Maintenance task scheduling method and device, equipment, storage medium and program product

Abstract

The invention discloses a maintenance task scheduling method and device, equipment, a storage medium and a program product, and belongs to the technical field of regular maintenance of airplanes. The method comprises the steps of generating a personnel portrait based on basic information, a qualification authorization state and historical task data of maintenance personnel; constructing a maintenance task model according to the lowest personnel demand, the qualification matching rule, the standard working hours and the parallel execution rule of the maintenance task; generating a scheduling constraint set based on a workshop section selection constraint, an employee uniqueness constraint, a task sequence dependency constraint and a working time interval constraint; constructing a target function according to the personnel portrait, the maintenance task model and the scheduling constraint set; calling a solver, performing task scheduling on the maintenance task by setting a weight combination of a target function, and generating a maintenance task scheduling scheme; and generating a visual scheduling plan based on task allocation and time sequence data in the maintenance task scheduling scheme. According to the embodiment of the invention, the scheduling efficiency and accuracy of the maintenance task can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft scheduled inspection and maintenance, and in particular to a maintenance task scheduling method and apparatus, equipment, storage medium, and program product. Background Art

[0002] Maintenance task scheduling refers to the allocation of maintenance tasks to available resources (such as personnel, equipment, etc.) under specific constraints in order to optimize certain goals (such as efficiency, cost, time, etc.). In the field of aircraft scheduled inspection and maintenance, the scheduling of maintenance tasks is a key link to ensure the airworthiness of aircraft and reduce downtime. Traditional scheduling methods rely on manual experience, with the Maintenance Control Center (MCC) manually assigning tasks based on work card lists, maintenance task packages, and personnel qualifications. This has problems with low scheduling efficiency and accuracy: manual scheduling needs to deal with multi-dimensional constraints (such as skill qualifications, task sequence, and working time restrictions). When faced with hundreds of tasks and dozens of maintenance personnel, it takes hours or even days to complete scheduling, which makes it difficult to meet the needs of rapid response and has low accuracy. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a maintenance task scheduling method and apparatus, equipment, storage medium and program product, which can effectively improve the scheduling efficiency and accuracy of maintenance tasks.

[0004] To achieve the above objectives, a first aspect of an embodiment of the present application provides a maintenance task scheduling method, comprising:

[0005] Generate personnel portraits based on maintenance personnel's basic information, qualification authorization status, and historical task data;

[0006] Construct a maintenance task model based on the minimum personnel requirements, qualification matching rules, standard working hours, and parallel execution rules of the maintenance task;

[0007] Generate a scheduling constraint set based on work section selection constraints, employee uniqueness constraints, task sequence dependency constraints, and work time interval constraints;

[0008] Constructing an objective function based on the personnel portrait, the maintenance task model, and the scheduling constraint set, wherein the objective function includes a total working time minimization item, a maintenance style score maximization item, and an experience matching maximization item;

[0009] Calling a solver to schedule the maintenance tasks by setting a weight combination of an objective function, and generating a maintenance task scheduling plan;

[0010] Based on the task allocation and time series data in the maintenance task scheduling solution, a visual scheduling plan is generated.

[0011] Compared with the prior art, the maintenance task scheduling method provided by the embodiment of the present application has the following beneficial effects: the present application constructs a multi-dimensional personnel portrait and a refined maintenance task model, combines multiple constraints such as work section selection, employee uniqueness and task sequence dependency, quantifies unstructured data such as maintenance style score and experience matching degree as the core optimization items of the objective function, and generates a maintenance task scheduling plan based on a dynamic weight combination call solver, thereby realizing full-process automated scheduling of scheduled maintenance tasks, effectively solving the technical problems of low efficiency and resource mismatch (accuracy) in traditional manual scheduling, and reducing scheduling time. It can also improve the flexibility and adaptability of the scheduling plan by dynamically adapting the weight strategy of each scenario, and the visual scheduling plan can provide real-time feedback on task execution status and resource utilization, providing a dynamic optimization basis for the maintenance site, thereby significantly improving the operational efficiency and safety of aircraft scheduled maintenance.

[0012] In some embodiments, the objective function includes:

[0013] Minimize total working hours: The corresponding weight is α1;

[0014] Maintenance style score maximization items: The corresponding weight is α2;

[0015] Experience matching maximization item: The corresponding weights are α3 and α4 respectively; the experience matching maximization item includes the maintenance number maximization item and the time to last maintenance minimization item, among which the maintenance number maximization item is: The corresponding weight is α3; the time from the last maintenance is minimized: The corresponding weight is α4;

[0016] The objective function is

[0017] Among them, C i Indicates the start time of work content i, S i represents the completion time of work content i, n represents the total number of work contents; m represents the total number of work sections, p j represents the total number of employees in section j; Y ijk is a zero-one variable, indicating whether employee k in section j is assigned to perform work content i. If assigned, Y ijk =1, otherwise, Y ijk =0;Q k represents the maintenance style score of employee k; B ki It represents the time interval from the last time employee k performed work content i to the current time, E ki Indicates the number of times employee k performs work content i.

[0018] In some embodiments, the calling of the solver to schedule the maintenance tasks by setting a weighted combination of objective functions to generate a maintenance task scheduling plan includes:

[0019] Inputting the objective function and its weight combination into a solver;

[0020] The solver generates different maintenance task scheduling schemes according to different weight combinations.

[0021] In some embodiments, generating a personnel portrait based on the maintenance personnel's basic information, qualification authorization status, and historical task data includes:

[0022] Obtain basic information and qualification authorization status data of maintenance personnel. The basic information includes employee number, work section, and maintenance style score. The qualification authorization status data includes engine test authorization status and scheduled maintenance Class B qualification authorization status.

