CN117350521A - Operation and maintenance duty management system and method based on big data analysis - Google Patents
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Abstract
The invention relates to the technical field of operation and maintenance management, in particular to an operation and maintenance duty management system and method based on big data analysis, comprising the following steps: the operation and maintenance data acquisition module acquires operation and maintenance work order information and operation and maintenance personnel information, all acquired data are transmitted to the database, the operation and maintenance personnel are analyzed by the operation and maintenance data acquisition module to obtain a moving route after receiving the operation and maintenance personnel, whether the repeated operation and maintenance personnel appear is judged, the repeated order processing module checks the judgment result to select the best operation and maintenance personnel for the operation and maintenance work of the repeated operation and maintenance personnel to be repeatedly received, the operation and maintenance personnel management module distributes operation and maintenance work orders for the operation and maintenance personnel of the residual repeated operation and maintenance work, timely discovers and early warns the phenomenon of the repeated operation and maintenance personnel, and performs scheduling management of the operation and maintenance personnel to distribute proper operation and maintenance personnel to provide different operation and maintenance services, so that the problem of repeated operation and maintenance work is solved in time, and smooth operation and maintenance work is facilitated.
Description
Technical Field
The invention relates to the technical field of operation and maintenance management, in particular to an operation and maintenance duty management system and method based on big data analysis.
Background
In order to improve the competitiveness of the service, enterprises often provide operation and maintenance outsourcing services and continuously upgrade the operation and maintenance services, and the existing operation and maintenance task processing is generally as follows: the field service operation and maintenance personnel receive the operation and maintenance order and go to the destination to provide operation and maintenance service, after the operation and maintenance service is completed, the operation and maintenance personnel need to return to the unit to input information and confirm, and as the range of the operation and maintenance service is continuously expanded, management work needs to be carried out on the operation and maintenance personnel in time to ensure the smooth progress of the operation and maintenance work;
however, there are still some problems with existing operation and maintenance personnel management methods: with the increasing of IT operation and maintenance orders, the problem that engineers repeatedly connect orders often occurs due to the fact that manual dispatch is adopted in the prior art, the repeated order connection phenomenon which possibly occurs when the repeated order connection situation is monitored and early warned in time is not caused, a plurality of engineers possibly go to the same destination to perform the same operation and maintenance work, the problem that operation and maintenance service is disordered easily and operation and maintenance service cost is increased endlessly is caused, and smooth promotion of operation and maintenance work is not facilitated.
Therefore, there is a need for an operation and maintenance duty management system and method based on big data analysis to solve the above problems.
Disclosure of Invention
The invention aims to provide an operation and maintenance duty management system and method based on big data analysis, which are used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an operation and maintenance duty management system based on big data analysis, the system comprising: the system comprises a fortune dimension acquisition module, a database, a repeated order judgment module, a repeated order processing module and a fortune dimension personnel management module;
the output end of the operation and maintenance data acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the repeated order receiving judgment module, the repeated order processing module and the operation and maintenance personnel management module, the output end of the repeated order receiving judgment module is connected with the input end of the repeated order processing module, and the output end of the repeated order processing module is connected with the input end of the operation and maintenance personnel management module;
collecting operation and maintenance work order information and operation and maintenance personnel information through the operation and maintenance data collecting module, and transmitting all collected data to the database;
storing all the collected data through the database;
analyzing a moving route of the operation and maintenance personnel after receiving the repeated receipt by the repeated receipt judging module, and judging whether the repeated receipt appears or not;
checking the judging result through the repeated order processing module, and selecting the optimal operation and maintenance personnel for the operation and maintenance work of the repeated order;
and distributing operation and maintenance work orders to the operation and maintenance personnel with the rest repeated orders through the operation and maintenance personnel management module.
Further, the operation and maintenance data acquisition module comprises an order information acquisition unit, a personnel information acquisition unit and an operation and maintenance personnel positioning unit;
the output ends of the order information acquisition unit, the personnel information acquisition unit and the operation and maintenance personnel positioning unit are connected with the input end of the database;
the order information acquisition unit is used for acquiring the moving route information of the operation and maintenance personnel and all the distributed operation and maintenance work order information when repeated connection of the order appears in the past, and the order information comprises destination information of operation and maintenance work and difficulty information of the operation and maintenance work;
the personnel information acquisition unit is used for acquiring qualification evaluation information of operation and maintenance personnel, wherein the qualification evaluation information comprises order quantity information processed by the operation and maintenance personnel in the past and operation and maintenance work difficulty information corresponding to the order;
the operation and maintenance personnel positioning unit is used for positioning all operation and maintenance personnel receiving the orders in real time and acquiring real-time position information of the operation and maintenance personnel.
Further, the repeated receipt judgment module comprises a track generation unit, a track superposition analysis unit and a repeated receipt judgment unit;
the input end of the track generating unit is connected with the output end of the database, the output end of the track generating unit is connected with the input end of the track coincidence analysis unit, and the output end of the track coincidence analysis unit is connected with the input end of the repeated receipt judgment unit;
the track generation unit is used for retrieving the real-time position information of all the operation and maintenance personnel receiving the orders and generating a moving route of the corresponding operation and maintenance personnel according to the real-time position;
the track coincidence analysis unit is used for analyzing the coincidence degree between the moving paths;
the repeated order judging unit is used for comparing the superposition degree, judging whether the repeated order phenomenon occurs currently according to the comparison result, and sending an early warning signal to the repeated order processing module when judging that the repeated order phenomenon occurs currently.
