CN117726321A - Maintenance scheme generation method, device, equipment and medium based on business score - Google Patents
Maintenance scheme generation method, device, equipment and medium based on business score Download PDFInfo
- Publication number
- CN117726321A CN117726321A CN202311747385.3A CN202311747385A CN117726321A CN 117726321 A CN117726321 A CN 117726321A CN 202311747385 A CN202311747385 A CN 202311747385A CN 117726321 A CN117726321 A CN 117726321A
- Authority
- CN
- China
- Prior art keywords
- maintenance
- task
- score
- service
- equipment
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012423 maintenance Methods 0.000 title claims abstract description 341
- 238000000034 method Methods 0.000 title claims abstract description 52
- 238000012545 processing Methods 0.000 claims abstract description 66
- 230000005856 abnormality Effects 0.000 claims abstract description 37
- 238000001514 detection method Methods 0.000 claims abstract description 36
- 238000007689 inspection Methods 0.000 claims description 43
- 230000002159 abnormal effect Effects 0.000 claims description 28
- 238000012549 training Methods 0.000 claims description 27
- 238000004590 computer program Methods 0.000 claims description 15
- 230000015654 memory Effects 0.000 claims description 10
- 238000013077 scoring method Methods 0.000 abstract description 3
- 238000004364 calculation method Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 6
- 230000002265 prevention Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000000306 recurrent effect Effects 0.000 description 1
- 230000006403 short-term memory Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to the technical field of equipment maintenance, and particularly discloses a maintenance scheme generation method, device, equipment and medium based on service scoring. The method comprises the following steps: acquiring operation data of equipment; processing the operation data based on an abnormality detection model to obtain an operation state of the equipment; acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel; and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel. According to the service scoring method and the service scoring device, service scores of maintenance personnel are obtained according to historical task information of the maintenance personnel, different maintenance personnel can be allocated for different types of equipment, the maintenance personnel are reasonably allocated in combination with the service scores of the maintenance personnel, and then a recommended maintenance scheme of the equipment is generated, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent, and the equipment maintenance efficiency is improved.
Description
Technical Field
The present disclosure relates to the field of equipment maintenance technologies, and in particular, to a service scoring-based maintenance scheme generating method, apparatus, device, and medium.
Background
The digital operation and maintenance platform needs to fully utilize the leading edge technologies such as big data, artificial intelligence and the like to construct a one-stop intelligent big data platform, and provides comprehensive, prospective and active intelligent management and service. The existing maintenance work lacks of big data technical support, which results in the reduction of equipment maintenance efficiency, so how to improve the equipment maintenance efficiency becomes a problem to be solved urgently.
Disclosure of Invention
The application provides a service scoring-based maintenance scheme generation method, device, equipment and medium, so as to improve the maintenance efficiency of the equipment.
In a first aspect, the present application provides a service score-based maintenance scheme generating method, where the method includes:
acquiring operation data of equipment;
processing the operation data based on an abnormality detection model to obtain an operation state of the equipment;
acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel;
and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
Further, the generating a recommended maintenance scheme for the device based on the operating state and the service score of the maintenance personnel includes:
Based on the running state, acquiring the abnormal information of the equipment, comparing a preset fault rule with the abnormal information, and determining the fault type of the equipment;
based on the fault type, searching an initial maintenance scheme corresponding to the fault type in a historical maintenance scheme table, and determining at least one maintainer corresponding to the fault type in a maintainer information table;
determining a target maintainer based on the business score of each maintainer;
the recommended maintenance scheme is generated based on the target maintenance personnel and the initial maintenance scheme.
Further, the obtaining the service score of the maintainer based on the historical task information of the maintainer includes:
based on the historical task information, respectively obtaining task processing time and task contribution degree of the historical inspection task and the historical maintenance task of the maintainer;
and obtaining the service score of the maintainer based on the task processing time and the task contribution degree.
Further, the obtaining the service score of the maintainer based on the task processing time and the task contribution degree includes:
Based on the task processing time and the task contribution degree, obtaining maintenance task total scores and inspection task total scores of maintenance personnel;
calculating and obtaining maintenance task scores of maintenance personnel based on a first preset weight, a second preset weight, the maintenance task total scores and the inspection task total scores;
and calculating and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score.
Further, the calculating to obtain the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score includes:
taking the maintenance task score of the historical task of the maintenance personnel as a first score;
calculating and obtaining maintenance task scores in a preset time period as second scores based on the maintenance task total scores and the inspection task total scores in the preset time period;
and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight, the first score and the second score.