[0023] Collecting historical task data of the maintenance personnel performing the maintenance task, the historical task data including the number of tasks, proficiency level, and the last task time;

[0024] The basic information, the qualification authorization status data and the historical task data are integrated and analyzed to obtain a personnel portrait.

[0025] In some embodiments, constructing a maintenance task model based on the minimum personnel requirements, qualification matching rules, standard working hours, and parallel execution rules of the maintenance task includes:

[0026] For each maintenance task, determine the minimum personnel requirement and the number of optional additional personnel to obtain the maintenance personnel requirement;

[0027] Set the qualification matching rules for each maintenance task to obtain personnel qualification requirements;

[0028] Determine the required man-hours by setting standard man-hours for each maintenance task based on historical data, task difficulty, and task category, and by establishing rules for reducing man-hours when additional staff are assigned to the task;

[0029] Analyze and determine the sequence dependencies and parallel execution rules between maintenance tasks to obtain work sequence information;

[0030] The maintenance manpower requirement, the personnel qualification requirement, the working hour requirement and the work sequence information are integrated to obtain a maintenance task model.

[0031] In some embodiments, generating a scheduling constraint set based on the work section selection constraint, the employee uniqueness constraint, the task sequence dependency constraint, and the work time interval constraint includes:

[0032] Determine that only one work section is selected to perform all maintenance tasks, forming a work section selection constraint;

[0033] It is stipulated that each maintenance task can only be completed by employees of the selected work section, forming an employee uniqueness constraint;

[0034] Analyze the logical sequence relationship between maintenance tasks to ensure that maintenance tasks are strictly executed in their mandatory sequence and that specific tasks are completed last in the specified sequence, forming task sequence dependency constraints;

[0035] Set a set time interval between the work content performed by each employee to form a work time interval constraint;

[0036] The work section selection constraint, the employee uniqueness constraint, the task sequence dependency constraint, and the work time interval constraint are aggregated to obtain a scheduling constraint set.

[0037] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a maintenance task scheduling device, the device comprising:

[0038] The portrait generation module is used to generate personnel portraits based on the maintenance personnel's basic information, qualification authorization status, and historical task data;

[0039] Model building module, used to build maintenance task models based on the minimum personnel requirements, qualification matching rules, standard working hours and parallel execution rules of maintenance tasks;

[0040] The constraint generation module is used to generate a scheduling constraint set based on work section selection constraints, employee uniqueness constraints, task sequence dependency constraints, and work time interval constraints;

[0041] A function construction module is used to construct an objective function based on the personnel portrait, the maintenance task model and the scheduling constraint set, wherein the objective function includes a total working time minimization item, a maintenance style score maximization item, and an experience matching degree maximization item;

[0042] A calling module is used to call the solver, schedule the maintenance tasks by setting a weight combination of the objective function, and generate a maintenance task scheduling plan;

[0043] The scheduling visualization module is used to generate a visual scheduling plan based on the task allocation and time series data in the maintenance task scheduling plan.

[0044] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements the method described in the first aspect above.

[0045] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the method described in the first aspect above.

[0046] To achieve the above-mentioned purpose, the fifth aspect of the embodiments of the present application proposes a computer program product, which includes a computer program or computer instructions. When the computer program or the computer instructions are executed by a processor, the method described in the first aspect is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the maintenance task scheduling method provided by an embodiment of the present application;

[0048] Figure 2 yes Figure 1 A flowchart of step S101 in FIG.

[0049] Figure 3 yes Figure 1 A flowchart of step S102 in FIG.

[0050] Figure 4 yes Figure 1 A flowchart of step S103 in FIG.

[0051] Figure 5 yes Figure 1 A flowchart of step S105 in FIG.

[0052] Figure 6 This is an example diagram of a visual scheduling plan of the maintenance task scheduling method provided in an embodiment of the present application;

[0053] Figure 7 This is a structural diagram of a maintenance task scheduling device provided in an embodiment of the present application;

[0054] Figure 8 This is a hardware structure diagram of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0056] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0057] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0058] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0059] First, let’s analyze some of the terms used in this application:

[0060] Scheduled inspections are periodic checks conducted to ensure an aircraft's airworthiness, based on the airworthiness documentation and aircraft maintenance plan. The frequency and inspection items of scheduled inspections are determined based on factors such as the aircraft's flight hours, number of takeoffs and landings (flight cycles), and calendar hours. The interval between scheduled inspections is determined by flight hours, flight cycles (landings), and calendar hours.

[0061] A-Checks: A-Checks are preliminary inspections that extend the depth and breadth of line maintenance and are scheduled periodically based on flight hours. The inspection interval varies depending on the aircraft type. For example, the Boeing 737-300 requires an A-Check every 200 flight hours, while the Airbus A320-200 requires an A-Check every 750 flight hours. A-Checks are typically performed 4 to 6 hours during overnight flights.

[0062] B-checks are conducted approximately every 6-8 months and typically require one to three days of hangar time. Because the inspection items are similar to those of A-checks, in actual operations, B-checks are often split into multiple A-checks or combined with C-checks.

[0063] C-Check: A C-Check is a more in-depth inspection of the entire aircraft, adding additional operational and functional checks, as well as lubrication and corrosion prevention work. The interval between C-Checks is determined by flight time, landing and takeoff times, or calendar hours, whichever comes first.

