CN113807653A - Fault repair work order positioning method based on fuzzy matching - Google Patents
Fault repair work order positioning method based on fuzzy matching Download PDFInfo
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- CN113807653A CN113807653A CN202110924559.3A CN202110924559A CN113807653A CN 113807653 A CN113807653 A CN 113807653A CN 202110924559 A CN202110924559 A CN 202110924559A CN 113807653 A CN113807653 A CN 113807653A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
Abstract
The invention provides a fault repair work order positioning method based on fuzzy matching. The fault repair work order positioning method based on fuzzy matching comprises the following steps: s1: establishing a fault work order identification model, wherein the fault work order identification model is obtained by training a fault training work order set; s2: accessing a management system to obtain a target fault work order; s3: collecting existing data on the target trouble ticket; s4: identifying the target fault work order through the fault work order identification model, and determining the category of the target fault work order; s5: establishing a fuzzy matching algorithm model; s6: and positioning the target fault work order through the fuzzy matching algorithm model according to the category of the target fault work order. The fault repair work order positioning method based on fuzzy matching has the advantages of automatically processing the fault work order and improving the processing efficiency of the fault work order.
Description
Technical Field
The invention relates to the technical field of work order processing, in particular to a fault repair work order positioning method based on fuzzy matching.
Background
The repair work order system is a network software system which manages, maintains and tracks a series of problems and requests by targets according to the requirements of different organizations, departments and external clients. The fault work order is a simple maintenance plan consisting of one or more operations, and the upper level department issues tasks and the lower level department receives the tasks.
At present, fault work orders are manually located and checked, workload is high, mistakes are easily made, the processing efficiency of the fault work orders is reduced, dispatching is easily omitted, and stable operation of an operation system is affected.
Therefore, there is a need to provide a new fault repair work order positioning method based on fuzzy matching to solve the above technical problems.
Disclosure of Invention
The invention solves the technical problem of providing a fault repair work order positioning method based on fuzzy matching, which can automatically process fault work orders and improve the processing efficiency of the fault work orders.
In order to solve the technical problem, the fault repair work order positioning method based on fuzzy matching provided by the invention comprises the following steps:
s1: establishing a fault work order identification model, wherein the fault work order identification model is obtained by training a fault training work order set;
s2: accessing a management system to obtain a target fault work order;
s3: collecting existing data on the target trouble ticket;
s4: identifying the target fault work order through the fault work order identification model, and determining the category of the target fault work order;
s5: establishing a fuzzy matching algorithm model;
s6: and positioning the target fault work order through the fuzzy matching algorithm model according to the category of the target fault work order.
Preferably, the accessing management system in step S2 specifically includes:
s201: setting a system password of the management system through a data encryption algorithm;
s202: and accessing the management system according to the system password.
Preferably, the data encryption algorithm is a standard DES algorithm.
Preferably, the existing data in step S3 includes:
and (4) operation code: job number of job;
the work types are as follows: the work type for completing the operation refers to the skill type for executing the maintenance work;
material table: a material table contained in the operation, the material table relating to material requirements for accomplishing the operation.
Failure start time: the time at which the fault was detected;
the failure reason is as follows: the technician or supplier believes the cause of the failure;
fault location: the specific location of the fault occurrence.
Preferably, the specific steps of establishing the fault work order identification model in step S1 are as follows:
s101: acquiring a fault work order set to be processed from the management system every other preset time;
s102: and training the fault training work order set according to a random forest algorithm to obtain the fault work order recognition model.
Preferably, the specific steps of identifying the target faulty work order through the faulty work order identification model in step S4 are as follows:
s401: dividing the fault type into a plurality of levels in advance according to the influence degree of the fault type;
s402: extracting fault characteristic quantity from the target fault work order according to the existing information;
s403: and judging the level of the fault type according to the fault characteristic quantity.
Preferably, the establishing of the fuzzy matching algorithm model in the step S5 includes the following steps:
s501: extracting a keyword tag from the existing data, and establishing a tag template;
s502: combing the data to be matched and extracting the keyword label;
s503: calculating the similarity between the keyword label of the data to be matched and the label of the label template according to a similarity calculation method;
s504: the calculated similarity is compared with a threshold value to judge whether the data is matched with the combed service data.