Further, the processing the operation data based on the abnormality detection model, before obtaining the operation state of the device, further includes:
Acquiring historical operation data and historical operation states of at least one device;
processing the historical operation data to generate a training data set;
and training a pre-training model based on the historical running state and the training data set to obtain the abnormality detection model.
Further, the processing the operation data based on the anomaly detection model to obtain an operation state of the device includes:
processing the operation data based on the abnormality detection model to obtain the abnormality times of the equipment in a preset time period;
and comparing the abnormal times with a preset abnormal threshold value to obtain the running state.
In a second aspect, the present application further provides a service score-based maintenance scheme generating device, where the device includes:
the operation data acquisition module is used for acquiring operation data of the equipment;
the running state obtaining module is used for processing the running data based on the abnormality detection model to obtain the running state of the equipment;
the service score obtaining module is used for obtaining service scores of maintenance personnel based on historical task information of the maintenance personnel;
And the recommended maintenance scheme generating module is used for generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
In a third aspect, the present application also provides a computer device comprising a memory and a processor; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the maintenance scheme generating method based on the business score when executing the computer program.
In a fourth aspect, the present application further provides a computer readable storage medium storing a computer program, which when executed by a processor causes the processor to implement a service score based maintenance scheme generation method as described above.
The application discloses a maintenance scheme generation method, a device, equipment and a medium based on service scoring, and operation data of the equipment are obtained; processing the operation data based on an abnormality detection model to obtain an operation state of the equipment; acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel; and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel. According to the service scoring method and the service scoring device, service scores of maintenance personnel are obtained according to historical task information of the maintenance personnel, different maintenance personnel can be allocated for different types of equipment, the maintenance personnel are reasonably allocated in combination with the service scores of the maintenance personnel, and then a recommended maintenance scheme of the equipment is generated, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent, and the equipment maintenance efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a first embodiment of a business score based maintenance scenario generation method provided by an embodiment of the present application;
FIG. 2 is a second embodiment of a business score based maintenance scenario generation method provided by an embodiment of the present application;
FIG. 3 is a flow chart illustrating a third embodiment of a business score based maintenance scenario generation method provided by an embodiment of the present application;
FIG. 4 is a schematic block diagram of a maintenance scheme generating device based on business score according to an embodiment of the present application;
fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application.
Description of the embodiments
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
It is to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
The embodiment of the application provides a maintenance scheme generation method, device, equipment and medium based on service scores. The maintenance scheme generating method based on the service scores can be applied to a server, maintenance personnel are reasonably distributed by combining the service scores of the maintenance personnel, and a recommended maintenance scheme of the equipment is generated, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent, and the equipment maintenance efficiency is improved. The server may be an independent server or a server cluster.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a schematic flowchart of a service score-based maintenance scheme generating method according to an embodiment of the present application. The maintenance scheme generating method based on the service score can be applied to a server and used for reasonably distributing maintenance personnel by combining the service score of the maintenance personnel to generate a recommended maintenance scheme of the equipment, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent and the equipment maintenance efficiency is improved.
As shown in fig. 1, the service score-based maintenance scheme generation method specifically includes steps S101 to S104.
S101, acquiring operation data of equipment.
In one embodiment, the operation data can be obtained through an operation data storage module carried by the device itself; the operational data may also be obtained by an external data monitoring module connected to the device.
S102, processing the operation data based on an abnormality detection model to obtain the operation state of the equipment.
Further, the processing the operation data based on the abnormality detection model, before obtaining the operation state of the device, further includes: acquiring historical operation data and historical operation states of at least one device; processing the historical operation data to generate a training data set; and training a pre-training model based on the historical running state and the training data set to obtain the abnormality detection model.
In one embodiment, historical operating data (current, voltage, power, temperature, humidity, etc.) and historical operating status (operating abnormal, operating normal) for a plurality of different types of devices are obtained from a historical record of the devices. The historical operation data are subjected to serialization and normalization processing, labels are marked for each data to distinguish different data of different tasks, a training data set is obtained, and a pre-training model is trained by adopting a reconstruction-based method (LSTM (Long short-term memory network model), GRU (Gate Recurrent Unit, gating and circulating unit), auto-Encoder and the like).
In one embodiment, the pre-training model obtains a predicted running state of the device according to the training data set, compares the predicted running state with a historical running state to obtain a prediction accuracy of the pre-training model, and corrects the model until the prediction accuracy reaches a preset threshold when the prediction accuracy does not reach the preset threshold, and takes the pre-training model corresponding to the prediction accuracy as the anomaly detection model.