Further, the repeated order processing module comprises a repeated order checking unit and an optimal personnel selecting unit;
the input end of the repeated order taking checking unit is connected with the output end of the repeated order taking judging unit, and the output ends of the repeated order taking checking unit and the database are connected with the input end of the optimal personnel selecting unit;
the repeated order receiving checking unit is used for checking whether repeated order phenomenon occurs currently or not after receiving the early warning signal;
and the optimal person selection unit is used for selecting the optimal person from the operation and maintenance personnel repeatedly receiving the repeated order to go to the operation and maintenance work destination corresponding to the current order to carry out operation and maintenance work when checking that the repeated order appears currently.
Further, the operation and maintenance personnel management module comprises a residual order information retrieving unit and a residual personnel distributing unit;
the input end of the residual order information calling unit is connected with the output end of the database, and the output ends of the residual order information calling unit and the optimal personnel selection unit are connected with the residual personnel distribution unit;
the residual order information retrieving unit is used for retrieving all order information which is not received except the repeated order and is remained to the residual personnel distributing unit;
the remaining personnel allocation unit is used for allocating operation and maintenance work orders to operation and maintenance personnel for the repeated connection orders remaining except the optimal personnel.
An operation and maintenance duty management method based on big data analysis comprises the following steps:
s1: collecting operation and maintenance work order information and operation and maintenance personnel information;
s2: analyzing the overlapping degree of the moving routes after the operation and maintenance personnel receive the bill, and judging whether repeated bill receiving occurs or not;
s3: checking the judging result, and if the repeated receipt appears, selecting the best operation and maintenance personnel for the operation and maintenance work of the repeated receipt;
s4: and distributing operation and maintenance work orders for operation and maintenance personnel with the rest repeated orders.
Further, in step S1: collecting the moving route of the operation and maintenance personnel when the repeated single-connection phenomenon appears in the past, displaying the moving route by using a GIS map, and collecting the longest overlapped route length d of the operation and maintenance personnel in the past with two random repeated single-connection processes in the process of going to the same destination i The lengths of routes of the two operation and maintenance personnel to the corresponding destination are L and H respectively, and the superposition degree between the corresponding two operation and maintenance personnel moving routes is w i Wherein w is i =[(d i /L)+(d i /H)]When the repeated single-receiving phenomenon appears in different times in the past, the longest superposition route length set of two operation and maintenance personnel randomly receiving the repeated single-receiving is d= { d in the process of going to the same destination 1 ，d 2 ，…，d i ，…，d n The superposition degree set between the moving routes of the operation and maintenance personnel corresponding to the repeated connection list is w= { w 1 ，w 2 ，…，w i ，…，w n N represents the number of times of repeated order receiving phenomenon, and collecting the information of all the current distributed operation and maintenance work orders: and acquiring destination information of operation and maintenance work and difficulty information of the operation and maintenance work, acquiring order quantity information processed by operation and maintenance personnel who receive the current order in the past and operation and maintenance work difficulty information corresponding to the order, positioning all operation and maintenance personnel who receive the current order in real time, and acquiring real-time position information of the operation and maintenance personnel.
Further, in step S2: call the current placeGenerating a moved route of the operation and maintenance personnel with the real-time position information of the operation and maintenance personnel with the order, acquiring m coincident routes in the moved routes of the two random operation and maintenance personnel, acquiring two end point abscissa of one coincident route at random as a and b respectively, and corresponding coincident route equation as y=f (x) (a is less than or equal to x is less than or equal to b), and according to a formula D j =∫ b a (1+y ’2 ) 1/2 dx calculation of random one coinciding route length D j Calculating the length of m overlapped routes in the same way to obtain the longest overlapped route length D in the m routes max The lengths of the moved routes corresponding to the two operation and maintenance personnel are respectively R and Z, and the length of the moved routes is obtained according to the formula W= [ (D) max /R)+(D max /Z)]Calculating to obtain the coincidence degree W between the current moving routes of two operation and maintenance staff, and calculating the data point { (d) 1 ，w 1 ），（d 2 ，w 2 ），…，（d n ，w n ) Performing straight line fitting, and establishing a repeated connection list judgment model as follows: y=c 1 *X+C 2 Wherein C 1 And C 2 Representing the fitting coefficient, D max Substituting the repeated single judgment model to let X=D max Obtaining the overlapping degree threshold value as C 1 *D max +C 2 Comparison of W and C 1 *D max +C 2 : if W is less than or equal to C 1 *D max +C 2 Judging that the repeated single-connection phenomenon does not occur to the corresponding two operation and maintenance personnel; if W is>C 1 *D max +C 2 Judging that the repeated single-connection phenomenon occurs to the corresponding two operation and maintenance personnel, and sending an early warning signal;
whether repeated bill receiving phenomenon occurs or not can be confirmed without waiting until an operation and maintenance person arrives at a destination, and the repeated bill receiving phenomenon is found in time in the middle, so that the problem of repeated bill receiving of an operation and maintenance engineer is solved, and the repeated bill receiving phenomenon is reduced;
the method comprises the steps of acquiring and analyzing route information of operation and maintenance personnel with repeated connection list in the past through a big data technology, wherein the operation and maintenance personnel with repeated connection list go to the same destination, so that the superposition degree of a moving route is high, a repeated connection list judging model is established by selecting the superposition degree of the moving route according to the longest superposition route length and the historical repeated connection list as training data, a proper superposition degree threshold value is set according to the moving route data when the historical actual repeated connection list is used, the superposition degree threshold value is compared with the superposition degree of the current route, whether repeated connection list phenomenon possibly occurs at present is estimated, and the accuracy of an estimated result and the effectiveness of sending early warning signals are improved.
