factors such as uneven personnel allocation, differences in the operation capabilities of some members, the failure of the scheduling system to reasonably allocate tasks, or the long-term formed fixed cooperation mode. The phenomenon of being dominated by a small number of members may improve short-term efficiency on the one hand, but may cause problems such as excessive fatigue of local members, decline in team cooperation ability, and instability of the quality of subsequent tasks in the long term. Therefore, the identification and analysis of this type of phenomenon help to reveal the structural problems in the team execution mode and provide a warning basis for scheduling optimization, which has important management value and system intelligent adjustment significance.

[0062] The first preset threshold is a standard value used to determine whether "the number of members actually completing the task operations is too small", usually set as a certain percentage of the total number of team members, such as less than 50%; the second preset threshold is a standard value used to determine whether "the task operation volume undertaken by these few members is too heavy", usually set as a certain percentage of the total task operation volume, such as more than 70%. The setting of these two thresholds can be adjusted according to the actual team structure, task complexity, and past statistical data experience to ensure that the identified tasks dominated by a small number of members are representative and deviated, facilitating subsequent trend analysis and priority correction.

[0063] During the implementation process, based on historical operation records, the system first analyzes the execution logs of each device debugging task and counts the subtask volume or operation steps completed by each member in the task operation records; then, according to the number of members and the total task volume, calculates the concentration degree of the task volume distribution among the actually participating members; if the conditions that the number of members is lower than the first preset ratio and the task volume ratio is higher than the second preset ratio are met, then it can be determined that this task is completed mainly by a small number of members. On this basis, calculate the ratio of the task volume of the leading members to the total task volume, which is the proportion of the task load dominated by a small number of members for this task.

[0064] Selecting specific historical device debugging tasks with the proportion of the task load dominated by a small number of members greater than the preset threshold is to find task instances with prominent leading characteristics as trend analysis samples. Through the statistical changes of these samples, it can be revealed whether there are obvious changes in the collaboration mode of the team in different time periods and different types of tasks, and then judge whether there is a tendency for the team structure to gradually solidify into being dominated by a small number of people.

[0065] The average slope of the evolution curve is a metric for measuring the trend of the proportion of the task load dominated by a small number of members changing over time, which can quantify the evolution direction and speed of the team collaboration structure. If the average slope is positive, it indicates that the phenomenon of being dominated by a small number of members is gradually intensifying; if it is negative, it means that the team collaboration tends to be balanced. Using this average slope as the second execution priority adjustment factor, it is possible to dynamically correct the task priority based on the change trend of the team collaboration structure. When the system detects that there is a long-term trend of uneven collaboration in the team, it can appropriately lower the execution priority of the subsequent tasks of this team to promote the adjustment of the collaboration mode and improve the sustainability of the team operation and the balance of task quality.

[0066] Furthermore, the life tree task management system based on the entire life cycle of civil aviation projects further includes:

[0067] A priority value correction module 400, which is used to correct the initial execution priority value by combining the first execution priority adjustment factor and the second execution priority adjustment factor.

[0068] Specifically, Figure 4The structural block diagram of the priority value correction module 400 in the system provided by the embodiments of the present invention is shown.

[0069] Among them, in the preferred embodiment provided by the present invention, the priority value correction module 400 specifically includes:

[0070] The initial priority value correction unit 401 is used to retrieve a preset execution priority value correction formula, and in combination with a first execution priority adjustment factor and a second execution priority adjustment factor, correct the initial execution priority value to obtain an optimized execution priority value;

[0071] The optimized priority value application unit 402 is used to apply the optimized execution priority value to the scheduling sorting and resource allocation strategy of the device debugging task of the target team for the target device, and is used to determine the final issuance order of the device debugging task of the target device and the corresponding scheduling execution window.

[0072] The execution priority value correction formula is: ;

[0073] Where refers to the optimized execution priority value, refers to the initial execution priority value, refers to the average value of several team status parameter values, refers to the preset standard status parameter value, refers to the first execution priority adjustment factor, that is, the deviation degree between the average value of several team status parameter values and the preset standard status parameter value, refers to the adjustment weight coefficient corresponding to the first execution priority adjustment factor, refers to the second execution priority adjustment factor, that is, the average slope of the evolution curve, refers to the adjustment weight coefficient corresponding to the second execution priority adjustment factor.

[0074] In the embodiments of the present invention, the priority value correction module corrects the initial execution priority value by combining the first execution priority adjustment factor and the second execution priority adjustment factor, aiming to establish a more dynamically adaptable task sorting mechanism to improve the scheduling accuracy of device debugging tasks in the context of multiple teams and multiple cycles. The first execution priority adjustment factor reflects the overall state performance of the target team after completing the same type of device debugging tasks, and mainly focuses on the fatigue degree and operation stability of the team during the long-term task execution process; the second execution priority adjustment factor focuses on the change trend of the collaboration structure of the target team, especially whether there is a tendency for a small number of members to continuously bear a high proportion of task loads.

[0075] Between the two, there are two dimensions for the system to evaluate the team's execution ability: one is the immediate execution ability evaluation centered on the "post-completion state", and the other is the structural risk evaluation centered on the "evolution of task collaboration mode". If the priority is corrected based on only a single factor, it may lead to the system's over-response to local performance or the neglect of structural trends. Therefore, the present invention fuses the two factors by setting weight coefficients, so as to take into account the team's current state and long-term performance trend in task scheduling, and achieve the comprehensiveness and accuracy of priority adjustment.