Further, the processing the operation data based on the anomaly detection model to obtain an operation state of the device includes: processing the operation data based on the abnormality detection model to obtain the abnormality times of the equipment in a preset time period; and comparing the abnormal times with a preset abnormal threshold value to obtain the running state.
In one embodiment, the operation data is subjected to serialization and normalization processing, and is used as an input parameter of an abnormality detection model, and is input into the abnormality detection model, and the abnormality detection model obtains and records the abnormality of the equipment at the current moment and obtains the abnormality times of the equipment in a preset time period by processing and analyzing the processed operation data.
In one embodiment, the number of anomalies is compared with a preset threshold number of anomalies, and when the number of anomalies is greater than or equal to the threshold number of anomalies, the operational state of the device is determined to be operational anomalies. For example, if the daily abnormality detection model detects that the number of times of abnormality of a certain device is 3 times and the threshold value of the number of times of abnormality is 2 times, the device is regarded as an operation abnormality device.
In one embodiment, the operational state of the device is determined to be a normal state when the number of anomalies is less than the threshold number of anomalies.
S103, obtaining service scores of maintenance personnel based on historical task information of the maintenance personnel.
In one embodiment, the task processing time and the task contribution degree of the historical inspection task and the historical maintenance task of the maintainer are obtained through the historical task information of the maintainer. And extracting task data of maintenance personnel corresponding to the corresponding numbers from the historical task information according to the personnel numbers, wherein the task data comprise inspection equipment information, maintenance equipment types, task processing time, task contribution degree and the like.
In one embodiment, the business score calculation process is divided into a single task score calculation, a weighted performance score calculation, and a comprehensive business score calculation. The single task score is obtained by obtaining scores of all inspection tasks and maintenance tasks through task processing time and task contribution degree, and substituting the task processing time and the task contribution degree into a preset single task scoring function for calculation.
In one embodiment, the weighted performance score, i.e., maintenance task score, is obtained from each of the single inspection task and the single maintenance task, and the maintenance task total score and the inspection task total score are obtained according to the formula: weighted performance score = first preset weight x total inspection task score/task number + second preset weight x total maintenance task score/task number, and maintenance task score is calculated. The first preset weight is the grading weight of the inspection task, the second preset weight is the grading weight of the maintenance task, the grading weight is determined by historical data, and the importance of the inspection task and the maintenance task is determined according to the historical data to be set.
In one embodiment, the service score of the maintainer is calculated according to a formula of third preset weight value x first score+fourth preset weight value x second score, wherein the first score is a maintenance task score of all tasks of the maintainer, the second score is a maintenance task score of the tasks within a preset time period, the third preset weight value is a scoring weight value of the first score, and the fourth preset weight value is a scoring weight value of the second score.
S104, generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
In one embodiment, the operational status of the device further includes anomaly information for the device. And acquiring abnormal information of the equipment based on the running state, such as the running time of the equipment, the position of the equipment, the recent inspection condition of the equipment, the historical fault record of the equipment and the like. And determining the fault type of the equipment according to the abnormality information of the equipment.
In one embodiment, a historical maintenance scheme corresponding to a fault type of a device is determined in a historical maintenance scheme table according to the fault type of the device as an initial maintenance scheme. The history maintenance scheme comparison table comprises different fault types and history maintenance schemes corresponding to the fault types, and the history maintenance scheme table is generated by counting the maintenance schemes of a plurality of devices with different fault types.
In one embodiment, the business score of the maintenance person corresponds to the capability value of the maintenance person, with a higher business score indicating a higher capability value of the maintenance person. When maintenance personnel with different capacities process maintenance tasks corresponding to the same fault type, the task completion efficiency is different, so that maintenance personnel with highest service scores are determined among the maintenance personnel corresponding to each fault type to process, and the maintenance task processing efficiency can be improved.
In one embodiment, a targeted maintenance person is added to the initial maintenance solution, and a recommended maintenance solution is generated that contains the targeted maintenance person.
The above embodiment provides a service score-based maintenance scheme generating method, device, equipment and medium, and operation data of the equipment are obtained; processing the operation data based on an abnormality detection model to obtain an operation state of the equipment; acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel; and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel. According to the service scoring method and the service scoring device, service scores of maintenance personnel are obtained according to historical task information of the maintenance personnel, different maintenance personnel can be allocated for different types of equipment, the maintenance personnel are reasonably allocated in combination with the service scores of the maintenance personnel, and then a recommended maintenance scheme of the equipment is generated, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent, and the equipment maintenance efficiency is improved.