[0064] A D-check is the highest level of comprehensive maintenance, requiring the entire aircraft to be disassembled, all cabin items (seats, galleys, etc.) removed, and the landing gear removed for a complete and comprehensive inspection. A D-check typically requires a return to a specialized repair facility, requiring two months of downtime and 40,000 man-hours. However, the interval between D-checks is longer, at 5-6 years. On average, a commercial airliner is retired after two to three D-checks.

[0065] Solver: A software or algorithmic tool that uses different algorithmic strategies to quickly find the optimal or feasible solution to a constrained optimization problem based on the provided objective function and constraints.

[0066] In existing technology, the aircraft scheduled inspection process is typically a collaborative effort across multiple departments. The typical operational process is as follows: the MCC issues a "Maintenance Work Entry and Exit Notice" to notify relevant units to prepare for the scheduled inspection; the scheduled inspection execution unit and the aircraft management unit jointly conduct a pre-inspection report to identify the aircraft's condition and defects; the scheduled inspection execution unit compiles work cards based on the defects and adds them to the scheduled inspection work package; three days before the aircraft arrives at the factory, the scheduled inspection execution unit completes the scheduled inspection work schedule, workflow diagram, planned work package, and routine work card list based on the scheduled inspection work package. However, existing technology also has shortcomings, including time-consuming manual scheduling and inefficient manual adjustments during changes; inefficient resource utilization, making it difficult to find the optimal solution; high error rates, prone to oversights such as skills mismatches that affect scheduling quality and execution efficiency; and a lack of fairness and transparency. Manual decision-making can be influenced by personal biases, leading to unfair scheduling and employee dissatisfaction or labor-management conflicts.

[0067] See also Figure 1 , Figure 1 This is an optional flowchart of the maintenance task scheduling method provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S106.

[0068] Step S101: Generate a personnel profile based on the maintenance personnel's basic information, qualification authorization status, and historical task data;

[0069] Step S102: constructing a maintenance task model based on the minimum personnel requirements, qualification matching rules, standard working hours, and parallel execution rules of the maintenance task;

[0070] Step S103: Generate a scheduling constraint set based on the work section selection constraint, employee uniqueness constraint, task sequence dependency constraint, and work time interval constraint;

[0071] Step S104: constructing an objective function based on the personnel portrait, maintenance task model, and scheduling constraint set. The objective function includes a total working time minimization item, a maintenance style score maximization item, and an experience matching maximization item;

[0072] Step S105: calling the solver to schedule the maintenance tasks by setting the weight combination of the objective function and generating a maintenance task scheduling plan;

[0073] Step S106: Generate a visual scheduling plan based on the task allocation and time series data in the maintenance task scheduling plan.

[0074] Steps S101 to S106 shown in the embodiment of the present application, by constructing a multi-dimensional personnel portrait and a refined maintenance task model, combined with multiple constraints such as work section selection, employee uniqueness and task sequence dependency, quantify unstructured data such as maintenance style score and experience matching as the core optimization items of the objective function, and call the solver based on the dynamic weight combination to generate a maintenance task scheduling plan, thereby realizing full-process automated scheduling of scheduled maintenance tasks, effectively solving the technical problems of low efficiency and resource mismatch (accuracy) in traditional manual scheduling, and while reducing scheduling time, it can also improve the flexibility and adaptability of the scheduling plan by dynamically adapting the weight strategy of each scenario, and the visual scheduling plan can provide real-time feedback on task execution status and resource utilization, providing a dynamic optimization basis for the maintenance site, thereby significantly improving the operational efficiency and safety of aircraft scheduled maintenance.

[0075] In step S101 of some embodiments, maintenance personnel refers to staff members engaged in fields such as aircraft maintenance tasks. Basic information includes employee number, work section, and maintenance style, wherein the employee number is used to uniquely identify each maintenance personnel; maintenance work is divided by work section, such as the four-shift work in the field of aircraft maintenance adopts a "day and night rest" cycle, and the specific time varies according to the geographical location of each base. Taking the 8:00 morning shift as an example, that is, 8:00-20:00 on the first day, 20:00-8:00 on the second day (8 am on the third day), rest on the third day, and rest on the fourth day. The embodiment of the present application allocates shifts according to the four-shift system, and the working time of each team is 12 hours to ensure the continuity of production. Maintenance style refers to the work attitude, discipline and meticulousness of employees when performing maintenance tasks in the past.

[0076] Qualification authorization status refers to engine test authorization (whether the employee is qualified to test the engine, yes or no) and scheduled inspection and maintenance Class B qualification (whether the employee has scheduled inspection and maintenance Class B qualification, yes or no), which determines whether the maintenance personnel can participate in specific types of maintenance tasks.

[0077] Historical task data includes work times (the cumulative number of times the employee has performed a specific scheduled maintenance task), proficiency level (based on the employee's performance and feedback in different maintenance tasks, the employee's proficiency is assessed in grades), and the last task time (recording the time when the employee last completed the maintenance task).

[0078] A personnel portrait is a comprehensive presentation of all aspects of maintenance personnel, including basic information, qualification information, and proficiency models, used to comprehensively describe the capabilities and characteristics of maintenance personnel. This application collects and integrates data from various aspects of maintenance personnel to establish a detailed personnel portrait for each maintenance personnel. This process enables systems such as solvers to more accurately understand information such as the capabilities, qualifications, and work experience of each maintenance personnel, providing strong data support for subsequent task allocation, improving the accuracy of matching task allocation with personnel capabilities, and thus improving the execution efficiency and quality of overall maintenance tasks.