Further, in step S3, after receiving the early warning signal, checking the order receiving information of the corresponding operation and maintenance personnel, if checking that the corresponding operation and maintenance personnel repeatedly receives the order, calling the current position information and qualification evaluation information of the corresponding two operation and maintenance personnel, and obtaining that the distance from the current position to the destination of the repeated order of one random operation and maintenance personnel is F 1 The number of orders processed by corresponding operation staff in the past is k, and the operation difficulty coefficient set of the corresponding processed orders is M= { M 1 ，M 2 ，…，M k } according to formula Q 1 =1/F 1 +k+(∑ k e=1 M e ) Calculation of matching degree Q of random one operation and maintenance personnel and current repeated order 1 Wherein M is e Representing the operation and maintenance work difficulty coefficient of the order processed by the e-th operation and maintenance personnel randomly, and obtaining the matching degree of the two operation and maintenance personnel and the current repeated order as Q respectively 1 And Q 2 Comparison of Q 1 And Q 2 Selecting an operation and maintenance person with higher matching degree as an optimal operation and maintenance person to go to an operation and maintenance work destination corresponding to the current repeated order to perform operation and maintenance work;
after the repeated order receiving phenomenon is checked, the most suitable person is needed to complete the repeated order in operation and maintenance personnel for repeated order receiving, the route to the destination and qualification information of the operation and maintenance personnel are combined to select, the shorter the route of the operation and maintenance personnel to the destination is, the faster the operation and maintenance personnel can reach the destination to complete the repeated order, time on the route is saved, the more the number of orders processed by the operation and maintenance personnel is, the richer the operation and maintenance working experience is, the greater the operation and maintenance working difficulty is, the stronger the operation and maintenance working capacity is, the best operation and maintenance personnel are selected by comparing the matching degree of the parameter analysis operation and maintenance personnel, the efficiency of the operation and maintenance work of the repeated order is improved by proper selection, and the operation and maintenance work can be better completed.
Further, in step S4: the method comprises the steps of calling operation and maintenance work order information of the rest non-picked orders except a current repeated order, obtaining a rest order destination position, generating a moving route of a non-optimal operation and maintenance person from the current position to the rest order destination position as a to-be-moved route, comparing the moving route of the non-optimal operation and maintenance person from the current position to the rest order destination position with the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination, taking the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination as an original moving route, screening out to-be-moved routes with overlapping parts with the original moving route from the current position of the non-optimal operation and maintenance person, screening out f to-be-moved routes altogether, and obtaining a overlapping route length set of f to-be-moved routes from the current position of the non-optimal operation and maintenance person to the original moving route as N= { N 1 ，N 2 ，…，N f And the operation and maintenance work difficulty coefficient set which is called to f residual orders is G= { G 1 ，G 2 ，…，G f And the operation and maintenance work difficulty coefficient set for calling the order processed by the non-optimal operation and maintenance personnel in the past is g= { g 1 ，g 2 ，…，g v V represents the number of orders processed by non-optimal operators in the past, and the matching degree P of the remaining random order and the non-optimal operators is calculated according to the following formula c ：
P c =N c +1/[(∑ v u=1 g u )-G c ]；
Wherein c=1, 2, …, f, c represents a route to be moved corresponding to the c-th order, u=1, 2, …, v, u represents the u-th order processed by the non-optimal operation and maintenance personnel in the past, and the matching degree set of the remaining orders and the non-optimal operation and maintenance personnel is obtained as p= { P 1 ，P 2 ，…，P f Comparing the matching degree, and distributing the operation and maintenance work order with the highest matching degree in the rest orders to non-optimal operation and maintenance personnel;
besides completing the processing of repeated orders, proper operation and maintenance work is allocated for the residual personnel receiving the repeated orders, so that the problem that the residual personnel only concentrate on the processing of the repeated orders and return to the original route due to the fact that the order is not received at the moment, and the cost of the operation and maintenance personnel on the route is increased is solved, in the aspect of the selection of the order of the residual personnel, the order corresponding to the moving route with the longer overlapping length of the route of the original repeated order destination from the current position of the residual personnel is selected, the problem that the residual personnel can not timely replace the correct route and even replace the incorrect route in a short time after suddenly receiving the notification of replacing the destination is solved, and the probability that the residual personnel waste excessive time on the route before the operation and maintenance work is reduced; meanwhile, the current residual order processing difficulty and the residual order difficulty difference value processed by the residual personnel in the past are combined to distribute orders, the smaller the difference value is, the closer the processing difficulty of the residual order is to the processing capacity of the personnel, and the proper operation and maintenance work orders are distributed for the residual personnel by combining the parameters, so that the whole operation and maintenance work flow advancing speed is improved, and the operation and maintenance work efficiency of the residual orders is improved.
