CN114926052A - Intelligent recommendation method and system for equipment maintenance personnel - Google Patents
Intelligent recommendation method and system for equipment maintenance personnel Download PDFInfo
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
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- 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
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- 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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- 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
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06398—Performance of employee with respect to a job function
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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
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- G—PHYSICS
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- 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
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Abstract
The invention provides an intelligent recommendation method and system for equipment maintenance personnel. The method comprises the following steps: acquiring a finished maintenance work order in a system where equipment is located; evaluating the maintenance quality of each maintenance worker based on the maintenance work order; evaluating the new troubleshooting and maintenance capacity of each maintenance worker based on the maintenance work order; evaluating the maintenance efficiency of each maintenance worker based on the maintenance work order; correcting the existing score of each maintenance person based on the maintenance order; and one or any combination of the four is/are comprehensively calculated, and the r persons before ranking are used as recommended maintenance persons. The intelligent recommendation method for the equipment maintenance personnel relies on objective data, a plurality of objective evaluation indexes according to the data are established, the influence of artificial malicious scoring is reduced, and the recommendation rationality is improved.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to an intelligent recommendation method and system for equipment maintenance personnel.
Background
With the continuous improvement of scientific technology and human living standard, more and more devices are applied to the production and living of the current. Therefore, after-sale problems of the devices become a problem which is more concerned by consumers at present. One of the most important items after sale of the equipment is the maintenance of the equipment.
When equipment needs to be serviced, the customer is generally unaware of how to select the service personnel in terms of the selection of the service personnel, and therefore needs to make recommendations to the equipment service personnel. However, most of the existing equipment maintenance personnel recommend the equipment maintenance personnel, the equipment maintenance personnel excessively rely on artificial evaluation data, and the equipment maintenance personnel occupy great subjective components, so that the objectivity of a recommendation result is insufficient.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide an intelligent recommendation method and system for equipment maintenance personnel.
In order to achieve the above object, the present invention provides an intelligent recommendation method for equipment maintenance personnel, comprising the following steps:
acquiring a finished maintenance work order in a system where equipment is located;
evaluating the maintenance quality of each maintenance worker based on the maintenance work order;
evaluating the new troubleshooting and maintenance capacity of each maintenance worker based on the maintenance work order;
evaluating the maintenance efficiency of each maintenance worker based on the maintenance work order;
correcting the existing score of each maintenance person based on the maintenance order;
and one or any combination of the four is/are comprehensively calculated, and the r persons before ranking are taken as recommended maintenance persons.
The intelligent recommendation method for the equipment maintenance personnel relies on objective data, a plurality of objective evaluation indexes according to the data are established, the influence of artificial malicious scoring is reduced, and the recommendation rationality is improved.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the maintenance work order comprises an emergency maintenance work order, a preventive maintenance work order and other maintenance work order data which are completed in the system.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the step of evaluating the maintenance quality Q of each maintenance worker comprises the following steps:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment to obtain an equipment fault classification set, wherein the equipment fault classification set comprises a plurality of subsets, the equipment types of the maintenance work orders in each subset are the same and the fault types are the same, and a time difference value of maintenance time of two adjacent same type faults of the same equipment in each subset is calculated; if the same type of fault does not occur after the last maintenance, the time difference is the current time-the last maintenance time;
calculating the sum of the time difference values corresponding to the same maintenance personnel in each subset; calculating the average time length avg (delta t) of the effective time length of the treatment effect of each maintenance worker on the same type of equipment, wherein the avg (delta t) is sum (delta t)/count; wherein count is the number of times that each maintenance worker maintains the same type of fault of the same type of equipment, delta t is the time difference of the maintenance time of two adjacent same type faults of the same equipment of each maintenance worker, and sum (delta t) refers to the total duration of the time difference of the maintenance time of two adjacent same type faults of the same type of equipment of each maintenance worker;
calculating the average maintenance times avg (cnt) (count)/pcount of the maintenance personnel for maintaining the same type of equipment; wherein count is the number of times each maintenance person maintains the same type of equipment, and sum (count) is the number of times all maintenance persons maintain the same type of equipment; pcount is the number of maintenance personnel;
calculating a maintenance quality evaluation score Q ═ count/avg (cnt) avg (delta t) of the same type of faults when each maintenance worker maintains the same type of equipment; the greater the Q value, the higher the quality of the overall repair.