[0079] See also Figure 2 In some embodiments, step S101 may include but is not limited to steps S201 to S203:

[0080] Step S201: Obtain basic information and qualification authorization status data of maintenance personnel. Basic information includes employee number, work section, and maintenance style score. Qualification authorization status data includes engine test authorization status and scheduled maintenance Class B qualification authorization status.

[0081] Step S202: collecting historical task data of maintenance tasks performed by maintenance personnel, including the number of tasks, proficiency level, and the time of the last task;

[0082] Step S203: Integrate and analyze the basic information, qualification authorization status data, and historical task data to obtain a personnel portrait.

[0083] In step S201 of some embodiments, basic information and qualification authorization status data of maintenance personnel are collected and obtained through certain methods (such as querying from a database, entering employee information into a system, etc., which are not specifically limited here). This step collects basic information and qualification authorization status data of maintenance personnel in a specific way, laying the foundation for subsequent comprehensive understanding and management of personnel. Accurately obtaining this information enables the system to clearly grasp the basic situation and professional qualifications of each maintenance personnel. When subsequently allocating and scheduling tasks, it can reasonably arrange work based on this information, ensure that the qualifications of personnel and tasks match, improve the accuracy and safety of maintenance work, and avoid work errors or safety hazards caused by inconsistent personnel qualifications.

[0084] In step S202 of some embodiments, historical task data of maintenance tasks performed by maintenance personnel is collated and obtained from relevant records or systems. Historical task data may be data recording the maintenance personnel's past performance of maintenance tasks. The number of tasks refers to the cumulative number of times the employee has performed a specific scheduled maintenance task, reflecting the employee's accumulated experience in the maintenance task; the proficiency level is a graded assessment of the employee's operational proficiency based on the employee's performance and feedback in different maintenance tasks, which can be used to measure the employee's ability to perform maintenance tasks; the last task time records the specific time when the employee last completed the maintenance task, which helps to determine the employee's familiarity with the task and the retention of their skills.

[0085] In step S203 of some embodiments, basic information, qualification authorization status data and historical task data are merged and summarized to form an organic whole, and ultimately a personnel portrait is generated.

[0086] This embodiment of the application integrates and analyzes the various types of data collected previously to form a personnel profile. This profile provides the system with a comprehensive window into the maintenance personnel, enabling more scientific and reasonable decisions based on the actual situation of the employees when scheduling maintenance tasks and training personnel. For example, when assigning tasks, the profile can be used to quickly identify the employee most suitable for a specific task, improving the efficiency and quality of maintenance task execution.

[0087] In step S102 of some embodiments, the maintenance task may be a specific maintenance work item, such as a scheduled maintenance task of an aircraft.

[0088] See also Figure 3 In some embodiments, step S102 may include but is not limited to steps S301 to S305:

[0089] Step S301: for each maintenance task, determine the minimum personnel requirement and the number of optional additional personnel to obtain the maintenance personnel requirement;

[0090] Step S302: Set the qualification matching rules for each maintenance task to obtain personnel qualification requirements;

[0091] Step S303 , referring to historical data, task difficulty, and task category, sets standard working hours for each maintenance task, formulates rules for reducing working hours when additional staff are assigned to the task, and determines working hour requirements;

[0092] Step S304: Analyze and determine the sequence dependencies and parallel execution rules between maintenance tasks to obtain work sequence information;

[0093] Step S305 : Integrate the maintenance personnel requirements, personnel qualification requirements, working hours requirements and work sequence information to obtain a maintenance task model.

[0094] In step S301 of some embodiments, the minimum personnel requirement may be the minimum number of personnel required to ensure the normal execution of each maintenance task. This is the basic manpower guarantee for completing the maintenance task. The optional additional personnel refers to the number of personnel that can be added based on actual conditions, after meeting the minimum personnel requirement, to shorten task completion time, etc. The maintenance headcount requirement refers to the personnel requirement for each maintenance task, including the minimum personnel requirement and the optional additional personnel.

[0095] In step S302 of some embodiments, the qualification matching rules may specify the employee qualifications required for each maintenance task. Some tasks may even require the collaboration of multiple employees with different qualifications. The personnel qualification requirements may determine the specific requirements for the personnel qualifications required for each maintenance task based on the set qualification matching rules.

[0096] In step S303 of some embodiments, historical data refers to relevant data such as the time recorded for executing similar maintenance tasks in the past, which can be used as a reference for setting standard working hours. Task difficulty refers to the degree of complexity of the maintenance task in terms of technology, operation, etc., and has an important impact on the determination of standard working hours and working hour reduction rules. Task category refers to the classification based on the characteristics and nature of the maintenance task. Tasks of different categories may have different working hour characteristics. Standard working hours are the time required for each maintenance task under normal circumstances, that is, according to standard operating procedures and work efficiency. Standard working hours are usually set based on historical data, task difficulty and task category.

[0097] Hour reduction rules specify the specific rules for reducing working hours when additional staff are assigned to maintenance tasks, while also taking into account issues such as reduced coordination efficiency due to overstaffing. Hour requirements refer to the time requirements for each maintenance task, determined by combining standard working hours with hour reduction rules.

[0098] The embodiments of the present application determine the required working hours by setting standard working hours based on various factors and formulating rules for reducing working hours. The setting of standard working hours provides a benchmark for the time scheduling of tasks, while the rules for reducing working hours take into account the changes in time when manpower is increased. In this way, when scheduling tasks, the start and end times of tasks can be reasonably arranged according to the working hour requirements, and human resources can be deployed to improve the time management efficiency of task execution.