Referring to fig. 2, fig. 2 is a schematic flowchart of a service score-based maintenance scheme generating method according to an embodiment of the present application. The maintenance scheme generating method based on the service score can be applied to a server and used for reasonably distributing maintenance personnel by combining the service score of the maintenance personnel to generate a recommended maintenance scheme of the equipment, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent and the equipment maintenance efficiency is improved.
As shown in fig. 2, the step S104 of the service score-based maintenance scheme generating method specifically includes steps S201 to S204.
S201, based on the running state, acquiring abnormal information of the equipment, comparing a preset fault rule with the abnormal information, and determining the fault type of the equipment;
in one embodiment, the operational status of the device further includes anomaly information for the device. For equipment with abnormal operation state, acquiring abnormal information of the equipment based on the operation state, such as the operated time length of the equipment, the position of the equipment, the recent inspection condition of the equipment, the historical fault record of the equipment and the like.
In one embodiment, historical inspection and historical fault records of the equipment are obtained by inquiring historical work order information of the equipment, and potential correlation between historical operation time length of the equipment and occurrence reasons of faults is obtained through analysis according to the historical inspection records and the fault records. Meanwhile, through comprehensively analyzing the equipment of the same type and the equipment close to the position, the correlation between equipment inspection frequency and equipment failure frequency is obtained, and a failure rule is generated on historical worksheet data.
In one embodiment, anomaly information for the device is matched with fault rules to determine the type of fault for the device. For example, if the failure rule of the class a failure is that the operation time is greater than 24 hours, when the operation time is greater than 24 hours in the abnormality information of the device that is operating abnormally, the device may be classified as the class a failure.
S202, searching an initial maintenance scheme corresponding to the fault type in a history maintenance scheme table based on the fault type, and determining at least one maintainer corresponding to the fault type in a maintainer information table;
in one embodiment, the history maintenance scheme comparison table includes different fault types and history maintenance schemes corresponding to the fault types, and the history maintenance scheme table is generated by counting the maintenance schemes of a plurality of devices with different fault types.
In one embodiment, by the fault type of the abnormal device, the maintenance scheme corresponding to the fault type is searched in the history maintenance scheme table to serve as an initial maintenance scheme, and the initial prevention scheme may include the fault type, the fault occurrence reason, the fault item, the recommended prevention days and the like.
In one embodiment, the maintenance personnel information table includes maintenance personnel self-related information (e.g., name, age, gender, age, etc.), and the type of fault that each maintenance personnel is responsible for handling. It will be appreciated that a maintenance person may be responsible for only one type of maintenance task, or may be responsible for multiple types of maintenance tasks.
In one embodiment, based on the determined fault type, a maintenance person that can handle the corresponding maintenance task for the fault type is determined in a maintenance person information table. It will be appreciated that at least one maintenance person can handle at least the maintenance tasks corresponding to each fault type in the maintenance person information table.
S203, determining a target maintainer based on the service score of each maintainer;
in one embodiment, after the maintainers capable of processing the maintenance task corresponding to the current fault type are extracted, service scores of the maintainers are compared, and the maintainer with the highest service score is determined to be the target maintainer of the current maintenance task.
In one embodiment, the business score of the maintenance person corresponds to the capability value of the maintenance person, with a higher business score indicating a higher capability value of the maintenance person. When maintenance personnel with different capacities process maintenance tasks corresponding to the same fault type, the task completion efficiency is different, so that maintenance personnel with highest service scores are determined among the maintenance personnel corresponding to each fault type to process, and the maintenance task processing efficiency can be improved.
It can be appreciated that if the maintainer with the highest business score is processing other tasks, the target maintainers are determined in turn according to the ranking of the business scores. Illustratively, for example, the ranking according to business score is the first name: a maintenance personnel, second name: and B, judging whether the maintenance personnel are in an idle state according to the ranking order because the maintenance personnel A are in a working state, and taking the maintenance personnel B as a target maintenance personnel of the current maintenance task if the maintenance personnel B are in the idle state.
In one embodiment, the service score of the maintainer may be obtained by obtaining the maintainer information after determining the maintainer corresponding to the current fault type, or may be obtained by pre-calculating and storing the service score in a maintainer information table.