According to the preferred embodiment, objective evaluation of the maintenance quality of each maintenance worker for maintaining the same type of equipment and the same type of faults is obtained by depending on objective data, and the recommendation reasonability is improved.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the step of evaluating the new troubleshooting and maintenance capability S of each maintenance personnel comprises the following steps:
based on all maintenance work orders, carrying out classified aggregation according to the same type of faults of the same type of equipment, and screening out a maintenance work order set P of the fault type which appears for the first time;
counting the number of maintenance work orders solved by each maintenance worker in the set P;
the new troubleshooting maintenance capability score S of each maintenance person is CntPerson/CntP, where CntPerson is the number of maintenance work orders solved by each maintenance person in the set P, and CntP is the total number of maintenance work orders in the set P.
The preferred embodiment relies on objective data to obtain objective evaluation of the new troubleshooting and maintenance capability of each maintenance worker, and the recommendation reasonableness is improved.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the step of evaluating the maintenance efficiency E of each maintenance worker comprises the following steps:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment and according to the conditions of maintenance by the same maintenance personnel to obtain a maintenance personnel maintenance equipment fault classification set; calculating the maintenance time of each maintenance work order in the set, wherein the maintenance time is the work order ending time and the work order starting time; the fault classification set of the maintenance personnel maintenance equipment comprises a plurality of subsets, and the equipment types, the fault types and the maintenance personnel of the maintenance work orders in each subset are the same; aiming at each subset, arranging the subsets in ascending order according to the end time of the maintenance work order to obtain a set A' ═ a 0 ,a 1 ,a 2 ,...a m ...,a n M is an integer, m is more than or equal to 0 and less than or equal to n, n is the maintenance worker singular number in the subset and is a nonnegative integer, a m The mth maintenance work order ending time is indicated;
initializing P1, P2; calculating t ═ a m+1 /a m If t is<1, representing that the efficiency is improved every time, P1 is P1+ 1; if t is>1, then calculate t' ═ a m+1 /a 0 If t'<1 represents the relative first effective rate improvement, P2 is P2+ 1; traverse all in the maintainer-repair-equipment fault classification setRepeating the step to obtain P1 and P2 corresponding to each subset;
and calculating the maintenance efficiency E of each maintenance worker for each fault type of each equipment type, namely (P1+ 0.8P 2)/count (A '), wherein the count (A') is the number of maintenance workers in the subset corresponding to the current calculation.
According to the preferred embodiment, objective evaluation of the maintenance efficiency of each maintenance personnel on each fault type of each equipment type is obtained by relying on objective data, and the recommendation reasonableness is improved.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the step of correcting the existing score of each maintenance person comprises the following steps:
calculating the average score of each fault type by a grader based on all maintenance work orders, and combining each grader-each fault type-average score as an element to obtain a set S;
calculating the average score of each marker for each maintenance worker to maintain each fault type, and combining the average score of each marker-each maintenance worker-each fault type-as an element to obtain a set S1;
traversing the sets S and S1, taking the element a in the set S, and then taking all the elements b meeting the condition from the set S1, wherein the condition is that the scorer and the fault type in the element a are the same as those in the element b;
comparing the average score in element a with the average score in all elements b; when Ka alpha < ═ Kb < ═ Ka beta is met, then the element b is counted into a set E, if not, then the element b is counted into a set E', wherein Ka is the average score corresponding to the element a, Kb is the average score corresponding to the element b, alpha and beta are positive real numbers, and if Ka beta > is the highest value of the score, then Ka beta is the highest value of the score;
calculating the average score of each maintenance worker for processing each fault type based on the elements in the set E', taking the average score of each maintenance worker-each fault type-as one element, and combining to obtain a set F;
and merging the set E and the set F to obtain an effective set G, and calculating the average score of each maintenance worker in the effective set G for processing each fault type, and recording the average score as delta.