[0099] In step S304 of some embodiments, sequential dependencies may be mandatory precedence relationships between maintenance tasks, meaning that some tasks must be completed before others can begin. Parallel execution rules determine which maintenance tasks can be performed simultaneously. Therefore, it is necessary to identify parallel tasks during task scheduling to fully utilize human resources and time.

[0100] Work sequence information describes the order in which maintenance tasks are performed, as well as which tasks can be performed in parallel. Clear work sequence information is crucial for properly arranging the execution of maintenance tasks. It ensures that tasks are performed in the correct order, avoiding confusion or incomplete work due to incorrect sequencing. Furthermore, identifying tasks that can be performed in parallel optimizes time and resources, improving overall maintenance efficiency.

[0101] In step S305 of some embodiments, the maintenance task model is a comprehensive model formed by integrating various aspects of the maintenance task information (number of people, qualifications, working hours, sequence, etc.), and is used to fully describe the characteristics and requirements of the maintenance task.

[0102] The constructed maintenance task model provides a comprehensive and systematic basis for subsequent maintenance task scheduling and resource allocation. By using the maintenance task model, solvers and other systems can more accurately understand the characteristics and requirements of each maintenance task, thereby more rationally performing tasks, personnel arrangements, and time planning, thereby improving the scientific nature and efficiency of maintenance task management.

[0103] In step S103 of some embodiments, various scheduling constraints are determined and aggregated to generate a scheduling constraint set. This set provides clear limits and specifications for scheduling maintenance tasks, ensuring that the task scheduling process meets various actual conditions and requirements, avoiding problems such as unreasonable task allocation and employee scheduling conflicts, and ensuring the rationality and orderliness of maintenance task scheduling.

[0104] See also Figure 4 In some embodiments, step S103 may include but is not limited to steps S401 to S405:

[0105] Step S401, determining to select only one work section to perform all maintenance tasks, forming a work section selection constraint;

[0106] Step S402: It is stipulated that each maintenance task can only be completed by employees of the selected work section, forming an employee uniqueness constraint;

[0107] Step S403: Analyze the logical order relationship between maintenance tasks to ensure that maintenance tasks are strictly executed in their mandatory order and that a specific task is completed last in the specified order, thus forming a task order dependency constraint.

[0108] Step S404: Set a set time interval between each employee's work content to form a work time interval constraint;

[0109] Step S405 , the work section selection constraints, employee uniqueness constraints, task sequence dependency constraints, and work time interval constraints are aggregated to obtain a scheduling constraint set.

[0110] In step S401 of some embodiments, the work section selection constraint is a restriction condition on the work sections for executing the maintenance task, stipulating that only one work section can be selected from a plurality of work sections to complete all maintenance tasks.

[0111] In step S402 of some embodiments, the employee uniqueness constraint is that each maintenance task can only be completed by employees of the selected work section.

[0112] In step S403 of some embodiments, the task sequence dependency constraint is to ensure that the maintenance tasks are strictly executed in their mandatory sequence, and to ensure that a specific task (such as the V2500 engine water washing task S_10) is completed last in the prescribed sequence.

[0113] In step S404 of some embodiments, the work time interval constraint is to ensure that there is a set time interval between the work content performed by each employee.

[0114] In step S405 of some embodiments, the scheduling constraint set refers to a set of the above-mentioned constraints, which is used to comprehensively limit and guide the scheduling of maintenance tasks. The scheduling constraint set may also include other constraints, such as capability level and authorization constraints.

[0115] Specifically, (1) the section selection constraint can be expressed as:

[0116]

[0117] Among them, X j Indicates whether section j is responsible for the maintenance task. If so, X j =1, otherwise, X j =0; m=4 represents the total number of work sections.

[0118] (2) The personnel quantity constraint can be expressed as:

[0119]

[0120] Among them, Y ijk Indicates whether employee k in section j is assigned to perform work content i. If assigned, Y ijk =1, otherwise, Y ijk =0;P jrepresents the total number of employees in section j; H i Indicates the minimum number of personnel required for work content i.

[0121] (3) Capability levels and authorization constraints:

[0122] a) One of the people needs to have a capability level of C or above and possess specific qualifications and authorizations, which can be expressed as:

[0123]

[0124] b) In addition, q persons (q is determined based on the maintenance task requirements) have a capability level of B or above and have the corresponding qualifications and authorizations, which can be expressed as:

[0125]

[0126] Among them, L k Indicates the ability level of employee k (L k =1 means A level, L k =2 means B level, and so on, L k =5 means E level), I is used to judge whether the capability level meets the requirements, I is a zero-one variable. k ≥3, I(L k ≥3) is 1, otherwise it is 0; I(L k ≥2) Similarly, when L k ≥2, I(L k ≥2) is 1, otherwise it is 0; A k Indicates the authorization status of employee k (A k =1 means authorized, A k =0 means no authorization).

[0127] (4) Task sequence dependency constraints (working time and sequence constraints):

[0128] a) Adjust the task completion time according to the number of personnel and the nature of the task, which can be expressed as:

[0129]

[0130] Among them, S i Indicates the start time of work content i, where S1 indicates the start time of the first work content, S 10 Indicates the start time of the V2500 engine water washing work; C i represents the completion time of work content i; T i represents the standard maintenance time of work content i; β i It indicates the amount of working time that can be reduced when one more employee is assigned to the work content i.