Compared with the prior art, the invention has the following beneficial effects:
the invention collects and analyzes the route information of operation and maintenance personnel with repeated connection list in the past through big data technology, selects the moving route coincidence degree according to the longest coincidence route length and the historical repeated connection list as training data to establish a repeated connection list judging model, sets a proper coincidence degree threshold according to the moving route data when the historical actual repeated connection list, compares with the coincidence degree of the current route, predicts whether the repeated connection list phenomenon is likely to occur at present, and improves the accuracy of the estimated result and the effectiveness of sending early warning signals;
after checking that the repeated order receiving phenomenon occurs, selecting the most suitable person from operation and maintenance personnel for repeated order receiving, selecting by combining the route to the destination and qualification information of the operation and maintenance personnel, analyzing the matching degree of the operation and maintenance personnel and the repeated order, and selecting the best operation and maintenance personnel by comparing the matching degree, thereby being beneficial to improving the operation and maintenance work efficiency of the repeated order through the suitable selection and helping to better complete the operation and maintenance work;
besides the processing of the repeated order, proper operation and maintenance work is allocated for the residual personnel receiving the repeated order, so that the problem that the residual personnel only concentrate on the processing of the repeated order and return to the original route due to the fact that the order is not received at the moment is avoided, the cost of the operation and maintenance personnel on the route is increased, in the aspect of order selection of the residual personnel, the order corresponding to the moving route with the longer overlapping length with the route of the original repeated order destination is selected from the current position of the residual personnel, the problem that the residual personnel can not timely replace the correct route and even replace the incorrect route in a short time due to the fact that the residual personnel suddenly receives the notification of replacing the destination is avoided, and the probability that excessive time and cost are wasted on the route of the residual personnel before the operation and maintenance work is reduced; meanwhile, the current residual order processing difficulty and the order difficulty difference value processed by the residual personnel in the past are combined to distribute orders, and proper operation and maintenance work orders are distributed to the residual personnel, so that the propulsion speed of the whole operation and maintenance work flow is increased on the whole, and the operation and maintenance work efficiency of the residual orders is improved;
the repeated bill receiving phenomenon can be confirmed without waiting until the operation and maintenance personnel reach the destination, and the repeated bill receiving phenomenon can be found in time in the middle, so that the problem of repeated bill receiving of operation and maintenance engineers is solved, and the repeated bill receiving phenomenon is reduced.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a block diagram of an operation and maintenance duty management system based on big data analysis of the present invention;
FIG. 2 is a flow chart of an operation and maintenance duty management method based on big data analysis.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The invention is further described below with reference to fig. 1-2 and the specific embodiments.
Example 1: as shown in fig. 1, the present embodiment provides an operation and maintenance duty management system based on big data analysis, the system includes: the system comprises a fortune dimension acquisition module, a database, a repeated order judgment module, a repeated order processing module and a fortune dimension personnel management module;
the output end of the operation and maintenance data acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the repeated order judgment module, the repeated order processing module and the operation and maintenance personnel management module, the output end of the repeated order judgment module is connected with the input end of the repeated order processing module, and the output end of the repeated order processing module is connected with the input end of the operation and maintenance personnel management module;
the operation and maintenance work order information and the operation and maintenance personnel information are collected through an operation and maintenance data collection module, and all collected data are transmitted to a database;
storing all collected data through a database;
analyzing a moving route of the operation and maintenance personnel after receiving the repeated receipt through a repeated receipt judging module, and judging whether the repeated receipt appears or not;
checking the judging result through the repeated order processing module, and selecting the optimal operation and maintenance personnel for the operation and maintenance work which is repeatedly checked;
and distributing operation and maintenance work orders to the operation and maintenance personnel with the rest repeated orders through the operation and maintenance personnel management module.
The operation and maintenance data acquisition module comprises an order information acquisition unit, a personnel information acquisition unit and an operation and maintenance personnel positioning unit;
the output ends of the order information acquisition unit, the personnel information acquisition unit and the operation and maintenance personnel positioning unit are connected with the input end of the database;
the order information acquisition unit is used for acquiring the moving route information of the operation and maintenance personnel and all the distributed operation and maintenance work order information when repeated connection of the order appears in the past, and the order information comprises destination information for operation and maintenance work and difficulty information for the operation and maintenance work;
the personnel information acquisition unit is used for acquiring qualification evaluation information of operation and maintenance personnel, wherein the qualification evaluation information comprises order quantity information processed by the operation and maintenance personnel in the past and operation and maintenance work difficulty information corresponding to the order;
the operation and maintenance personnel positioning unit is used for positioning all operation and maintenance personnel receiving the orders in real time and acquiring real-time position information of the operation and maintenance personnel.