Preferably, the similarity calculation method refers to an edit distance algorithm or a cosine theorem algorithm of a vector space model.
Preferably, the step S6 specifically includes the following steps:
s601: accessing a maintenance personnel background system in the management system;
s602: and matching the optimal maintenance personnel through a fuzzy matching algorithm according to the level of the target fault work order, and automatically dispatching the target fault work order to the optimal maintenance personnel.
Preferably, the best maintenance personnel are the maintenance personnel with the service capability reaching the standard and the nearest fault location in the current idle maintenance personnel.
Compared with the related technology, the fault repair work order positioning method based on fuzzy matching has the following beneficial effects:
the invention provides a fault repair work order positioning method based on fuzzy matching, which is characterized in that a fault work order is identified and positioned based on a type identification model, then a target fault work order is matched with maintenance personnel through a fuzzy matching algorithm, and the fault work order is sequentially dispatched to the optimal maintenance personnel according to different degrees of urgency of the fault work order, so that orderly dispatching work and reasonable distribution of human resources are realized, automatic processing of the fault work order is realized, the processing efficiency of the fault work order is improved, and the stable operation of an operation system is ensured.
Detailed Description
The present invention will be further described with reference to the following embodiments.
A fault repair work order positioning method based on fuzzy matching comprises the following steps:
s1: establishing a fault work order identification model, wherein the fault work order identification model is obtained by training a fault training work order set; the specific steps of establishing the fault work order identification model in the step S1 are as follows:
s101: acquiring a fault work order set to be processed from the management system every other preset time;
s102: and training the fault training work order set according to a random forest algorithm to obtain the fault work order recognition model.
The method comprises the steps of firstly obtaining initial data from professional network management fault data, then cleaning the initial data, dividing the initial data into a fault training worksheet set and a fault testing worksheet set, then respectively randomly sampling n samples from the fault training worksheet set and the fault testing worksheet set based on a random forest algorithm, randomly selecting k features from all the features in the n samples, and establishing a decision tree for the selected samples by using the features, wherein the decision tree can be CART or other mixed modes. And repeating the steps for m times to generate m decision trees to form a random forest. And for new fault data, determining through each tree, and finally confirming the classified target class based on a voting method. The voting method can be divided into an absolute majority voting method and a relative majority voting method. And continuously and circularly training the model by using the fault training work order set and the fault testing work order set until the prediction accuracy of the type recognition model reaches 95 percent.
S2: accessing a management system to obtain a target fault work order; the access management system specifically includes:
s201: setting a system password of the management system through a data encryption algorithm;
s202: and accessing the management system according to the system password, wherein the data encryption algorithm is a standard DES algorithm.
S3: collecting existing data on the target trouble ticket; the existing data includes:
and (4) operation code: job number of job;
the work types are as follows: the work type for completing the operation refers to the skill type for executing the maintenance work;
material table: a material table contained in the operation, the material table relating to material requirements for accomplishing the operation.
Failure start time: the time at which the fault was detected;
the failure reason is as follows: the technician or supplier believes the cause of the failure;
fault location: the specific location of the fault occurrence.
S4: identifying the target fault work order through the fault work order identification model, and determining the category of the target fault work order, wherein the specific steps are as follows:
s401: dividing the fault type into a plurality of levels in advance according to the influence degree of the fault type; the processing of the fault work order needs to have a mild or severe grade, and the grade of the fault type determines the processing sequence of the fault work order. The classification standard of the fault type grade is set according to actual needs, for example, the fault type of the electrical equipment can be classified into two grades of emergency fault and general fault according to whether the fault type affects the normal operation of the equipment; the emergency fault refers to the condition that maintenance personnel need to maintain in time, otherwise, immeasurable loss can be brought; the general failure means that the device may be automatically recovered from the general failure state. And the fault work order corresponding to the emergency fault is processed before the fault work order corresponding to the general fault.
S402: extracting fault characteristic quantity from the target fault work order according to the existing information;
s403: and judging the level of the fault type according to the fault characteristic quantity.