[0131] b) Ensure the maintenance task sequence so that the V2500 engine water washing task S_10 must be completed last, which can be expressed as:

[0132]

[0133] c) Ensure that all maintenance tasks are completed within 12 hours of the work section, which can be expressed as:

[0134] C 10 ≤S1+12

[0135] d) Work interval constraint (employee rest time constraint), which ensures that there is a half-hour interval between the work content performed by each employee, which can be expressed as:

[0136]

[0137] e) Employee uniqueness constraint: Each maintenance task can only be completed by employees of the selected work section, which can be expressed as:

[0138]

[0139] In step S104 of some embodiments, the objective function is a mathematical function used to measure the quality of maintenance task scheduling plans, and the optimal scheduling plan is determined by optimizing different objectives. Among them, the total working time minimization term is the part of the objective function that aims to minimize the total working time of the maintenance task, and the total working time is the sum of the time required to complete all maintenance tasks. The maintenance style score maximization term is the part of the objective function that aims to maximize the maintenance style score of employees involved in the maintenance task. The maintenance style score reflects the work attitude, discipline and other aspects of the employees. The experience matching maximization term is the part of the objective function that aims to maximize the experience matching degree of employees in performing tasks. The experience matching degree takes into account factors such as the number of times and proficiency of employees in performing specific tasks.

[0140] The embodiment of the present application constructs an objective function containing multiple optimization objectives by integrating information of personnel profiles, maintenance task models, and scheduling constraint sets. The objective function includes:

[0141] Minimize total working hours: The corresponding weight is α1;

[0142] Maintenance style score maximization items: The corresponding weight is α2;

[0143] Experience matching maximization item (minimize work interval + maximize work number): The corresponding weights are α3 and α4; the experience matching degree maximization item includes the maintenance number maximization item and the time to last maintenance minimization item, among which the maintenance number maximization item is: The corresponding weight is α3; the time from the last maintenance is minimized: The corresponding weight is α4;

[0144] The objective function is

[0145] Among them, C i Indicates the start time of work content i, S i represents the completion time of work content i, n represents the total number of work contents. When the maintenance task is V2500 engine water washing, n = 10 represents the total number of work contents including V2500 engine water washing; m represents the total number of work sections, p j represents the total number of employees in section j; Y ijk is a zero-one variable, indicating whether employee k in section j is assigned to perform work content i. If assigned, Y ijk =1, otherwise, Y ijk =0;Q k represents the maintenance style score of employee k; B ki It represents the time interval from the last time employee k performed work content i to the current time, E ki Indicates the number of times employee k performs work content i.

[0146] It should be noted that the optimal maintenance task scheduling solution can be achieved by balancing multiple objectives through the weighted combination of the objective function. Taking the overall objective function as minimum, the weights α1, α2, α3, and α4 can be appropriately set to achieve a trade-off between multiple objectives, such as total man-hours, maintenance style score, and experience matching, thereby finding the optimal maintenance task scheduling solution that meets actual needs. For example, if the goal is to complete tasks efficiently, the weight of α1 can be increased to highlight the importance of minimizing total man-hours. If the emphasis is on maintenance quality and safety, the weight of α2 can be increased to emphasize the critical importance of maximizing the maintenance style score.

[0147] It's important to note that total work time is defined as the requirement to complete all assigned maintenance tasks within a specified timeframe (12 hours). The optimization goal for total work time is to minimize it and avoid overtime or delays caused by task procrastination. Total work time is weighted higher because it directly impacts on-time task completion and resource efficiency.

[0148] Definition of experience matching (proficiency): The proficiency of an employee in performing a maintenance task, including the number of times the employee has performed the maintenance task in history and the time of the most recent performance of the maintenance task. The optimization goal of experience matching (proficiency): Select the employee with the highest or lowest proficiency to assign maintenance tasks based on specific strategies; when proficiency is prioritized, give priority to experienced employees; when education is prioritized: select employees with lower proficiency to improve the overall skill level of the team. The weight corresponding to experience matching (proficiency): can be adjusted according to the importance of different maintenance tasks. For complex tasks, proficiency may have a greater weight; for non-urgent tasks, the weight may be lower.

[0149] Maintenance style is defined as: an employee's work attitude, discipline, and compliance with safety regulations. The optimization goal for maintenance style is: prioritize employees with a positive maintenance style for critical tasks. The weighting of maintenance style is: for high-standard tasks, maintenance style carries a higher weight; for general tasks, style may be less important than other variables.

[0150] In step S105 of some embodiments, the weight combination is the weight value set for different objectives in the objective function (e.g., minimizing total working hours, maximizing maintenance style score, and maximizing experience matching), which is used to balance the importance of different objectives in the optimization process. The maintenance task scheduling plan is a plan that determines the task allocation for each maintenance personnel and the time sequence of task execution based on the optimization results of the objective function.

[0151] See also Figure 5 In some embodiments, step S105 may include but is not limited to steps S501 to S502:

[0152] Step S501, input the objective function and its weight combination into the solver;

[0153] In step S502 , the solver generates different maintenance task scheduling solutions according to different weight combinations.

[0154] In step S501 of some embodiments, a solver is called and a weight combination of an objective function is set to optimize the scheduling of maintenance tasks.

[0155] In step S502 of some embodiments, based on different weight combinations, the solver can generate corresponding maintenance task scheduling solutions for different requirements (such as time priority, safety priority, training priority, etc.).

[0156] For example, when the weight combination of the objective function is [5.0, -0.1, 1.0, -0.01], the solver generates a maintenance task scheduling plan with the goal of minimizing the total task time while ensuring basic operational compliance. This plan is suitable for time-sensitive tasks such as emergency troubleshooting when there are many production tasks.