The repeated receipt judgment module comprises a track generation unit, a track coincidence analysis unit and a repeated receipt judgment unit;
the input end of the track generating unit is connected with the output end of the database, the output end of the track generating unit is connected with the input end of the track coincidence analysis unit, and the output end of the track coincidence analysis unit is connected with the input end of the repeated connection list judging unit;
the track generation unit is used for retrieving the real-time position information of all the operation and maintenance personnel receiving the orders and generating a moving route of the corresponding operation and maintenance personnel according to the real-time position;
the track coincidence analysis unit is used for analyzing the coincidence degree between the moving paths;
the repeated order judgment unit is used for comparing the overlapping degree, judging whether the repeated order phenomenon occurs currently according to the comparison result, and sending an early warning signal to the repeated order processing module when judging that the repeated order phenomenon occurs currently.
The repeated order processing module comprises a repeated order checking unit and an optimal personnel selecting unit;
the input end of the repeated connection list checking unit is connected with the output end of the repeated connection list judging unit, and the repeated connection list checking unit and the output end of the database are connected with the input end of the optimal personnel selecting unit;
the repeated order checking unit is used for checking whether repeated order phenomenon occurs at present after receiving the early warning signal;
and the optimal person selection unit is used for selecting the optimal person from the operation and maintenance personnel for repeatedly taking the order to go to the operation and maintenance work destination corresponding to the current order to carry out operation and maintenance work when checking that the repeated order appears currently.
The operation and maintenance personnel management module comprises a residual order information retrieving unit and a residual personnel distributing unit;
the input end of the residual order information calling unit is connected with the output end of the database, and the output ends of the residual order information calling unit and the optimal personnel selection unit are connected with the residual personnel distribution unit;
the residual order information retrieving unit is used for retrieving all order information which is not received except the repeated order and is left to the residual personnel distributing unit;
the remaining person allocation unit is used for allocating operation and maintenance work orders to operation and maintenance persons of the repeated connection orders which are left except the optimal person.
Example 2: as shown in fig. 2, the present embodiment provides an operation and maintenance duty management method based on big data analysis, which is implemented based on the management system in the embodiment, and specifically includes the following steps:
s1: collecting operation and maintenance work order information and operation and maintenance personnel information, collecting the moving route of operation and maintenance personnel when the repeated order receiving phenomenon appears in the past, displaying the moving route by using a GIS map, and collecting the longest superposition route length d of the operation and maintenance personnel which randomly and repeatedly receive the order in the past in the process of going to the same destination i The route length of two operation and maintenance staff to the corresponding destination is L=20 and H=22 respectively, and the coincidence degree between the corresponding two operation and maintenance staff moving routes is w i Wherein w is i =[(d i /L)+(d i /H)]When the repeated single-receiving phenomenon appears in different times in the past, the longest overlapped route length set of two operation and maintenance personnel randomly receiving the repeated single-receiving is d= { d when the operation and maintenance personnel go to the same destination 1 ，d 2 ，d 3 The overlapping degree set between the moving paths of the operation and maintenance personnel corresponding to the repeated connection list is w= { w } = {15, 20, 16} 1 ，w 2 ，w 3 } = {0.72,0.82,0.75}, collect all currently served operation and maintenance work order information: destination information of operation and maintenance work and difficulty information of operation and maintenance work are carried out, order quantity information processed by operation and maintenance personnel who receive the current order and operation and maintenance work difficulty information corresponding to the order are collected, real-time positioning is carried out on all operation and maintenance personnel who receive the current order,acquiring real-time position information of operation and maintenance personnel;
s2: analyzing the overlapping degree of the moving routes of the operation and maintenance personnel after receiving the bill, judging whether repeated bill receiving occurs, calling the real-time position information of all operation and maintenance personnel currently receiving the bill, generating the moved routes of the operation and maintenance personnel, acquiring m overlapping routes in the moved routes of two random operation and maintenance personnel, acquiring the two end point transverse coordinates of one random overlapping route to be a and b respectively, and corresponding overlapping route equation to be y=f (x) (a is less than or equal to x is less than or equal to b), and according to the formula D j =∫ b a (1+y ’2 ) 1/2 dx calculation of random one coinciding route length D j Calculating the length of m overlapped routes in the same way to obtain the longest overlapped route length D in the m routes max =7, the lengths of the moved routes corresponding to the two operation staff are obtained as r=10 and z=12, respectively, according to the formula w= [ (D) max /R)+(D max /Z)]And (2) calculating to obtain the coincidence degree W (approximately 0.64) between the current moving routes of the two operation and maintenance personnel, performing straight line fitting on data points (15,0.72), (20,0.82) and (16,0.75), and establishing a repeated connection list judgment model as follows: y=c 1 *X+C 2 Wherein C 1 And C 2 Representing the fitting coefficients according to formula C 1 =[n∑ n i=1 (d i *w i )-∑ n i=1 d i ∑ n i=1 w i ]/[n∑ n i=1 (d i ) 2 -(∑ n i=1 d i ) 2 ]、C 2 =[∑ n i=1 w i -C 1 ∑ n i=1 d i ]Respectively calculating/n to obtain C 1 ≈0.02、C 2 Approximately 0.42, D max Substituting the repeated single judgment model to let X=D max =7, resulting in a coincidence degree threshold of C 1 *D max +C 2 =0.56, compare W and C 1 *D max +C 2 ：W>C 1 *D max +C 2 Judging that the repeated single-connection phenomenon occurs to the corresponding two operation and maintenance personnel, and sending an early warning signal;