S204, generating the recommended maintenance scheme based on the target maintenance personnel and the initial maintenance scheme.
In one embodiment, the target maintainer is added into the initial maintenance scheme, the recommended maintenance scheme containing the target maintainer is generated, the maintainer can be rapidly allocated to process maintenance tasks, the maintainer in an idle state can be fully mobilized, and the optimal maintainer can be allocated to maintenance tasks of different fault types, so that the maintenance task processing efficiency is improved.
For example, the initial prevention scheme may include a fault type, a fault occurrence reason, a fault project, a recommended prevention day, etc., and the recommended maintenance scheme includes information (such as name, age, working age, etc.) of the target maintenance personnel.
Referring to fig. 3, fig. 3 is a schematic flowchart of a service score-based maintenance scheme generating method according to an embodiment of the present application. The maintenance scheme generating method based on the service score can be applied to a server and used for reasonably distributing maintenance personnel by combining the service score of the maintenance personnel to generate a recommended maintenance scheme of the equipment, so that the maintenance capability of the maintenance personnel can be exerted to the maximum extent and the equipment maintenance efficiency is improved.
As shown in fig. 3, the step S103 of the maintenance scheme generating method based on the business score specifically includes steps S301 to S302.
S301, based on the historical task information, respectively obtaining task processing time and task contribution degree of a historical inspection task and a historical maintenance task of the maintainer;
s302, obtaining service scores of the maintainers based on the task processing time and the task contribution degree.
In one embodiment, the task processing time and the task contribution degree of the historical inspection task and the historical maintenance task of the maintainer are obtained through the historical task information of the maintainer. And extracting task data of maintenance personnel corresponding to the corresponding numbers from the historical task information according to the personnel numbers, wherein the task data comprise inspection equipment information, maintenance equipment types, task processing time, task contribution degree and the like.
Further, the obtaining the service score of the maintainer based on the task processing time and the task contribution degree includes: based on the task processing time and the task contribution degree, obtaining maintenance task total scores and inspection task total scores of maintenance personnel; calculating and obtaining maintenance task scores of maintenance personnel based on a first preset weight, a second preset weight, the maintenance task total scores and the inspection task total scores; and calculating and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score.
Further, calculating to obtain the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score includes: taking the maintenance task score of the historical task of the maintenance personnel as a first score; calculating and obtaining maintenance task scores in a preset time period as second scores based on the maintenance task total scores and the inspection task total scores in the preset time period; and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight, the first score and the second score.
In one embodiment, the business score calculation process is divided into a single task score calculation, a weighted performance score calculation, and a comprehensive business score calculation. The single task score is obtained by obtaining scores of all inspection tasks and maintenance tasks through task processing time and task contribution degree, and substituting the task processing time and the task contribution degree into a preset single task scoring function for calculation.
In one embodiment, the weighted performance score, i.e., maintenance task score, is obtained from each of the single inspection task and the single maintenance task, and the maintenance task total score and the inspection task total score are obtained according to the formula: weighted performance score = first preset weight x total inspection task score/task number + second preset weight x total maintenance task score/task number, and maintenance task score is calculated. The first preset weight is the grading weight of the inspection task, the second preset weight is the grading weight of the maintenance task, the grading weight is determined by historical data, and the importance of the inspection task and the maintenance task is determined according to the historical data to be set.
Illustratively, for example, by analyzing the history data, the importance of the inspection task is greater, and thus the scoring weight of the inspection task is set to 70% and the scoring weight of the maintenance task is set to 30%. Weighted performance score = 0.7 x patrol task performance total score/task number +0.3 x maintenance task performance total score/task number.
In one embodiment, the service score of the maintainer is calculated according to a formula of third preset weight value x first score+fourth preset weight value x second score, wherein the first score is a maintenance task score of all tasks of the maintainer, the second score is a maintenance task score of the tasks within a preset time period, the third preset weight value is a scoring weight value of the first score, and the fourth preset weight value is a scoring weight value of the second score.
For example, a preset time period is set to be within 30 days, wherein the weight of the overall maintenance task score of the calculator is set to be 80%, and the weight of the maintenance task score in the preset time period is set to be 20%. Business score = 0.8 x maintenance task score + maintenance task score within 0.2 x 30 days.
In one embodiment, service scores of each maintainer for processing maintenance tasks are obtained according to historical maintenance data of the maintainers, maintenance personnel with highest service scores are determined according to fault types of the maintenance tasks, the speed of the maintainers for processing the maintenance tasks is improved, and the processing efficiency of the maintenance tasks is effectively improved.