[0157] When the weight combination of the objective function is [1, -5, 3.0, -2.0], the solver generates a maintenance task scheduling plan with the goal of maximizing the operation safety factor while ensuring task completion. This is suitable for reducing the risk of human error when production safety pressure is high.

[0158] When the weight combination of the objective function is [1, -0.1, -3.0, 5.0], the solver generates a maintenance task scheduling plan with the goal of giving priority to employees with qualified but low proficiency while ensuring task completion. This plan is suitable for improving the skill level of low-proficiency employees when the task is not urgent and employees are allowed to grow their skills.

[0159] In step S106 of some embodiments, task assignments refer to the specific maintenance tasks assigned to each maintenance personnel as determined in the maintenance task scheduling plan. Time series data refers to data related to the time sequence of each maintenance task in the maintenance task scheduling plan, such as the start and completion times. The visualized scheduling plan can be a maintenance task scheduling plan presented in an intuitive manner, such as a graphic or chart, for easy viewing and management by relevant personnel.

[0160] This embodiment of the application visualizes the key information (task assignment and time series data) in the maintenance task scheduling plan to generate a visual scheduling plan. This intuitive presentation allows relevant personnel to more clearly understand the task allocation and time schedule, facilitating task management, resource coordination, and progress management, improving work convenience and efficiency, and helping to better implement the maintenance task scheduling plan.

[0161] See also Figure 6 , Figure 6It is a visual scheduling plan diagram of the maintenance task scheduling method provided by the embodiment of the present application. The maintenance personnel can first select the work section of the day from the first, second, third and fourth work sections, and then select the maintenance task to add tasks such as V2500 engine water washing, replacement of the air intake duct, etc. to the pre-selected task list. The selected tasks will be presented in the list and can also be deleted or cleared with one click. After clicking the maintenance task scheduling button, the solver and other systems can generate a visual scheduling plan corresponding to the optimal maintenance task scheduling solution. When scheduling maintenance tasks, the embodiment of the present application will ensure that each worker has a 30-minute break between the work of different maintenance tasks. In the visual scheduling plan, different colors represent different maintenance tasks, and "Level" is used to indicate the worker's proficiency in a certain job. The worker can also intuitively see the content of his work for the day.

[0162] See also Figure 7 The embodiment of the present application further provides a maintenance task scheduling device that can implement the above maintenance task scheduling method, and the device includes:

[0163] The portrait generation module 701 is used to generate a personnel portrait based on the basic information, qualification authorization status and historical task data of the maintenance personnel;

[0164] Model building module 702, for building a maintenance task model based on the minimum personnel requirements, qualification matching rules, standard working hours and parallel execution rules of the maintenance task;

[0165] The constraint generation module 703 is used to generate a scheduling constraint set based on the work section selection constraint, the employee uniqueness constraint, the task sequence dependency constraint, and the work time interval constraint;

[0166] Function construction module 704, for constructing an objective function based on the personnel profile, maintenance task model, and scheduling constraint set. The objective function includes a total working time minimization term, a maintenance style score maximization term, and an experience matching degree maximization term;

[0167] The calling module 705 is used to call the solver, schedule the maintenance tasks by setting the weight combination of the objective function, and generate a maintenance task scheduling plan;

[0168] The scheduling visualization module 706 is used to generate a visual scheduling plan based on the task allocation and time series data in the maintenance task scheduling plan.

[0169] The specific implementation of the maintenance task scheduling device is substantially the same as the specific embodiment of the maintenance task scheduling method described above, and will not be described in detail herein.

[0170] In a third aspect, the present application provides an electronic device, see Figure 8, which is a structural diagram of an electronic device provided by this application.

[0171] like Figure 8 As shown, the equipment includes:

[0172] Memory 31, for storing computer programs;

[0173] a processor 32 for executing computer programs;

[0174] When the processor 32 executes the computer program, the maintenance task scheduling method according to any of the above embodiments is implemented.

[0175] For example, the computer program can be divided into one or more modules / units, one or more modules / units are stored in the memory 31 and executed by the processor 32 to complete the present application. One or more modules / units can be a series of computer program instruction segments that can perform specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0176] The processor 32 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0177] The memory 31 can be used to store computer programs and / or modules. The processor 32 implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory 31 and accessing the data stored in the memory 31. The memory 31 may mainly include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function, an image playback function, etc.); the data storage area may store data generated based on the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory 31 may include high-speed random access memory and non-volatile memory, such as a hard disk, internal memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0178] It should be noted that the above electronic device includes a processor and a memory, but is not limited to a processor and a memory. Those skilled in the art will understand that Figure 8 The structural diagram is merely an example of the electronic device described above and does not limit the electronic device. The electronic device may include more components than shown in the figure, or may combine certain components, or may include different components.

[0179] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed, the maintenance task scheduling method of any of the above embodiments is implemented.

[0180] It should be understood that the present application can implement all or part of the processes in the maintenance task scheduling method described above by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the maintenance task scheduling method described above. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, mobile hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signals, telecommunication signals, and software distribution media. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased based on the requirements of legislation and patent practice in relevant jurisdictions. For example, in some relevant jurisdictions, based on legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0181] In a fifth aspect, an embodiment of the present application further provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the maintenance task scheduling method of any of the above embodiments.

[0182] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware through a computer program. The program can be stored in a computer-readable storage medium, and when executed, the program can include the processes in the above-described method embodiments. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0183] The above is a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications are also considered to be within the scope of protection of the present application.