s3: checking the judging result, if the weight is increasedA multiplex bill, selecting the best operation and maintenance personnel for the operation and maintenance work of the repeated bill, checking the bill receiving information of the corresponding operation and maintenance personnel after receiving the early warning signal, if the repeated bill receiving of the corresponding operation and maintenance personnel is checked, calling the current position information and qualification evaluation information of the corresponding two operation and maintenance personnel, and obtaining that the path from the current position to the repeated order destination of a random operation and maintenance personnel is F 1 =10, the number of orders processed by the corresponding operation staff in the past is k=7, and the operation work difficulty coefficient set of the corresponding processed orders is m= { M 1 ，M 2 ，M 3 ，M 4 ，M 5 ，M 6 ，M 7 } = {0.8,0.5,0.7,0.6,0.5,0.8,0.7}, according to formula Q 1 =1/F 1 +k+(∑ k e=1 M e ) Calculation of matching degree Q of random one operation and maintenance personnel and current repeated order 1 Approximately 7.76, where M e Representing the operation and maintenance work difficulty coefficient of the order processed by the e-th operation and maintenance personnel randomly, and obtaining the matching degree of the two operation and maintenance personnel and the current repeated order as Q respectively 1 =7.76、Q 2 =6.88, compare Q 1 And Q 2 ，Q 1 >Q 2 Selecting a first operation and maintenance person as an optimal operation and maintenance person to go to an operation and maintenance work destination corresponding to the current repeated order to carry out operation and maintenance work;
if W is less than or equal to C 1 *D max +C 2 Judging that the repeated single-connection phenomenon does not occur to the corresponding two operation and maintenance personnel;
s4: the operation and maintenance work order information of the rest non-accepted orders except the current repeated order is called, the position of the rest order destination is obtained, a moving route of a non-optimal operation and maintenance person from the current position to the position of the rest order destination is generated to serve as a route to be moved, the moving route of the non-optimal operation and maintenance person from the current position to the position of the rest order destination is compared with the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination, the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination serves as an original moving route, and the part to be overlapped with the original moving route from the current position of the non-optimal operation and maintenance person is screened outThe moving route is screened out, f routes to be moved are screened out, and the length set of the overlapping routes of the f routes to be moved and the original moving route from the current position of the non-optimal operation and maintenance personnel is N= { N 1 ，N 2 ，…，N f And the operation and maintenance work difficulty coefficient set which is called to f residual orders is G= { G 1 ，G 2 ，…，G f And the operation and maintenance work difficulty coefficient set for calling the order processed by the non-optimal operation and maintenance personnel in the past is g= { g 1 ，g 2 ，…，g v V represents the number of orders that non-optimal operators have previously processed, according to equation P c =N c +1/[(∑ v u=1 g u )-G c ]Calculating the matching degree P of the remaining random order and the non-optimal operation and maintenance personnel c Wherein c=1, 2, …, f, c represents a route to be moved corresponding to the c-th order, u=1, 2, …, v, u represents the u-th order processed by the non-optimal operation and maintenance personnel in the past, and the matching degree set of the remaining orders and the non-optimal operation and maintenance personnel is p= { P 1 ，P 2 ，…，P f Comparing the matching degree, and distributing the operation and maintenance work order with the highest matching degree in the rest orders to non-optimal operation and maintenance personnel;
for example: screening out 3 routes to be moved in total, and obtaining that the length set of the coincident route of the 3 routes to be moved from the current position of the non-optimal operation and maintenance personnel and the original moving route is N= { N 1 ，N 2 ，N 3 The operation and maintenance work difficulty coefficient set called to the residual order is G= { G = {12, 10,5} 1 ，G 2 ，G 3 The operation and maintenance work difficulty coefficient set of the order processed by the non-optimal operation and maintenance personnel in the past is called as g= { g } = {0.8,0.4,0.7} 1 ，g 2 ，g 3 ，g 4 ，g 5 The matching degree set of the residual order and the non-optimal operation and maintenance personnel is obtained as P= { P } = {0.4,0.5,0.7,0.6,0.5}, wherein the matching degree set of the residual order and the non-optimal operation and maintenance personnel is obtained 1 ，P 2 ，P 3 And (3) comparing the matching degree with 11.96 and 19.14,5.75, wherein the order with the highest matching degree is the second order, and distributing the second operation and maintenance work order for non-optimal operation and maintenance personnel.
Finally, it should be noted that: the foregoing is merely a preferred example of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An operation and maintenance value duty management system based on big data analysis is characterized in that: the system comprises: the system comprises a fortune dimension acquisition module, a database, a repeated order judgment module, a repeated order processing module and a fortune dimension personnel management module;
the output end of the operation and maintenance data acquisition module is connected with the input end of the database, the output end of the database is connected with the input ends of the repeated order receiving judgment module, the repeated order processing module and the operation and maintenance personnel management module, the output end of the repeated order receiving judgment module is connected with the input end of the repeated order processing module, and the output end of the repeated order processing module is connected with the input end of the operation and maintenance personnel management module;
collecting operation and maintenance work order information and operation and maintenance personnel information through the operation and maintenance data collecting module, and transmitting all collected data to the database;
storing all the collected data through the database;
analyzing a moving route of the operation and maintenance personnel after receiving the repeated receipt by the repeated receipt judging module, and judging whether the repeated receipt appears or not;
checking the judging result through the repeated order processing module, and selecting the optimal operation and maintenance personnel for the operation and maintenance work of the repeated order;
and distributing operation and maintenance work orders to the operation and maintenance personnel with the rest repeated orders through the operation and maintenance personnel management module.