The preferred embodiment corrects the score processed by the maintenance personnel by relying on objective data, reduces the influence of artificial malicious score, and improves the recommendation reasonableness.
The preferred scheme of the intelligent recommendation method for the equipment maintenance personnel is as follows: the comprehensive calculation comprises the following steps:
judging whether the fault needing to be maintained is a new fault;
if the fault is a new fault, calculating a new fault recommendation comprehensive integral Sc of each maintenance worker, wherein S is the new fault troubleshooting maintenance capacity of each maintenance worker, E1 is the maintenance efficiency evaluation of each maintenance worker, and E1 is sum (E), wherein sum (E) refers to the maintenance quality evaluation total score of each maintenance worker for all types of equipment and all types of faults;
if the fault is not a new fault, the equipment type of the equipment and the fault type of the fault needing to be maintained, calculating a known fault recommendation comprehensive integral Sc ═ Q '. E'. multidot.delta 'of each maintenance worker, wherein Q' is the maintenance quality of each maintenance worker for the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained, delta 'is the average score of each maintenance worker for the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained, and E' is the maintenance efficiency of each maintenance worker for the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained;
and sequencing the recommended comprehensive points Sc according to the size, and processing the fault needing to be maintained by r maintenance personnel before the points in the recommended comprehensive points.
According to the optimal scheme, whether the fault to be maintained is a new fault or an existing fault is judged, and then recommendation is performed according to objective data, so that the recommendation rationality is improved.
The application also provides an equipment maintenance personnel intelligence recommendation system, include:
the storage unit is used for storing all maintenance work order information in the system;
and the processing unit is connected with the storage unit and is used for intelligently recommending the equipment maintenance personnel according to the intelligent equipment maintenance personnel recommending method based on the maintenance work order information. The intelligent recommendation system for the equipment maintenance personnel has all the advantages of the intelligent recommendation method for the equipment maintenance personnel.
The beneficial effects of the invention are:
according to the invention, a plurality of objective evaluation indexes according to objective data are established through objective data, and the maintenance quality of each maintenance worker is evaluated; evaluating the new troubleshooting and maintenance capability S of each maintenance worker; evaluating the maintenance efficiency E of each maintenance worker; correcting the existing score of each maintenance worker; the most suitable maintenance personnel are recommended according to the new faults and the existing faults, the recommendation rationality is improved, the maintenance efficiency of enterprise equipment is improved, and therefore the production efficiency is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart of the evaluation of the repair quality of each repair person;
FIG. 2 is a schematic flow diagram of the evaluation of the new troubleshooting service capabilities of each service person;
FIG. 3 is a schematic flow chart of the evaluation of the repair efficiency of each repair person;
FIG. 4 is a schematic flow chart of the correction of existing scores for each service person;
FIG. 5 is a flow diagram of a comprehensive calculation of recommended maintenance personnel.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, unless otherwise specified and limited, it is to be noted that the terms "mounted," "connected," and "connected" are to be interpreted broadly, and may be, for example, a mechanical connection or an electrical connection, a communication between two elements, a direct connection, or an indirect connection via an intermediate medium, and specific meanings of the terms may be understood by those skilled in the art according to specific situations.
The invention provides an intelligent recommendation method for equipment maintenance personnel, which comprises the following steps:
and acquiring the finished maintenance work order in the system where the equipment is located.
Specifically, the repair order includes an emergency repair order, a preventive maintenance order, and other repair order data that have been completed in the system.
And evaluating the maintenance quality of each maintenance worker based on the maintenance work order.
Here, the evaluation of the maintenance quality of each maintenance person can be accurate to the maintenance quality evaluation of each maintenance person for maintaining the same type of equipment.
As shown in fig. 1, the specific steps are:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment to obtain an equipment fault classification set, wherein the equipment fault classification set comprises a plurality of subsets, the equipment types of the maintenance work orders in each subset are the same and the fault types are the same, and the time difference of the maintenance time of the same type of adjacent two faults of the same equipment in each subset is calculated; and if the same type of fault does not occur after the last maintenance, the time difference is the current time and the last maintenance time.