S5: establishing a fuzzy matching algorithm model, which comprises the following specific steps:
s501: extracting a keyword tag from the existing data, and establishing a tag template;
s502: combing the data to be matched and extracting the keyword label;
s503: calculating the similarity between the keyword label of the data to be matched and the label of the label template according to a similarity calculation method; the similarity calculation method refers to an edit distance algorithm and a cosine theorem algorithm of a vector space model.
S504: the calculated similarity is compared with a threshold value to judge whether the data is matched with the combed service data.
S6: according to the category of the target fault work order, positioning the target fault work order through the fuzzy matching algorithm model; the method specifically comprises the following steps:
s601: accessing a maintenance personnel background system in the management system;
s602: and matching the best maintenance personnel through a fuzzy matching algorithm according to the level of the target fault work order, and automatically dispatching the target fault work order to the best maintenance personnel, wherein the best maintenance personnel are the maintenance personnel with the service capability reaching the standard and closest to the fault site in the current idle maintenance personnel.
The currently idle maintenance personnel refer to maintenance personnel who are not allocated with the fault work order currently, and include maintenance personnel who are not allocated with the fault work order and maintenance personnel who have processed the fault work order allocated for the last time. The database stores a working condition information statistical table of the current idle maintenance personnel, and the table records the service capability statistical information of the current idle maintenance personnel, and simultaneously can also record the geographical position statistical information of the current idle maintenance personnel and the like. Correspondingly, when a service capability value of a certain emergency fault to a maintenance person is received, the best maintenance person with the service capability reaching the current idle maintenance person is screened out, which may be that when a service capability value of a certain emergency fault to a maintenance person is received, the maintenance person with the highest service capability and higher than the service capability value is selected out of the service capability statistics information of the current idle maintenance person and is used as the best maintenance person. Or, when receiving a service capability value of a certain emergency fault to a serviceman, selecting, from the service capability level statistical information of currently idle servicemen, a serviceman whose service capability value is higher than the value and which is closest to the value (i.e., closest to the geographical location of the inverter in which the emergency fault occurs) as an optimal serviceman. When all fault work orders corresponding to the emergency faults are dispatched, the best maintenance personnel are matched with the fault work orders corresponding to the common faults in sequence, and due to the fact that the fault work orders are the common faults, strict requirements on the service level of the maintenance personnel are not needed during matching, and only the best maintenance personnel are required to be solved quickly, for example, the maintenance personnel closest to the fault work orders can be screened out from the currently idle maintenance personnel to serve as the best maintenance personnel.
Compared with the related technology, the fault repair work order positioning method based on fuzzy matching has the following beneficial effects:
the invention provides a fault repair work order positioning method based on fuzzy matching, which is characterized in that a fault work order is identified and positioned based on a type identification model, then a target fault work order is matched with maintenance personnel through a fuzzy matching algorithm, and the fault work order is sequentially dispatched to the optimal maintenance personnel according to different degrees of urgency of the fault work order, so that orderly dispatching work and reasonable distribution of human resources are realized, automatic processing of the fault work order is realized, the processing efficiency of the fault work order is improved, and the stable operation of an operation system is ensured.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by the present specification, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A fault repair work order positioning method based on fuzzy matching is characterized by comprising the following steps:
s1: establishing a fault work order identification model, wherein the fault work order identification model is obtained by training a fault training work order set;
s2: accessing a management system to obtain a target fault work order;
s3: collecting existing data on the target trouble ticket;
s4: identifying the target fault work order through the fault work order identification model, and determining the category of the target fault work order;
s5: establishing a fuzzy matching algorithm model;
s6: and positioning the target fault work order through the fuzzy matching algorithm model according to the category of the target fault work order.
2. The method for locating the fault report repair work order based on the fuzzy matching as claimed in claim 1, wherein the accessing the management system in the step S2 specifically includes:
s201: setting a system password of the management system through a data encryption algorithm;
s202: and accessing the management system according to the system password.
3. The troubleshooting work order locating method based on fuzzy matching as claimed in claim 2, wherein the data encryption algorithm is a standard DES algorithm.
4. The troubleshooting work order locating method based on fuzzy matching as claimed in claim 1, wherein the existing data in the step S3 includes:
and (4) operation code: job number of job;
the work types are as follows: the work type for completing the operation refers to the skill type for executing the maintenance work;
material table: a material table contained in the operation, the material table relating to material requirements for accomplishing the operation.