2. An operation and maintenance value service management system based on big data analysis according to claim 1, wherein: the operation and maintenance data acquisition module comprises an order information acquisition unit, a personnel information acquisition unit and an operation and maintenance personnel positioning unit;
the output ends of the order information acquisition unit, the personnel information acquisition unit and the operation and maintenance personnel positioning unit are connected with the input end of the database;
the order information acquisition unit is used for acquiring the moving route information of the operation and maintenance personnel and all the distributed operation and maintenance work order information when repeated connection of the order appears in the past, and the order information comprises destination information of operation and maintenance work and difficulty information of the operation and maintenance work;
the personnel information acquisition unit is used for acquiring qualification evaluation information of operation and maintenance personnel, wherein the qualification evaluation information comprises order quantity information processed by the operation and maintenance personnel in the past and operation and maintenance work difficulty information corresponding to the order;
the operation and maintenance personnel positioning unit is used for positioning all operation and maintenance personnel receiving the orders in real time and acquiring real-time position information of the operation and maintenance personnel.
3. An operation and maintenance value service management system based on big data analysis according to claim 1, wherein: the repeated receipt judgment module comprises a track generation unit, a track coincidence analysis unit and a repeated receipt judgment unit;
the input end of the track generating unit is connected with the output end of the database, the output end of the track generating unit is connected with the input end of the track coincidence analysis unit, and the output end of the track coincidence analysis unit is connected with the input end of the repeated receipt judgment unit;
the track generation unit is used for retrieving the real-time position information of all the operation and maintenance personnel receiving the orders and generating a moving route of the corresponding operation and maintenance personnel according to the real-time position;
the track coincidence analysis unit is used for analyzing the coincidence degree between the moving paths;
the repeated order judging unit is used for comparing the superposition degree, judging whether the repeated order phenomenon occurs currently according to the comparison result, and sending an early warning signal to the repeated order processing module when judging that the repeated order phenomenon occurs currently.
4. An operation and maintenance value service management system based on big data analysis according to claim 3, wherein: the repeated order processing module comprises a repeated order checking unit and an optimal personnel selecting unit;
the input end of the repeated order taking checking unit is connected with the output end of the repeated order taking judging unit, and the output ends of the repeated order taking checking unit and the database are connected with the input end of the optimal personnel selecting unit;
the repeated order receiving checking unit is used for checking whether repeated order phenomenon occurs currently or not after receiving the early warning signal;
and the optimal person selection unit is used for selecting the optimal person from the operation and maintenance personnel repeatedly receiving the repeated order to go to the operation and maintenance work destination corresponding to the current order to carry out operation and maintenance work when checking that the repeated order appears currently.
5. An operation and maintenance value service management system based on big data analysis according to claim 4, wherein: the operation and maintenance personnel management module comprises a residual order information retrieving unit and a residual personnel distributing unit;
the input end of the residual order information calling unit is connected with the output end of the database, and the output ends of the residual order information calling unit and the optimal personnel selection unit are connected with the residual personnel distribution unit;
the residual order information retrieving unit is used for retrieving all order information which is not received except the repeated order and is remained to the residual personnel distributing unit;
the remaining personnel allocation unit is used for allocating operation and maintenance work orders to operation and maintenance personnel for the repeated connection orders remaining except the optimal personnel.
6. An operation and maintenance value service management method based on big data analysis is characterized in that: the method comprises the following steps:
s1: collecting operation and maintenance work order information and operation and maintenance personnel information;
s2: analyzing the overlapping degree of the moving routes after the operation and maintenance personnel receive the bill, and judging whether repeated bill receiving occurs or not;
s3: checking the judging result, and if the repeated receipt appears, selecting the best operation and maintenance personnel for the operation and maintenance work of the repeated receipt;
s4: and distributing operation and maintenance work orders for operation and maintenance personnel with the rest repeated orders.
7. The operation and maintenance value service management method based on big data analysis according to claim 6, wherein: in step S1: collecting the moving route of the operation and maintenance personnel when the repeated single-connection phenomenon appears in the past, displaying the moving route by using a GIS map, and collecting the longest overlapped route length d of the operation and maintenance personnel in the past with two random repeated single-connection processes in the process of going to the same destination i The lengths of routes of the two operation and maintenance personnel to the corresponding destination are L and H respectively, and the superposition degree between the corresponding two operation and maintenance personnel moving routes is w i Wherein w is i =[(d i /L)+(d i /H)]When the repeated single-receiving phenomenon appears in different times in the past, the longest superposition route length set of two operation and maintenance personnel randomly receiving the repeated single-receiving is d= { d in the process of going to the same destination 1 ，d 2 ，…，d i ，…，d n The superposition degree set between the moving routes of the operation and maintenance personnel corresponding to the repeated connection list is w= { w 1 ，w 2 ，…，w i ，…，w n N represents the number of times of repeated order receiving phenomenon, and collecting the information of all the current distributed operation and maintenance work orders: and acquiring destination information of operation and maintenance work and difficulty information of the operation and maintenance work, acquiring order quantity information processed by operation and maintenance personnel who receive the current order in the past and operation and maintenance work difficulty information corresponding to the order, positioning all operation and maintenance personnel who receive the current order in real time, and acquiring real-time position information of the operation and maintenance personnel.