Calculating the sum of the time difference values corresponding to the same maintenance personnel in each subset; calculating the average time length avg (delta t) of the effective time length of the treatment effect of each maintenance worker on the same type of equipment, wherein the avg (delta t) is sum (delta t)/count; the count is the number of times that each maintenance person maintains the same type of fault of the same type of equipment, the delta t is the time difference of maintenance time of two adjacent faults of the same type of equipment by each maintenance person, and sum (delta t) refers to the total duration of the time difference of the maintenance time of two adjacent faults of the same type of equipment by each maintenance person.
Calculating the average maintenance times avg (cnt) (count)/pcount of the maintenance personnel for maintaining the same type of equipment; wherein count is the number of times each maintenance person maintains the same type of equipment, and sum (count) is the number of times all maintenance persons maintain the same type of equipment; pcount is the number of maintenance personnel;
calculating a maintenance quality evaluation score Q ═ count/avg (cnt) × avg (δ t) of the same type of faults when each maintenance worker maintains the same type of equipment; the greater the Q value, the higher the quality of the overall repair.
For example, suppose a device has A, B, C three types, each of which has a, b, c three failure types. The classification and aggregation are carried out according to the same type faults of the same type of equipment to obtain an equipment fault classification set 1, wherein the set 1 is { { Aa }, { Ab }, { Ac }, { Ba }, { Bb }, { Bc }, { Ca }, { Cb }, { Cc } }, { Aa }, { Ab }, { Ac }, { Ba }, { Bb }, { Bc }, { Ca }, { Cb }, and { Cc } are subsets in the set 1, and the subsets { Aa } are taken as an example to represent maintenance orders with the equipment type A and the fault type a, and the time difference value of two adjacent maintenance faults of the same equipment in the maintenance orders of the two adjacent maintenance types a is calculated. That is, there may be a plurality of devices that are all a-type devices and all have performed maintenance for a-type faults, and if one of the devices has performed maintenance for a-type faults three times in sequence, then 3 time difference values are obtained: second repair time-first repair time; third repair time-second repair time; current time-third repair time; adding all the time difference values calculated by each device to obtain the total time length of the time difference value of the maintenance time of the type a fault of the type A device; and screening the subset { Aa } according to the condition of maintenance of the same maintenance personnel, and adding all the time difference values obtained by calculation of each equipment in the screened maintenance work order to obtain the total duration of the time difference values of the maintenance time of each maintenance personnel for the type a faults of the type A equipment, wherein the number-1 of the added time difference values is the number of times of the maintenance of the type a faults of the type A equipment by each maintenance personnel. And performing the same operation on all the subsets to finally obtain the times count of the same type of faults of the equipment of the same type maintained by each maintenance personnel, wherein the total time length sum (delta t) of the time difference value of the maintenance time of the two adjacent faults of the same type of the equipment by each maintenance personnel refers to the times sum (count) of the same type of faults of the equipment maintained by all the maintenance personnel. Therefore, the maintenance quality evaluation score Q of the same type of faults of the same type of equipment maintained by each maintenance personnel can be calculated.
And evaluating the new troubleshooting and maintenance capacity of each maintenance worker based on the maintenance worker list.
As shown in fig. 2, the specific steps are:
based on all maintenance work orders, classifying and aggregating according to the same type of faults of the same type of equipment, and screening out a maintenance work order set P of the first fault type.
And counting the number of the maintenance work orders solved by each maintenance worker in the set P.
The new troubleshooting maintenance capability score S of each maintenance person is CntPerson/CntP, where CntPerson is the number of maintenance work orders solved by each maintenance person in the set P, and CntP is the total number of maintenance work orders in the set P.
And evaluating the maintenance efficiency of each maintenance personnel based on the maintenance work order.