Claims

1. A maintenance task scheduling method, characterized in that: include: Generate personnel portraits based on maintenance personnel's basic information, qualification authorization status, and historical task data; Construct a maintenance task model based on the minimum personnel requirements, qualification matching rules, standard working hours, and parallel execution rules of the maintenance task; Generate a scheduling constraint set based on work section selection constraints, employee uniqueness constraints, task sequence dependency constraints, and work time interval constraints; Constructing an objective function based on the personnel portrait, the maintenance task model, and the scheduling constraint set, wherein the objective function includes a total working time minimization item, a maintenance style score maximization item, and an experience matching maximization item; Calling a solver to schedule the maintenance tasks by setting a weight combination of an objective function, and generating a maintenance task scheduling plan; Based on the task allocation and time series data in the maintenance task scheduling solution, a visual scheduling plan is generated.

2. The maintenance task scheduling method according to claim 1, characterized in that: The objective function includes: Minimize total working hours: The corresponding weight is α1; Maintenance style score maximization items: The corresponding weight is α2; Experience matching maximization item: The corresponding weights are α3 and α4 respectively; the experience matching maximization item includes the maintenance number maximization item and the time to last maintenance minimization item, among which the maintenance number maximization item is: The corresponding weight is α3; the time from the last maintenance is minimized: The corresponding weight is α4; The objective function is Among them, C i Indicates the start time of work content i, S i represents the completion time of work content i, n represents the total number of work contents; m represents the total number of work sections, p j represents the total number of employees in section j; Y ijk is a zero-one variable, indicating whether employee k in section j is assigned to perform work content i. If assigned, Y ijk =1, otherwise, Y ijk =0;Q k represents the maintenance style score of employee k; B ki It represents the time interval from the last time employee k performed work content i to the current time, E ki Indicates the number of times employee k performs work content i.

3. The maintenance task scheduling method according to claim 2, characterized in that: The calling solver performs task scheduling on the maintenance task by setting a weight combination of an objective function to generate a maintenance task scheduling plan, including: Inputting the objective function and its weight combination into a solver; The solver generates different maintenance task scheduling schemes according to different weight combinations.

4. The maintenance task scheduling method according to claim 1, wherein: The personnel portrait is generated based on the basic information, qualification authorization status and historical task data of the maintenance personnel, including: Obtain basic information and qualification authorization status data of maintenance personnel. The basic information includes employee number, work section, and maintenance style score. The qualification authorization status data includes engine test authorization status and scheduled maintenance Class B qualification authorization status. Collecting historical task data of the maintenance personnel performing the maintenance task, the historical task data including the number of tasks, proficiency level, and the last task time; The basic information, the qualification authorization status data and the historical task data are integrated and analyzed to obtain a personnel portrait.

5. The maintenance task scheduling method according to claim 1, wherein: The maintenance task model is constructed based on the minimum personnel requirements, qualification matching rules, standard working hours and parallel execution rules of the maintenance task, including: For each maintenance task, determine the minimum personnel requirement and the number of optional additional personnel to obtain the maintenance personnel requirement; Set the qualification matching rules for each maintenance task to obtain personnel qualification requirements; Determine the required man-hours by setting standard man-hours for each maintenance task based on historical data, task difficulty, and task category, and by establishing rules for reducing man-hours when additional staff are assigned to the task; Analyze and determine the sequence dependencies and parallel execution rules between maintenance tasks to obtain work sequence information; The maintenance manpower requirement, the personnel qualification requirement, the working hour requirement and the work sequence information are integrated to obtain a maintenance task model.

6. The maintenance task scheduling method according to claim 1, wherein: The generation of a scheduling constraint set based on the work section selection constraint, employee uniqueness constraint, task sequence dependency constraint, and work time interval constraint includes: Determine that only one work section is selected to perform all maintenance tasks, forming a work section selection constraint; It is stipulated that each maintenance task can only be completed by employees of the selected work section, forming an employee uniqueness constraint; Analyze the logical sequence relationship between maintenance tasks to ensure that maintenance tasks are strictly executed in their mandatory sequence and that specific tasks are completed last in the specified sequence, forming task sequence dependency constraints; Set a set time interval between the work content performed by each employee to form a work time interval constraint; The work section selection constraint, the employee uniqueness constraint, the task sequence dependency constraint, and the work time interval constraint are aggregated to obtain a scheduling constraint set.

7. A maintenance task scheduling device, characterized in that: include: The portrait generation module is used to generate personnel portraits based on the maintenance personnel's basic information, qualification authorization status, and historical task data; Model building module, used to build maintenance task models based on the minimum personnel requirements, qualification matching rules, standard working hours and parallel execution rules of maintenance tasks; The constraint generation module is used to generate a scheduling constraint set based on work section selection constraints, employee uniqueness constraints, task sequence dependency constraints, and work time interval constraints; A function construction module is used to construct an objective function based on the personnel portrait, the maintenance task model and the scheduling constraint set, wherein the objective function includes a total working time minimization item, a maintenance style score maximization item, and an experience matching degree maximization item; A calling module is used to call the solver, schedule the maintenance tasks by setting a weight combination of the objective function, and generate a maintenance task scheduling plan; The scheduling visualization module is used to generate a visual scheduling plan based on the task allocation and time series data in the maintenance task scheduling plan.

8. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the maintenance task scheduling method according to any one of claims 1 to 6 is implemented.

9. 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, the device where the computer-readable storage medium is located is controlled to execute the maintenance task scheduling method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product includes a computer program or computer instructions, and when the computer program or the computer instructions are executed by a processor, the maintenance task scheduling method according to any one of claims 1 to 6 is implemented.

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