Referring to fig. 4, fig. 4 is a schematic block diagram of a service-score-based maintenance scheme generating apparatus according to an embodiment of the present application, where the service-score-based maintenance scheme generating apparatus is configured to perform the foregoing service-score-based maintenance scheme generating method. The maintenance scheme generating device based on the business score can be configured on a server.
As shown in fig. 4, the service score-based maintenance scheme generating apparatus 400 includes:
an operation data obtaining module 401, configured to obtain operation data of a device;
an operation state obtaining module 402, configured to process the operation data based on an anomaly detection model, to obtain an operation state of the device;
a service score obtaining module 403, configured to obtain a service score of a maintainer based on historical task information of the maintainer;
and the recommended maintenance scheme generating module 404 is configured to generate a recommended maintenance scheme of the device based on the running state and the service score of the maintenance personnel.
In one embodiment, the recommended maintenance solution generation module 404 includes:
the fault type determining unit is used for acquiring the abnormal information of the equipment based on the running state, comparing a preset fault rule with the abnormal information and determining the fault type of the equipment;
The maintainer searching unit is used for searching an initial maintenance scheme corresponding to the fault type in the historical maintenance scheme table based on the fault type, and determining at least one maintainer corresponding to the fault type in the maintainer information table;
a target maintainer determination unit, configured to determine a target maintainer based on a service score of each maintainer;
and the recommended maintenance scheme generating unit is used for generating the recommended maintenance scheme based on the target maintenance personnel and the initial maintenance scheme.
In one embodiment, the business score obtaining module 403 includes:
the historical work information obtaining sub-module is used for respectively obtaining task processing time and task contribution degree of the historical inspection task and the historical maintenance task of the maintainer based on the historical task information;
and the business score obtaining sub-module is used for obtaining the business score of the maintainer based on the task processing time and the task contribution degree.
In one embodiment, the business score obtaining sub-module includes:
the total score obtaining unit is used for obtaining the maintenance task total score and the inspection task total score of the maintainer based on the task processing time and the task contribution degree;
The maintenance task score obtaining unit is used for calculating and obtaining the maintenance task score of the maintainer based on the first preset weight, the second preset weight, the maintenance task total score and the inspection task total score;
the service score obtaining unit is used for calculating and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score.
In one embodiment, the service score obtaining unit includes:
a first score obtaining subunit, configured to take a maintenance task score of the historical task of the maintenance person as a first score;
the second score obtaining subunit is used for calculating and obtaining the maintenance task score in the preset time period as a second score based on the maintenance task total score and the inspection task total score in the preset time period;
and the business score obtaining subunit is used for obtaining the business score of the maintainer based on the third preset weight, the fourth preset weight, the first score and the second score.
In one embodiment, the service score-based maintenance scheme generating apparatus 400 further includes: an anomaly detection model acquisition module, the anomaly detection model acquisition module comprising:
A history data obtaining unit, configured to obtain history operation data and a history operation state of at least one device;
the training data set generating unit is used for processing the historical operation data to generate a training data set;
the abnormality detection model obtaining unit is used for training a pre-training model based on the historical running state and the training data set to obtain the abnormality detection model.
In one embodiment, the operation state obtaining module 402 includes:
the abnormal times obtaining unit is used for processing the operation data based on the abnormal detection model to obtain abnormal times of the equipment in a preset time period;
and the running state obtaining unit is used for comparing the abnormal times with a preset abnormal threshold value to obtain the running state.
It should be noted that, for convenience and brevity of description, the specific working process of the apparatus and each module described above may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The apparatus described above may be implemented in the form of a computer program which is executable on a computer device as shown in fig. 5.
Referring to fig. 5, fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device may be a server.
With reference to FIG. 5, the computer device includes a processor, memory, and a network interface connected by a system bus, where the memory may include a non-volatile storage medium and an internal memory.
The non-volatile storage medium may store an operating system and a computer program. The computer program comprises program instructions that, when executed, cause the processor to perform any of a number of business scoring based maintenance solution generation methods.
The processor is used to provide computing and control capabilities to support the operation of the entire computer device.
The internal memory provides an environment for the execution of a computer program in a non-volatile storage medium that, when executed by a processor, causes the processor to perform any of a number of business scoring-based maintenance solution generation methods.