Here, the evaluation of the maintenance efficiency of each maintenance person can be accurate to the maintenance efficiency of each maintenance person for each failure type of each equipment type. As shown in fig. 3, the specific steps are as follows:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment and by the conditions maintained by the same maintenance personnel to obtain a maintenance personnel maintenance equipment fault classification set; calculating the maintenance time of each maintenance work order in the set, wherein the maintenance time is the work order ending time-work order starting time; the fault classification set of the maintenance personnel maintenance equipment comprises a plurality of subsets, and each subsetThe equipment types, fault types and maintenance personnel of the combined maintenance work orders are the same; aiming at each subset, arranging the subsets in ascending order according to the end time of the maintenance work order to obtain a set A' ═ a 0 ,a 1 ,a 2 ,...a m ...,a n M is an integer, m is more than or equal to 0 and less than or equal to n, n is the maintenance worker singular number in the subset and is a nonnegative integer, a m Refers to the m-th repair order end time.
Initializing P1, P2; calculating t ═ a m+1 /a m If t is<1, representing that the efficiency is improved every time, P1 is P1+ 1; if t is>1, then calculate t ═ a m+1 /a 0 If t'<1 represents the relative first effective rate improvement, P2 is P2+ 1; and traversing all the subsets in the repair personnel repair equipment fault classification set, and repeating the step to obtain P1 and P2 corresponding to each subset.
And calculating the maintenance efficiency E of each maintenance worker for each fault type of each equipment type, namely (P1+ 0.8P 2)/count (A '), wherein the count (A') is the number of maintenance workers in the subset corresponding to the current calculation.
And correcting the existing scores of each maintenance person based on the maintenance order.
Here, the existing rating for each service person may be corrected to the exact rating correction for each service person handling each fault type. As shown in fig. 4, the specific steps are as follows:
calculating the average score of each fault type by a grader based on all maintenance work orders, and combining each grader-each fault type-average score as an element to obtain a set S;
and calculating the average score of each marker for each maintenance worker to maintain each fault type, and combining the average scores of each marker, each maintenance worker, each fault type and each fault type as one element to obtain a set S1.
And traversing the sets S and S1, taking the element a in the set S, and then taking all the elements b meeting the condition that the scorer and the fault type in the element a are the same as those in the element b from the set S1.
Comparing the average score in element a to the average score in all elements b; and when Ka alpha < ═ Kb < ═ Ka beta is met, the element b is counted into a set E, if not, the element b is counted into a set E', wherein Ka is the average score corresponding to the element a, Kb is the average score corresponding to the element b, alpha and beta are positive real numbers, and if Ka beta > is the highest score, the Ka beta is the highest score.
Calculating the average score of each maintenance worker for processing each fault type based on the elements in the set E', taking the average score of each maintenance worker-each fault type-as one element, and combining to obtain a set F;
and combining the set E and the set F to obtain an effective set G, calculating the average score of each fault type processed by each maintenance worker in the effective set G, and recording the average score as delta, namely finishing the score correction of each fault type processed by each maintenance worker.
And one or any combination of the four is/are comprehensively calculated, and the r persons before ranking are used as recommended maintenance persons.
Specifically, as shown in fig. 5, it may be determined whether the fault to be repaired is a new fault.
And if the faults are new faults, calculating a new fault recommendation comprehensive integral Sc of each maintenance personnel, wherein S is the new fault troubleshooting maintenance capacity of each maintenance personnel, E1 is the maintenance efficiency evaluation of each maintenance personnel, and E1 is sum (E), wherein sum (E) refers to the maintenance quality evaluation total score of each maintenance personnel for all types of equipment and all types of faults.
If the current equipment type of the equipment required to be maintained and the fault type of the fault required to be maintained are not the new fault, the known fault recommendation comprehensive integral Sc-Q 'E' delta 'of each maintenance person is calculated, wherein Q' is the maintenance quality of each maintenance person on the equipment type of the equipment required to be maintained and the fault type of the fault required to be maintained, delta 'is the average score of each maintenance person on the equipment type of the equipment required to be maintained and the fault type of the fault required to be maintained, and E' is the maintenance efficiency of each maintenance person on the equipment type of the equipment required to be maintained and the fault type of the fault required to be maintained.
And sequencing the recommended comprehensive points Sc according to the size, and processing the fault needing to be maintained by r maintenance personnel before the points in the recommended comprehensive points.