8. The operation and maintenance value service management method based on big data analysis according to claim 7, wherein: in step S2: invoking the currentGenerating the moving routes of the operation and maintenance personnel by real-time position information of all the operation and maintenance personnel who receive the order, acquiring m coincident routes in the moving routes of the two operation and maintenance personnel at random, acquiring two end point abscissa of one coincident route at random as a and b respectively, and corresponding coincident route equation as y=f (x) (a is less than or equal to x is less than or equal to b), and according to a formula D j =∫ b a (1+y ’2 ) 1/ 2 dx calculation of random one coinciding route length D j Calculating the length of m overlapped routes in the same way to obtain the longest overlapped route length D in the m routes max The lengths of the moved routes corresponding to the two operation and maintenance personnel are respectively R and Z, and the length of the moved routes is obtained according to the formula W= [ (D) max /R)+(D max /Z)]Calculating to obtain the coincidence degree W between the current moving routes of two operation and maintenance staff, and calculating the data point { (d) 1 ，w 1 ），（d 2 ，w 2 ），…，（d n ，w n ) Performing straight line fitting, and establishing a repeated connection list judgment model as follows: y=c 1 *X+C 2 Wherein C 1 And C 2 Representing the fitting coefficient, D max Substituting the repeated single judgment model to let X=D max Obtaining the overlapping degree threshold value as C 1 *D max +C 2 Comparison of W and C 1 *D max +C 2 : if W is less than or equal to C 1 *D max +C 2 Judging that the repeated single-connection phenomenon does not occur to the corresponding two operation and maintenance personnel; if W is>C 1 *D max +C 2 And judging that the repeated single-connection phenomenon occurs to the corresponding two operation and maintenance personnel, and sending an early warning signal.
9. The operation and maintenance value service management method based on big data analysis according to claim 8, wherein: in step S3, after receiving the early warning signal, checking the order receiving information of the corresponding operation and maintenance personnel, if checking the repeated order receiving of the corresponding operation and maintenance personnel, calling the current position information and qualification evaluation information of the corresponding two operation and maintenance personnel, and obtaining the route from the current position to the repeated order destination of a random operation and maintenance personnel as F 1 Corresponding to the number of orders processed by operation and maintenance personnel in the pastThe operation and maintenance work difficulty coefficient set of the corresponding processed order is M= { M 1 ，M 2 ，…，M k } according to formula Q 1 =1/F 1 +k+(∑ k e=1 M e ) Calculation of matching degree Q of random one operation and maintenance personnel and current repeated order 1 Wherein M is e Representing the operation and maintenance work difficulty coefficient of the order processed by the e-th operation and maintenance personnel randomly, and obtaining the matching degree of the two operation and maintenance personnel and the current repeated order as Q respectively 1 And Q 2 Comparison of Q 1 And Q 2 And selecting an operation and maintenance person with higher matching degree as an optimal operation and maintenance person to go to an operation and maintenance work destination corresponding to the current repeated order to carry out operation and maintenance work.
10. The operation and maintenance value service management method based on big data analysis according to claim 7, wherein: in step S4: the method comprises the steps of calling operation and maintenance work order information of the rest non-picked orders except a current repeated order, obtaining a rest order destination position, generating a moving route of a non-optimal operation and maintenance person from the current position to the rest order destination position as a to-be-moved route, comparing the moving route of the non-optimal operation and maintenance person from the current position to the rest order destination position with the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination, taking the moving route of the non-optimal operation and maintenance person from the current position to the repeated order destination as an original moving route, screening out to-be-moved routes with overlapping parts with the original moving route from the current position of the non-optimal operation and maintenance person, screening out f to-be-moved routes altogether, and obtaining a overlapping route length set of f to-be-moved routes from the current position of the non-optimal operation and maintenance person to the original moving route as N= { N 1 ，N 2 ，…，N f And the operation and maintenance work difficulty coefficient set which is called to f residual orders is G= { G 1 ，G 2 ，…，G f And the operation and maintenance work difficulty coefficient set for calling the order processed by the non-optimal operation and maintenance personnel in the past is g= { g 1 ，g 2 ，…，g v V represents the number of orders that the non-optimal operation staff has previously processedCalculating the matching degree P of the remaining random order and the non-optimal operation and maintenance personnel according to the following formula c ：
P c =N c +1/[(∑ v u=1 g u )-G c ]；
Wherein c=1, 2, …, f, c represents a route to be moved corresponding to the c-th order, u=1, 2, …, v, u represents the u-th order processed by the non-optimal operation and maintenance personnel in the past, and the matching degree set of the remaining orders and the non-optimal operation and maintenance personnel is obtained as p= { P 1 ，P 2 ，…，P f And (3) comparing the matching degree, and distributing the operation and maintenance work orders with the highest matching degree in the rest orders to non-optimal operation and maintenance personnel.
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