Failure start time: the time at which the fault was detected;
the failure reason is as follows: the technician or supplier believes the cause of the failure;
fault location: the specific location of the fault occurrence.
5. The method for locating the fault report repair work order based on the fuzzy matching as claimed in claim 1, wherein the specific steps of establishing the fault work order identification model in the step S1 are as follows:
s101: acquiring a fault work order set to be processed from the management system every other preset time;
s102: and training the fault training work order set according to a random forest algorithm to obtain the fault work order recognition model.
6. The method for locating the fault report repair work order based on the fuzzy matching as claimed in claim 1, wherein the specific steps of identifying the target fault work order by the fault work order identification model in the step S4 are as follows:
s401: dividing the fault type into a plurality of levels in advance according to the influence degree of the fault type;
s402: extracting fault characteristic quantity from the target fault work order according to the existing information;
s403: and judging the level of the fault type according to the fault characteristic quantity.
7. The fault report repair work order positioning method based on fuzzy matching as claimed in claim 1, wherein said step S5 of establishing a fuzzy matching algorithm model comprises the steps of:
s501: extracting a keyword tag from the existing data, and establishing a tag template;
s502: combing the data to be matched and extracting the keyword label;
s503: calculating the similarity between the keyword label of the data to be matched and the label of the label template according to a similarity calculation method;
s504: the calculated similarity is compared with a threshold value to judge whether the data is matched with the combed service data.
8. The troubleshooting work order locating method based on fuzzy matching as recited in claim 7, wherein the similarity calculation method refers to an edit distance algorithm, a cosine theorem algorithm of a vector space model.
9. The method for locating the fault report repair work order based on the fuzzy matching as claimed in claim 1, wherein said step S6 specifically includes the following steps:
s601: accessing a maintenance personnel background system in the management system;
s602: and matching the optimal maintenance personnel through a fuzzy matching algorithm according to the level of the target fault work order, and automatically dispatching the target fault work order to the optimal maintenance personnel.
10. The method of claim 9, wherein the best maintainer is the maintainer with qualified business capability nearest to the fault location among the currently idle maintainers.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114742484A (en) * | 2022-06-13 | 2022-07-12 | 北京神州光大科技有限公司 | Method, system, device and medium for processing information technology service requirement |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090037772A1 (en) * | 2007-08-03 | 2009-02-05 | Wegerich Stephan W | Fuzzy classification approach to fault pattern matching |
| CN109858746A (en) * | 2018-12-26 | 2019-06-07 | 阳光电源股份有限公司 | A kind of fault ticket distributing method and fault ticket management system |
| CN111797593A (en) * | 2020-06-19 | 2020-10-20 | 翰博瑞强(上海)医药科技有限公司 | Medical event coding method based on fuzzy matching |
| CN112001572A (en) * | 2020-10-27 | 2020-11-27 | 绿漫科技有限公司 | Work order intelligent allocation method |
| CN112183782A (en) * | 2020-10-13 | 2021-01-05 | 中国联合网络通信集团有限公司 | Fault work order processing method and equipment |
-
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- 2021-08-12 CN CN202110924559.3A patent/CN113807653A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090037772A1 (en) * | 2007-08-03 | 2009-02-05 | Wegerich Stephan W | Fuzzy classification approach to fault pattern matching |
| CN109858746A (en) * | 2018-12-26 | 2019-06-07 | 阳光电源股份有限公司 | A kind of fault ticket distributing method and fault ticket management system |
| CN111797593A (en) * | 2020-06-19 | 2020-10-20 | 翰博瑞强(上海)医药科技有限公司 | Medical event coding method based on fuzzy matching |
| CN112183782A (en) * | 2020-10-13 | 2021-01-05 | 中国联合网络通信集团有限公司 | Fault work order processing method and equipment |
| CN112001572A (en) * | 2020-10-27 | 2020-11-27 | 绿漫科技有限公司 | Work order intelligent allocation method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114742484A (en) * | 2022-06-13 | 2022-07-12 | 北京神州光大科技有限公司 | Method, system, device and medium for processing information technology service requirement |
| CN114742484B (en) * | 2022-06-13 | 2022-08-26 | 北京神州光大科技有限公司 | Method, system, device and medium for processing information technology service requirement |
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