The invention also provides an intelligent recommendation system for equipment maintenance personnel, which comprises a storage unit and a processing unit, wherein the storage unit stores all maintenance work order information in the system; and the processing unit is connected with the storage unit and carries out intelligent recommendation on equipment maintenance personnel according to the intelligent recommendation method for the equipment maintenance personnel based on the maintenance work order information.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (8)
1. An intelligent recommendation method for equipment maintenance personnel is characterized by comprising the following steps:
acquiring a finished maintenance work order in a system where equipment is located;
evaluating the maintenance quality of each maintenance worker based on the maintenance work order;
evaluating the new troubleshooting and maintenance capacity of each maintenance worker based on the maintenance work order;
evaluating the maintenance efficiency of each maintenance worker based on the maintenance work order;
correcting the existing score of each maintenance person based on the maintenance order;
and one or any combination of the four is/are comprehensively calculated, and the r persons before ranking are taken as recommended maintenance persons.
2. The intelligent recommendation method for equipment maintenance personnel according to claim 1, wherein the repair order comprises an emergency repair order, a preventive maintenance order, and other repair order data that have been completed in the system.
3. The intelligent recommendation method for equipment maintenance personnel according to claim 1, characterized in that the step of evaluating the maintenance quality Q of each maintenance personnel comprises:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment to obtain an equipment fault classification set, wherein the equipment fault classification set comprises a plurality of subsets, the equipment types of the maintenance work orders in each subset are the same and the fault types are the same, and the time difference of the maintenance time of the same type of adjacent two faults of the same equipment in each subset is calculated; if the same type of fault does not occur after the last maintenance, the time difference value is the current time-the last maintenance time;
calculating the sum of the time difference values corresponding to the same maintenance personnel in each subset; calculating the average time length avg (delta t) of the effective time length of the treatment effect of each maintenance worker on the same type of equipment, wherein the avg (delta t) is sum (delta t)/count; wherein count is the number of times that each maintenance worker maintains the same type of fault of the same type of equipment, delta t is the time difference of the maintenance time of two adjacent same type faults of the same equipment of each maintenance worker, and sum (delta t) refers to the total duration of the time difference of the maintenance time of two adjacent same type faults of the same type of equipment of each maintenance worker;
calculating the average maintenance times avg (cnt) (count)/pcount of maintenance personnel for maintaining the same type of equipment; wherein count is the number of times each maintenance worker maintains the same type of equipment, and sum (count) is the number of times all maintenance workers maintain the same type of equipment; pcount is the number of maintenance personnel;
calculating a maintenance quality evaluation score Q ═ count/avg (cnt) avg (delta t) of the same type of faults when each maintenance worker maintains the same type of equipment; the greater the Q value, the higher the overall repair quality.
4. The intelligent recommendation method for equipment maintenance personnel according to claim 1, wherein the step of evaluating the new troubleshooting maintenance capability S of each maintenance personnel comprises:
based on all maintenance work orders, carrying out classified aggregation according to the same type of faults of the same type of equipment, and screening out a maintenance work order set P of the fault type which appears for the first time;
counting the number of maintenance work orders solved by each maintenance worker in the set P;
the new troubleshooting maintenance capability score S of each maintenance person is CntPerson/CntP, where CntPerson is the number of maintenance work orders solved by each maintenance person in the set P, and CntP is the total number of maintenance work orders in the set P.