The network interface is used for network communication such as transmitting assigned tasks and the like. It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein in one embodiment the processor is configured to run a computer program stored in the memory to implement the steps of:
acquiring operation data of equipment;
processing the operation data based on an abnormality detection model to obtain an operation state of the equipment;
acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel;
and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
In one embodiment, the processor, when implementing generating the recommended maintenance solution for the device based on the operating status and the service score of the maintenance person, is configured to implement:
Based on the running state, acquiring the abnormal information of the equipment, comparing a preset fault rule with the abnormal information, and determining the fault type of the equipment;
based on the fault type, searching an initial maintenance scheme corresponding to the fault type in a historical maintenance scheme table, and determining at least one maintainer corresponding to the fault type in a maintainer information table;
determining a target maintainer based on the business score of each maintainer;
the recommended maintenance scheme is generated based on the target maintenance personnel and the initial maintenance scheme.
In one embodiment, the processor is configured to, when implementing historical task information based on a maintenance person, obtain a service score for the maintenance person, implement:
based on the historical task information, respectively obtaining task processing time and task contribution degree of the historical inspection task and the historical maintenance task of the maintainer;
and obtaining the service score of the maintainer based on the task processing time and the task contribution degree.
In one embodiment, the processor is configured to, when implementing obtaining the service score of the maintenance person based on the task processing time and the task contribution, implement:
Based on the task processing time and the task contribution degree, obtaining maintenance task total scores and inspection task total scores of maintenance personnel;
calculating and obtaining maintenance task scores of maintenance personnel based on a first preset weight, a second preset weight, the maintenance task total scores and the inspection task total scores;
and calculating and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score.
In one embodiment, the processor is configured to, when implementing obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight, and the maintenance task score, perform:
taking the maintenance task score of the historical task of the maintenance personnel as a first score;
calculating and obtaining maintenance task scores in a preset time period as second scores based on the maintenance task total scores and the inspection task total scores in the preset time period;
and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight, the first score and the second score.
In one embodiment, before implementing the anomaly detection model, the processor is further configured to, before implementing the processing of the operation data to obtain the operation state of the device, implement:
Acquiring historical operation data and historical operation states of at least one device;
processing the historical operation data to generate a training data set;
and training a pre-training model based on the historical running state and the training data set to obtain the abnormality detection model.
In one embodiment, when the processor processes the operation data based on the anomaly detection model, the processor is configured to implement:
processing the operation data based on the abnormality detection model to obtain the abnormality times of the equipment in a preset time period;
and comparing the abnormal times with a preset abnormal threshold value to obtain the running state.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, the computer program comprises program instructions, and the processor executes the program instructions to realize any service score-based maintenance scheme generation method provided by the embodiment of the application.
The computer readable storage medium may be an internal storage unit of the computer device according to the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, which are provided on the computer device.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A service score-based maintenance scheme generation method, comprising:
acquiring operation data of equipment;
processing the operation data based on an abnormality detection model to obtain an operation state of the equipment;
acquiring service scores of maintenance personnel based on historical task information of the maintenance personnel;
and generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
2. The service-score-based maintenance scheme generation method according to claim 1, wherein the generating a recommended maintenance scheme for the device based on the operation state and the service score of the maintenance person includes:
based on the running state, acquiring the abnormal information of the equipment, comparing a preset fault rule with the abnormal information, and determining the fault type of the equipment;
Based on the fault type, searching an initial maintenance scheme corresponding to the fault type in a historical maintenance scheme table, and determining at least one maintainer corresponding to the fault type in a maintainer information table;
determining a target maintainer based on the business score of each maintainer;
the recommended maintenance scheme is generated based on the target maintenance personnel and the initial maintenance scheme.
3. The service score-based maintenance scheme generation method according to claim 1, wherein the obtaining service scores of maintenance personnel based on historical task information of the maintenance personnel comprises:
based on the historical task information, respectively obtaining task processing time and task contribution degree of the historical inspection task and the historical maintenance task of the maintainer;
and obtaining the service score of the maintainer based on the task processing time and the task contribution degree.
4. The service-score-based maintenance scheme generation method according to claim 3, wherein the obtaining the service score of the maintenance person based on the task processing time and the task contribution degree includes:
Based on the task processing time and the task contribution degree, obtaining maintenance task total scores and inspection task total scores of maintenance personnel;
calculating and obtaining maintenance task scores of maintenance personnel based on a first preset weight, a second preset weight, the maintenance task total scores and the inspection task total scores;
and calculating and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score.