[0076] For example, in a certain scheduling cycle, the system needs to assign a debugging task of a communication navigation device to a target team. The task was given an original priority value of 0.85 in the initial evaluation. After the system retrieves the historical operation records, through the first adjustment factor determination module analysis, it is found that the average state parameter value of the team after completing similar tasks recently is 72, and the preset standard state parameter value set by the system for this type of task is 60, with an obvious deviation in the state. At this time, the first adjustment weight coefficient set by the system is 0.3. On the other hand, the system further identifies through the second adjustment factor determination module that there is an obvious upward trend in the proportion of tasks dominated by fewer members in the team, and the average slope of the evolution curve is 0.05, corresponding to the second adjustment weight coefficient of 0.4. Based on these two deviation values, the system calculates the comprehensive correction result and reduces the original priority value from 0.85 to 0.72.

[0077] Subsequently, the priority value correction module submits the corrected priority value to the task scheduling engine. The system automatically sorts all the pending device debugging tasks according to the optimized priority value, and combines the on-site resource availability and task window limitations to determine the final issuance order and precise scheduling execution period of the communication navigation device debugging task. Through this mechanism, the system not only ensures the scheduling efficiency, but also effectively avoids unreasonable scheduling arrangements for high-load teams, which helps to improve the stability of the overall engineering task execution and the quality control ability.

[0078] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0079] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above-described embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0080] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0081] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention should be subject to the appended claims.

[0082] The above is only the preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A life tree task management system based on the full life cycle of civil aviation projects, characterized in that The system includes: a data acquisition module, a first adjustment factor determination module, a second adjustment factor determination module, and a priority value correction module, where: The data acquisition module is configured to determine the specified type of the to-be-assigned debugging task and obtain the historical operation record of the target team for the target device after generating an initial execution priority value for the to-be-assigned device debugging task of the target team for the target device; The first adjustment factor determination module is configured to screen out historical device debugging tasks consistent with the specified type from the historical operation record, determine the team status parameter value after the completion of the historical device debugging task, analyze the deviation degree between the average value of several team status parameter values and the preset standard status parameter value, and determine the first execution priority adjustment factor accordingly; The second adjustment factor determination module is configured to screen out several specific historical device debugging tasks with the load ratio of tasks dominated by a small number of members greater than a preset threshold from several historical device debugging tasks, determine the trend of the load ratio of tasks dominated by a small number of members in several specific historical device debugging tasks changing over time, and determine the second execution priority adjustment factor accordingly; The priority value correction module is configured to correct the initial execution priority value by combining the first execution priority adjustment factor and the second execution priority adjustment factor.

2. The life tree task management system based on the full life cycle of civil aviation projects according to claim 1, characterized in that, The team status parameter value refers to a comprehensive index reflecting the overall fatigue state of the team after task execution, including the weighted values of dimensions such as task execution duration, response delay, post-task operation error rate, and member collaboration efficiency.

3. The life tree task management system based on the full life cycle of civil aviation projects according to claim 2, wherein The first adjustment factor determination module specifically includes: The team status parameter value determination unit is configured to parse the historical operation record, screen out several historical device debugging tasks consistent with the specified type therefrom, and determine the team status parameter value of the target team after the completion of each historical device debugging task based on the historical operation record; The average value calculation unit is configured to determine the preset standard status parameter value corresponding to the device debugging task of the specified type for the target team and calculate the average value of several team status parameter values; The deviation degree quantification unit is configured to quantify the deviation degree between the average value and the preset standard status parameter value, and use this deviation degree as the basis for the first execution priority adjustment factor.

4. The life tree task management system based on the whole life cycle of civil aviation projects according to claim 1, wherein, The "dominated by a small number of members" means that during the execution of the device debugging task, the number of members actually completing the task operation is lower than the first preset proportion threshold of the total number of team members, and the task operation volume undertaken by these few members exceeds the second preset proportion threshold of the total task volume.

5. The life tree task management system based on the whole life cycle of civil aviation projects according to claim 4, characterized in that, The second adjustment factor determination module specifically includes: The load ratio calculation unit is configured to calculate, based on the historical operation record, the load ratio of the task volume completed by a small number of members to the total task volume of each historical device debugging task after completion; The evolution curve drawing unit is configured to screen out several specific historical device debugging tasks with the load ratio of tasks dominated by a small number of members greater than a preset threshold from several historical device debugging tasks, and draw the evolution curve of the load ratio of tasks dominated by a small number of members of the specific tasks in chronological order of task occurrence; An average slope calculation unit is configured to calculate the average slope of the evolution curve and use the average slope as the second execution priority adjustment factor.

6. The life tree task management system based on the entire life cycle of civil aviation projects according to claim 5, characterized in that, Specifically, the priority value correction module includes: An initial priority value correction unit is configured to retrieve a preset execution priority value correction formula, and combine the first execution priority adjustment factor and the second execution priority adjustment factor to correct the initial execution priority value to obtain an optimized execution priority value; An optimized priority value application unit is configured to apply the optimized execution priority value to the scheduling sorting and resource allocation strategy of the equipment debugging tasks of the target team for the target equipment, and is used to determine the final issuance order of the equipment debugging tasks of the target equipment and the corresponding scheduling execution window.

7. The life tree task management system based on the full life cycle of civil aviation projects according to claim 6, characterized in that The execution priority value correction formula is as follows: ; Among them refers to the optimized execution priority value refers to the initial execution priority value refers to the average value of several team status parameter values refers to the preset standard status parameter value refers to the first execution priority adjustment factor, that is, the deviation degree between the average value of several team status parameter values and the preset standard status parameter value refers to the adjustment weight coefficient corresponding to the first execution priority adjustment factor refers to the second execution priority adjustment factor, that is, the average slope of the evolution curve refers to the adjustment weight coefficient corresponding to the second execution priority adjustment factor

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