5. The intelligent recommendation method for equipment maintenance personnel according to claim 1, wherein the step of evaluating the maintenance efficiency E of each maintenance personnel comprises:
based on all maintenance work orders, carrying out classification and aggregation according to the same type of faults of the same type of equipment and according to the conditions of maintenance by the same maintenance personnel to obtain a maintenance personnel maintenance equipment fault classification set; calculating the maintenance time of each maintenance work order in the set, wherein the maintenance time is the work order ending time-work order starting time; the fault classification set of the maintenance personnel maintenance equipment comprises a plurality of subsets, and the equipment types, the fault types and the maintenance personnel of the maintenance work orders in each subset are the same; aiming at each subset, arranging the subsets in ascending order according to the end time of the maintenance work order to obtain a set A ═ { a ═ a 0 ,a 1 ,a 2 ,...a m ...,a n M is an integer, m is more than or equal to 0 and less than or equal to n, n is the maintenance worker singular number in the subset and is a nonnegative integer, a m To the mth oneEnd time of maintenance work order;
initializing P1, P2; calculating t ═ a m+1 /a m If t is<1, representing that the efficiency is improved every time, P1 is P1+ 1; if t is>1, then calculate t' ═ a m+1 /a 0 If t'<1 represents the relative first effective rate improvement, P2 is P2+ 1; traversing all the subsets in the fault classification set of the maintenance personnel maintenance equipment, and repeating the step to obtain P1 and P2 corresponding to each subset;
and calculating the maintenance efficiency E ═ of (P1+0.8 × P2)/count (A ') of each fault type of each equipment type by each maintenance worker, wherein the count (A') is the number of maintenance workers in the subset corresponding to the current calculation.
6. The intelligent recommendation method for equipment maintenance personnel according to claim 1, characterized in that the step of correcting the existing score of each maintenance personnel comprises:
calculating the average score of each fault type by a grader based on all maintenance work orders, and combining each grader-each fault type-average score as an element to obtain a set S;
calculating the average score of each marker for each maintenance worker to maintain each fault type, and combining the average score of each marker-each maintenance worker-each fault type-as an element to obtain a set S1;
traversing the sets S and S1, taking the element a in the set S, and then taking all the elements b meeting the condition from the set S1, wherein the condition is that the scorer and the fault type in the element a are the same as those in the element b;
comparing the average score in element a to the average score in all elements b; when Ka alpha < ═ Kb < ═ Ka beta is met, then the element b is counted into a set E, if not, then the element b is counted into a set E', wherein Ka is the average score corresponding to the element a, Kb is the average score corresponding to the element b, alpha and beta are positive real numbers, and if Ka beta > is the highest value of the score, then Ka beta is the highest value of the score;
calculating the average score of each maintenance worker for processing each fault type based on the elements in the set E', taking the average score of each maintenance worker-each fault type-as one element, and combining to obtain a set F;
and merging the set E and the set F to obtain an effective set G, and calculating the average score of each maintenance worker processing each fault type in the effective set G, and recording the average score as delta.
7. The intelligent recommendation method for equipment maintenance personnel according to claim 1, wherein the step of comprehensive calculation is as follows:
judging whether the fault needing to be maintained is a new fault;
if the fault is a new fault, calculating a new fault recommendation comprehensive integral Sc of each maintenance worker, wherein S is the new fault troubleshooting maintenance capacity of each maintenance worker, E1 is the maintenance efficiency evaluation of each maintenance worker, and E1 is sum (E), wherein sum (E) refers to the maintenance quality evaluation total score of each maintenance worker for all types of equipment and all types of faults;
if the fault is not a new fault, the equipment type of the equipment and the fault type of the fault needing to be maintained, calculating a known fault recommendation comprehensive integral Sc of each maintenance worker, wherein Q ' is the maintenance quality of each maintenance worker for the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained, delta ' is the average score of each maintenance worker for processing the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained, and E ' is the maintenance efficiency of each maintenance worker for the equipment type of the equipment needing to be maintained currently and the fault type of the fault needing to be maintained;
and sequencing the recommended comprehensive points Sc according to the size, and processing the fault needing to be maintained by r maintenance personnel before the points in the recommended comprehensive points.
8. An equipment maintenance person intelligent recommendation system, comprising:
the storage unit is used for storing all maintenance work order information in the system;
the processing unit is connected with the storage unit and used for intelligently recommending the equipment maintenance personnel according to the equipment maintenance personnel intelligent recommendation method of any one of claims 1-7 based on the maintenance work order information.
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| US20060085239A1 (en) * | 2004-10-14 | 2006-04-20 | Thomas Tracey R | Method of selecting and matching professionals |
| CN111860889A (en) * | 2020-07-17 | 2020-10-30 | 黄健 | Electromechanical device intelligent maintenance management system based on BIM |
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