5. The service score-based maintenance scheme generating method according to claim 4, wherein the calculating to obtain the service score of the maintainer based on the third preset weight, the fourth preset weight and the maintenance task score includes:
taking the maintenance task score of the historical task of the maintenance personnel as a first score;
calculating and obtaining maintenance task scores in a preset time period as second scores based on the maintenance task total scores and the inspection task total scores in the preset time period;
and obtaining the service score of the maintainer based on the third preset weight, the fourth preset weight, the first score and the second score.
6. The service-score-based maintenance scheme generation method according to claim 1, wherein the processing the operation data based on the anomaly detection model, before obtaining the operation state of the device, further comprises:
acquiring historical operation data and historical operation states of at least one device;
processing the historical operation data to generate a training data set;
and training a pre-training model based on the historical running state and the training data set to obtain the abnormality detection model.
7. The maintenance-time-based maintenance scenario generation method according to any one of claims 1 to 6, wherein the processing the operation data based on the abnormality detection model to obtain the operation state of the device includes:
processing the operation data based on the abnormality detection model to obtain the abnormality times of the equipment in a preset time period;
and comparing the abnormal times with a preset abnormal threshold value to obtain the running state.
8. A service-scoring-based maintenance scheme generation apparatus, comprising:
the operation data acquisition module is used for acquiring operation data of the equipment;
The running state obtaining module is used for processing the running data based on the abnormality detection model to obtain the running state of the equipment;
the service score obtaining module is used for obtaining service scores of maintenance personnel based on historical task information of the maintenance personnel;
and the recommended maintenance scheme generating module is used for generating a recommended maintenance scheme of the equipment based on the running state and the service score of the maintenance personnel.
9. A computer device, the computer device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor configured to execute the computer program and implement the business score-based maintenance scenario generation method according to any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the service score based maintenance scheme generation method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311747385.3A CN117726321A (en) | 2023-12-19 | 2023-12-19 | Maintenance scheme generation method, device, equipment and medium based on business score |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311747385.3A CN117726321A (en) | 2023-12-19 | 2023-12-19 | Maintenance scheme generation method, device, equipment and medium based on business score |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117726321A true CN117726321A (en) | 2024-03-19 |
Family
ID=90199473
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311747385.3A Pending CN117726321A (en) | 2023-12-19 | 2023-12-19 | Maintenance scheme generation method, device, equipment and medium based on business score |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117726321A (en) |
-
2023
- 2023-12-19 CN CN202311747385.3A patent/CN117726321A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2020259421A1 (en) | Method and apparatus for monitoring service system | |
| US9424157B2 (en) | Early detection of failing computers | |
| US10579459B2 (en) | Log events for root cause error diagnosis | |
| US10965541B2 (en) | Method and system to proactively determine potential outages in an information technology environment | |
| US10592308B2 (en) | Aggregation based event identification | |
| Gu et al. | Online anomaly prediction for robust cluster systems | |
| US8732534B2 (en) | Predictive incident management | |
| US8949676B2 (en) | Real-time event storm detection in a cloud environment | |
| EP3663919B1 (en) | System and method of automated fault correction in a network environment | |
| Hoffmann et al. | Advanced failure prediction in complex software systems | |
| CN114328102A (en) | Equipment state monitoring method, device, equipment and computer readable storage medium | |
| US10831587B2 (en) | Determination of cause of error state of elements in a computing environment based on an element's number of impacted elements and the number in an error state | |
| Bogojeska et al. | Classifying server behavior and predicting impact of modernization actions | |
| CN112532455B (en) | Abnormal root cause positioning method and device | |
| CN113992602B (en) | Cable monitoring data uploading method, device, equipment and storage medium | |
| CN113472582A (en) | System and method for alarm correlation and alarm aggregation in information technology monitoring | |
| dos Santos et al. | A solution for identifying the root cause of problems in it change management | |
| CN117726321A (en) | Maintenance scheme generation method, device, equipment and medium based on business score | |
| US12028223B2 (en) | Capacity aware cloud environment node recovery system | |
| CN117974098A (en) | Maintenance scheme generation method, device, equipment and medium based on maintenance time | |
| US11768730B2 (en) | Analyzing device, analyzing method, and analyzing program | |
| US20220334914A1 (en) | Anomaly coping support apparatus, method, and program | |
| CN114692082A (en) | Method, system, device and medium for identifying battery swapping user | |
| US20230084950A1 (en) | System and method for monitoring complex structures | |
| US20220206486A1 (en) | Method and system for predictive maintenance of a machinery asset |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |