Service management method for engineering maintenance personnel

Abstract

The invention discloses a service management method for engineering maintenance personnel, and the method comprises the steps: obtaining a task starting point and a task ending point according to a work order task of the engineering maintenance personnel, and determining a task plan path and plan arrival time through a map API; acquiring position data of the engineering maintenance personnel, comparing the task plan path with the position data to obtain an offset distance, acquiring actual arrival time of the engineering maintenance personnel to the task end point, and comparing the actual arrival time with the plan arrival time to obtain delay time; and responding to the customer score, and combining the offset distance and the delay time to obtain a work order task score of the project maintenance personnel. Through combination of dynamic path monitoring, delay time quantification and customer scoring, service quality can be scientifically evaluated, intelligent decision is supported, service efficiency is improved, and a full-process and quantifiable intelligent management solution is provided for engineering maintenance service.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of service management, and particularly relates to a service management method for engineering maintenance personnel. BACKGROUND

[0002] In the field of engineering maintenance services, with the diversification of service demand and the continuous improvement of customer requirements for service quality, how to efficiently manage the work flow of engineering maintenance personnel and ensure that they complete tasks on time and with quality has become a key problem for the development of the industry.

[0003] Traditional service management modes rely on manual recording and post-feedback, and have the following pain points. First, path monitoring is insufficient. Engineering maintenance personnel need to go to designated locations according to work order tasks, but existing technologies cannot track the deviation of their actual driving paths from preset paths in real time, which makes it impossible to verify whether they have executed tasks according to the planned route. In the case of delayed arrival, it is difficult to determine whether it is due to subjective reasons of the engineering maintenance personnel or unreasonable task allocation, so it is difficult to accurately evaluate the engineering maintenance personnel and to optimize and improve the system.

[0004] Second, time management is extensive. Existing technologies usually only judge task completion through static clocking (such as uploading time after arrival at the destination), which cannot dynamically calculate delay time and lacks intelligent response mechanisms for external factors such as traffic congestion and weather. In the case of low customer ratings, it is difficult to determine whether it is due to the delayed arrival of the engineering maintenance personnel or the low service attitude or technical level of the engineering maintenance personnel.

[0005] Third, the service quality evaluation is single, relying only on customer feedback ratings or the impression ratings of management personnel, which leads to strong subjectivity of evaluation results and difficulty in forming a closed-loop management, affecting the pertinence of service improvement.

[0006] In the case of disconnection between customer ratings, delay time and path deviation, it is difficult to reflect the real service quality of the engineering maintenance personnel and to take targeted improvement measures. SUMMARY

[0007] The application provides a service management method for engineering maintenance personnel, which solves the problem that in the case of disconnection between customer ratings, delay time and path deviation, it is difficult to reflect the real service quality of the engineering maintenance personnel and to take targeted improvement measures.

[0008] The technical scheme adopted by the application is:

[0009] A service management method for engineering maintenance personnel, comprising:

[0010] According to the work order task of the engineering maintenance personnel, a task starting point and a task ending point are obtained, a task plan path and a plan arrival time are determined through a map API;

[0011] Position data of the engineering maintenance personnel is obtained, the task plan path and the position data are compared to obtain a deviation distance, actual arrival time of the engineering maintenance personnel at the task ending point is obtained, and the actual arrival time and the plan arrival time are compared to obtain a delay time;

[0012] In response to a customer score, the deviation distance and the delay time are combined to obtain a work order task score of the engineering maintenance personnel.

[0013] The application provides a service management method for engineering maintenance personnel, and has the following additional technical features:

[0014] Before determining the work order task of the engineering maintenance personnel, the following steps are further included:

[0015] The engineering maintenance personnel who do not execute the work order task are screened to obtain corresponding position data of the engineering maintenance personnel;

[0016] According to the distance between the position data and the task ending point, the historical work order task score of the engineering maintenance personnel and the task level of the work order task are combined to determine the engineering maintenance personnel who execute the work order task.

[0017] A task starting point and a task ending point are obtained, a task plan path and a plan arrival time are determined through a map API, and specifically:

[0018] According to the task starting point and the task ending point, a map API is called, and based on real-time traffic, weather and traffic restriction rules, the arrival time of each path in the path set is determined;

[0019] According to the arrival time, the task plan path and the plan arrival time are determined.

[0020] The task plan path and the position data are compared to obtain a deviation distance, and specifically:

[0021] According to a mobile device, the position data is obtained through GPS / Beidou / cellular network, the task plan path and the position data are compared to obtain a deviation distance;

[0022] If the mobile device is offline for more than 5 minutes, a device exception alarm is triggered to notify the operation and maintenance personnel.

[0023] The actual arrival time of the engineering maintenance personnel at the task ending point is obtained, and specifically:

[0024] In response to the photo check-in of the engineering maintenance personnel, wherein the photo has a time stamp and a geographical location watermark;

[0025] Verify the matching of the geographical location watermark and the task end point. If the deviation between the two is less than or equal to 50 m, it is confirmed that they match, and the actual arrival time is obtained through the time stamp;

[0026] Otherwise, it is confirmed that they do not match, marked as a false check-in, and the operation and maintenance personnel are notified.

[0027] In response to the customer score, the offset distance, and the delay time, the work order task score of the engineering maintenance personnel is obtained, specifically:

[0028] According to the offset distance, when the offset distance is less than or equal to 500 m, it is judged that there is no offset, and a position reference score is set,

[0029] When the offset distance is greater than 500 m, it is judged that there is an offset, and the position reference score is adjusted to obtain a position trajectory score, which is negatively correlated with the offset distance;

[0030] According to the delay time, when the delay time is greater than or equal to -10 minutes and less than or equal to 10 minutes, it is judged that there is no delay, and a time reference score is set,

[0031] When the delay time is less than -10 minutes, it is judged that there is an advance, and the time reference score is adjusted to obtain a delay time score, which is negatively correlated with the delay time,

[0032] When the delay time is greater than 10 minutes, it is judged that there is a delay, and the time reference score is adjusted to obtain a delay time score, which is negatively correlated with the delay time;

[0033] In response to the customer evaluation, a customer score is obtained;

[0034] According to the customer score, in combination with the position trajectory score and the delay time score, the work order task score is obtained.

[0035] The work order task score is obtained, specifically:

[0036] According to the customer score, the position trajectory score, and the delay time score, normalization processing is performed, and a weighted work order task score is obtained;

[0037] According to the work order task score, when the work order task score is greater than or equal to 0.85, it is judged to be excellent,

[0038] When the work order task score is less than 0.85 and greater than or equal to 0.70, it is judged to be good,

[0039] When the work order task score is less than 0.70, greater than or equal to 0.50, it is judged as qualified,

[0040] When the work order task score is less than 0.50, it is judged as unqualified.

[0041] After obtaining the work order task score, further comprising:

[0042] After being judged as unqualified for a plurality of times in succession, reason analysis is performed,

[0043] If the normalized customer score and the position trajectory score are less than 0.50 for a plurality of times, it is determined as an engineer reason;

[0044] If the normalized delay time score is less than 0.50 for a plurality of times, it is determined as a system reason, and the engineering maintenance personnel configuration is adjusted according to the heat map of unqualified work order tasks.

[0045] The application further provides a storage medium,

[0046] The storage medium has a computer program stored thereon, and the computer program is executed to realize the steps of the service management method for engineering maintenance personnel.

[0047] The application further provides a processing device, comprising:

[0048] A memory for storing a computer program;

[0049] A processor for executing the computer program to realize the steps of the service management method for engineering maintenance personnel.

[0050] Due to the adoption of the above technical solutions, the application has the following beneficial effects:

[0051] 1. In the application, the best path and the planned arrival time are calculated based on real-time traffic, weather and traffic restriction rules through a map API. The actual path of the engineering maintenance personnel is compared with the preset path in real time to obtain the offset distance. The driving path of the engineer is tracked in real time to avoid efficiency loss caused by subjective detours or navigation errors and ensure that the task is performed according to the optimal route. The planned arrival time is calculated in combination with real-time traffic and weather data to reduce the risk of delay caused by static path planning and improve the efficiency of task completion. The abnormal path behavior is identified through the offset distance threshold (such as 500 meters) to correct the deviation in time and avoid wasting time due to detours.

[0052] The actual arrival time of the engineer at the task end point is obtained, compared with the planned arrival time, and the delay time is calculated. The time quantified delay is combined with the offset distance to distinguish between reasonable delay caused by external factors (such as traffic congestion) and abnormality caused by subjective behavior of the engineer (such as detours).

[0053] The customer score, offset distance and delay time are combined to calculate the work order task score. The customer subjective feedback is combined with objective data (path efficiency, time accuracy) to avoid the deviation of single dimension evaluation, and the scientificity and reliability of the score are improved. The work order task score is generated, the comprehensive performance of the engineer is intuitively reflected, the problem root (such as path deviation, delay timeout) is quickly located according to the score result (such as unqualified work order), and the subsequent training or system optimization is guided.

[0054] In summary, the present application solves the core problems of insufficient path monitoring, extensive time management and disconnection of service quality evaluation in the prior art through the innovative combination of dynamic path monitoring, delay time quantification and multi-dimensional scoring, can scientifically evaluate the service quality, support intelligent decision-making, improve the service efficiency, and provides a full-process and quantifiable intelligent management solution for engineering maintenance service. BRIEF DESCRIPTION OF DRAWINGS

[0055] The accompanying drawings, which are included to provide a further understanding of the present application, form a part of the present application and illustrate the illustrative embodiments of the present application and together with the description serve to explain the present application. In the drawings:

[0056] Figure 1 The flowchart of the service management method for engineering maintenance personnel according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0057] In order to more clearly illustrate the overall concept of the present application, the following will be described in detail with reference to the accompanying drawings.

[0058] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be practiced in other ways different from those described herein, therefore, the scope of protection of the present application is not limited by the specific embodiments disclosed below.

[0059] As shown in Figure 1 A service management method for engineering maintenance personnel, comprising:

[0060] S100: According to the work order task of the engineering maintenance personnel, the task starting point and the task ending point are obtained, and the task plan path and the plan arrival time are determined through the map API.

[0061] The core purpose of this step is to dynamically plan the optimal path and the plan arrival time of the engineering maintenance personnel through the map API, so as to provide a scientific basis for subsequent task execution, and solve the problems of insufficient path monitoring and extensive time management in the traditional service management mode.

[0062] Obtain the task starting point and the task ending point. The task starting point (the current location of the engineer) and the task ending point (the address of the customer) are extracted from the work order task. Specifically, the engineer is currently located at point A and needs to go to point B to perform the maintenance task.

[0063] Using the Gaode, Baidu or Google Maps API, the path is calculated according to the task starting point and the task ending point. According to the preset path selection rule (for example, the shortest path or the earliest arrival time), the task plan path and the plan arrival time are determined.

[0064] The task plan path serves as the basis for subsequent deviation distance calculation, and the plan arrival time serves as the basis for subsequent delay time calculation. In addition, the customer can view the task plan path and the estimated arrival time of the engineer through the system, thereby enhancing the sense of trust.

[0065] For example, the time consumption of the three paths returned by the map API is 30 minutes, 35 minutes and 40 minutes respectively. The 30-minute path is selected as the task plan path, and the plan arrival time is 30 minutes after the start of the task.

[0066] This step solves the problems of insufficient path monitoring and extensive time management in the traditional service management mode through dynamic path planning and time estimation of the map API.

[0067] S200: Obtain the location data of the engineering maintenance personnel, compare the task plan path and the location data to obtain the deviation distance, obtain the actual arrival time of the engineering maintenance personnel at the task ending point, and compare the actual arrival time and the plan arrival time to obtain the delay time.

[0068] The core purpose of this step is to monitor the deviation of the actual path and the plan path of the engineering maintenance personnel in real time, and to quantify the time deviation of the engineering maintenance personnel in reaching the task ending point, thereby providing a data basis for subsequent service quality evaluation and abnormal processing.

[0069] Obtain the location data, and obtain the location data (latitude and longitude coordinates, time stamp) of the engineering maintenance personnel in real time through the GPS / Beidou / cellular network of the mobile device (smartphone or dedicated terminal). Every minute or dynamically adjusted according to the network state (such as encrypted collection during congestion). The location data is uploaded to the central server and stored in association with the work order ID and the engineer ID.

[0070] Compare the plan path and the actual path. The plan path is the optimal path generated in the foregoing step (based on the map API), and the actual path is the actual driving trajectory drawn according to the real-time location data of the engineer. The Haversine formula or the path comparison function of the map API is used to calculate the deviation distance between the actual path and the preset path.

[0071] It can be understood that the traditional method relies on static clock-in (such as uploading the location after arriving at the destination), which cannot verify whether the engineer performs the task according to the planned route. The engineer may forge the clock-in record, but actually does not go to the task site according to the preset path. The present application avoids wasting time due to detours or navigation errors through real-time path deviation detection, and reduces disputes caused by subjective judgment (such as "late").

[0072] The actual arrival time is obtained, which is the time when the engineer arrives at the task end point. The delay time is obtained by the actual arrival time-plan arrival time.

[0073] Through the offset distance and the delay time data, the root cause of the problem (such as delay caused by the engineer detouring, delay caused by traffic congestion) is located. Historical data is summarized, common delay patterns are analyzed, and targeted strategies are taken for optimization (such as engineer training, engineer resource allocation optimization).

[0074] This step solves the problems of insufficient path monitoring, extensive time management, and slow abnormal response in the traditional service management mode through the innovative combination of real-time path comparison, time deviation quantification, and automatic early warning.

[0075] S300: In response to the customer score, the offset distance, and the delay time, a work order task score of the engineering maintenance personnel is obtained.

[0076] The core purpose of this step is to generate a work order task score of the engineering maintenance personnel through comprehensive analysis of the customer score, path deviation (offset distance), and time deviation (delay time), so as to realize scientific quantitative evaluation of the service quality.

[0077] The customer score is obtained, which is filled in by the customer through the App or the short message (three dimensions of service efficiency, service attitude, and service quality).

[0078] The path deviation is analyzed, and the offset distance score is obtained according to the offset distance. It can be understood that the smaller the offset distance is, the higher the offset distance score is. Similarly, the time deviation is analyzed, and the delay time score is obtained according to the delay time. The smaller the delay time is, the higher the delay time score is.

[0079] It should be noted that the customer score is generally set to 1-5 points, and the offset distance score and the delay time score can be 10 points or 100 points, which is not limited by the present application.

[0080] Because the customer score, the offset distance score, and the delay time score are different, the normalization is needed before the work order task scoring, and then the weighting is obtained. Through the combination of objective data (path deviation, time deviation) and subjective feedback (customer score), the artificial bias is avoided, and the scientificity and reliability of the evaluation are improved. In addition, through the score decomposition (such as customer score, position trajectory score, and delay time score), the problem root (such as path deviation and low engineer efficiency) is quickly identified, and the accurate problem positioning and improvement are supported.

[0081] The multi-dimension integration of the customer score, the path deviation, and the time deviation solves the core problems of high subjectivity, difficult problem positioning, and poor improvement targeting in the traditional service quality evaluation.

[0082] As a preferred embodiment of the present application, before determining the work order task of the engineering maintenance personnel, the method further comprises:

[0083] The engineering maintenance personnel who do not execute the work order task are screened, and the position data corresponding to the engineering maintenance personnel is obtained.

[0084] The engineering maintenance personnel who execute the work order task are determined according to the distance between the position data and the task terminal point, the historical work order task score of the engineering maintenance personnel, and the task level of the work order task.

[0085] The core purpose of the embodiment is to scientifically select the most suitable engineering maintenance personnel through the multi-dimension screening and matching strategy before the work order task is assigned, so as to optimize the resource allocation, improve the task execution efficiency, and improve the service quality.

[0086] The list of engineers who do not execute the task is screened by excluding the engineers who are executing the task or are in the dormant state.

[0087] The real-time position (longitude and latitude coordinates) of each candidate engineer is obtained through the mobile device (GPS / Beidou / cellular network), the straight-line distance between the current position of the candidate engineer and the task terminal point is calculated by using the Haversine formula (or the actual driving distance is obtained through the map API), and the distance weight accounts for 50% (for example, the closer the distance, the higher the priority). The engineer closest to the distance is preferentially assigned, the distance consumption is reduced, and the response speed is improved.

[0088] The weight distribution is adjusted according to the task emergency degree (such as ordinary maintenance and emergency fault), for example: in the high-priority task, the historical score weight is increased to 40%, and the distance weight is reduced to 30%.

[0089] Extract the past work order task score of the engineer from the historical work order record, get the mean score, high priority task requirement score >= 0.80, ordinary task requirement score >= 0.65, to re-screen the engineering maintenance personnel according to the task priority. Ensure that the high priority task is executed by a high performance engineer, and reduce the customer complaint rate.

[0090] The distance is normalized and weighted with the mean score to determine the engineering maintenance personnel executing the work order task. Through the multi-dimensional weighting model (distance, historical score, task level), dynamic balance is achieved, subjective decision bias is avoided, and inefficient scheduling (such as assigning a low-scoring engineer far away) is avoided.

[0091] The present embodiment solves the core problems of single-dimensional dependence, low response efficiency and unstable service quality in traditional resource allocation through a multi-dimensional weighting decision model, and realizes the scientificity of resource allocation.

[0092] As a preferred embodiment of the present application, the task starting point and task ending point are obtained, and the task planning path and planned arrival time are determined through the map API, specifically:

[0093] According to the task starting point and task ending point, the map API is called, and based on real-time traffic, weather, and traffic restriction rules, the arrival time of each path in the path set is determined;

[0094] According to the arrival time, the task planning path and planned arrival time are determined.

[0095] The core purpose of the present embodiment is to dynamically generate the optimal path and planned arrival time through the map API, solve the limitations of static route dependence in traditional path planning, and adapt to real-time traffic and environmental changes, thereby improving the task execution efficiency and service quality.

[0096] According to the task starting point and ending point, use Gaode, Baidu or Google Maps API, generate multiple candidate paths based on real-time traffic (such as congestion index, accident information) and weather (such as rain and snow causing slippery road surface), consider traffic restriction rules (such as trucks are prohibited in certain areas), and filter out paths that do not meet the conditions.

[0097] The map API returns multiple candidate paths (such as the fastest path, the shortest distance path, and the congestion avoidance path), for each path, based on real-time traffic flow, weather influence (such as 10% speed reduction in rainy weather), and traffic restriction rules to adjust the speed, and calculate the time consumption.

[0098] Preferably, the path with the shortest time consumption is selected as the planned path, and if multiple paths have similar time consumption, the path deviating from the high-risk area (such as the congestion section) is selected.

[0099] For example, the map API returns the time-consuming of three paths as 30 minutes, 35 minutes and 40 minutes respectively, the 30-minute path is selected as the planned path, and the planned arrival time is 30 minutes after the task starts.

[0100] It can be understood that the traditional method relies on static paths (such as fixed routes or historically optimal paths), which cannot adapt to real-time traffic and weather changes, resulting in low path efficiency, and engineers may be forced to detour, increasing the task completion time. The embodiment adjusts the route according to the real-time traffic, reduces the detour, and shortens the task completion time. The path and time data provide an objective basis for subsequent task allocation (such as selecting the closest engineer with a high historical score), reducing the cost of manual intervention.

[0101] The embodiment solves the problems of insufficient path monitoring and extensive time management in the traditional service management mode through dynamic path planning and time estimation of the map API.

[0102] As a preferred embodiment of the present application, the offset distance is obtained by comparing the task planned path and the position data, specifically:

[0103] According to the mobile device, the position data is obtained by GPS / Beidou / cellular network, and the offset distance is obtained by comparing the task planned path and the position data;

[0104] If the mobile device is offline for more than 5 minutes, trigger device exception alarm, notify operation and maintenance personnel.

[0105] The core purpose of the embodiment is to obtain the position data of the engineering maintenance personnel in real time through the multi-source positioning technology of the mobile device, and dynamically compare the planned path and the actual path to calculate the offset distance, so as to realize the precise monitoring of the path execution of the engineer. At the same time, through the device offline alarm mechanism, the continuity and reliability of the system data are ensured.

[0106] Through the mobile device, GPS / Beidou / cellular network (such as Wi-Fi, base station positioning) positioning is adopted to ensure the availability of position data in different scenarios (such as indoor, tunnel). Of course, the positioning technology can also be used in combination, for example, GPS has high precision (5-10 meters), cellular network has wide coverage (100-500 meters), and the positioning robustness is improved through multi-source data fusion.

[0107] The mobile device uploads the position data (longitude and latitude, timestamp) at a frequency of once per minute to ensure real-time performance. In poor network state, a cache mechanism is used to temporarily store data, and the data is supplemented after recovery.

[0108] The planned path is generated by the map API (based on the starting point, end point and real-time traffic data), and the actual path is drawn by the real-time location data of the engineer (point set trajectory). The deviation distance between the actual path and the preset path is calculated using the Haversine formula or the path comparison function of the map API.

[0109] If the mobile device does not upload location data for 5 minutes (such as signal interruption, device failure), the "device abnormal alarm" is triggered. The operation and maintenance personnel are notified (SMS / APP push), and the device is reconnected or standby resources are dispatched. The device offline alarm mechanism can timely find the data missing problem, avoid the path monitoring blind area caused by device failure, and ensure the continuity of system data. If the engineer's mobile phone battery is depleted, the system can quickly notify the operation and maintenance personnel to replace the device, reducing the risk of task delay.

[0110] The embodiment solves the core problems of insufficient path monitoring, low data reliability and difficult identification of abnormal behavior in the traditional service management mode through the innovative combination of multi-source positioning technology, dynamic deviation distance calculation and device offline alarm mechanism.

[0111] As a preferred embodiment of the present application, the actual arrival time of the engineering maintenance personnel at the task end point is obtained, specifically:

[0112] In response to the photo check-in of the engineering maintenance personnel, the photo has a timestamp and a geographic location watermark;

[0113] Verify the matching of the geographic location watermark and the task end point. If the deviation between the two is less than or equal to 50m, it is confirmed to be matched, and the actual arrival time is obtained through the timestamp;

[0114] Otherwise, it is confirmed to be unmatched, marked as false check-in, and the operation and maintenance personnel are notified.

[0115] The core purpose of the embodiment is to accurately obtain the actual arrival time of the engineering maintenance personnel at the task end point by combining the geographic location watermark verification of photo check-in with the timestamp, and to prevent false check-in behavior, thereby ensuring the authenticity and reliability of service management data.

[0116] After the engineer arrives at the task end point, the photo check-in is performed through the mobile device (smartphone or dedicated terminal). The photo needs to contain a timestamp (accurate to seconds) and a geographic location watermark (such as latitude and longitude coordinates).

[0117] The system automatically calculates the deviation distance of the geographical position watermark in the photographed photo and the task end point coordinates. If the deviation is less than or equal to 50 meters, it is determined to be matched, and the actual arrival time is recorded through the timestamp. If the deviation is greater than 50 meters, it is determined to be not matched, and is marked as a false clock-in. Through the matching verification of the geographical position watermark and the task end point, the possibility of false clock-in is eliminated, and false clock-in behavior is prevented.

[0118] The Haversine formula is used to calculate the straight-line distance between two points, or the actual driving distance is obtained through a map API (such as Gaode, Baidu Map).

[0119] For false clock-in behavior that does not match, the system automatically marks and notifies the operation and maintenance personnel (SMS / APP push). False clock-in records will be archived as a basis for subsequent performance evaluation or responsibility tracing.

[0120] When it is determined to be matched, that is, a real clock-in, the actual arrival time is obtained through the timestamp. The comparison of the actual arrival time and the planned arrival time needs to be based on real data to avoid errors in the calculation of delay time caused by false clock-in, and to improve the objectivity of service quality evaluation.

[0121] The present embodiment solves the core problems of unreliable clock-in data and difficult identification of false clock-in in the traditional service management mode by combining geographical position watermark verification of photographed clock-in with timestamps.

[0122] As a preferred embodiment of the present application, in response to customer scores, the offset distance and the delay time are combined to obtain a work order task score of the engineering maintenance personnel, specifically:

[0123] According to the offset distance, when the offset distance is less than or equal to 500m, it is judged that there is no offset, and a position reference score is set,

[0124] When the offset distance is greater than 500m, it is judged that there is an offset, and the position reference score is adjusted to obtain a position trajectory score, the position trajectory score is negatively correlated with the offset distance;

[0125] According to the delay time, when the delay time is greater than or equal to -10 minutes and less than or equal to 10 minutes, it is judged that there is no delay, and a time reference score is set,

[0126] When the delay time is less than -10 minutes, it is judged that there is an advance, the time reference score is adjusted to obtain a delay time score, the delay time score is negatively correlated with the delay time,

[0127] When the delay time is greater than 10 minutes, it is judged that there is a delay, the time reference score is adjusted to obtain a delay time score, the delay time score is negatively correlated with the delay time;

[0128] obtaining a customer score in response to a customer evaluation;

[0129] obtaining the work order task score according to the customer score, in combination with the position trajectory score and the delay time score.

[0130] The core purpose of the embodiment is to scientifically quantify the work order task score of the engineering maintenance personnel through comprehensive analysis of the customer score, path deviation (offset distance) and time deviation (delay time), so as to realize accurate evaluation of the service quality.

[0131] According to the offset distance, the position trajectory score is determined. If there is no offset, i.e. the offset distance ≤ 500 meters, a position reference score (full score 1.0) is set.

[0132] If there is offset, i.e. the offset distance > 500 meters, the position trajectory score is negatively correlated with the offset distance (e.g. the score decreases by 0.1 for each additional 100 meters).

[0133] According to the time deviation, the delay time score is determined. If there is no delay, i.e. the delay time ∈ [-10, 10] minutes, a time reference score (full score 1.0) is set.

[0134] If there is advance, i.e. the delay time < -10 minutes, the time score is negatively correlated with the advance time (e.g. the score decreases by 0.05 for each 1 minute advance).

[0135] If there is delay, i.e. the delay time > 10 minutes, the time score is negatively correlated with the delay time (e.g. the score decreases by 0.05 for each 1 minute delay).

[0136] The customer score is obtained. The customer fills out a score table (three dimensions of service efficiency, service attitude and service quality, 1-5 point system) through an App or a short message. The original score (1-5 points) is converted to a range of 0-1.

[0137] The customer score, the position trajectory score and the delay time score are weighted to obtain the work order task score, with weights set to 0.4, 0.3 and 0.3 respectively. Through the combination of objective data (path deviation, time deviation) and subjective feedback (customer score), human bias is avoided, and the scientificity and credibility of the evaluation are improved. If the customer score is marked as "invalid" (e.g. not submitted within 24 hours of completing the work order), the system can exclude the score and recalculate.

[0138] In addition, dynamic adjustment of the weights is supported (e.g. the score weight of high-value customers is increased), to adapt to different business needs. For example, in an emergency work order, the time score weight can be increased to 40%, to prioritize on-time rate.

[0139] The embodiment solves the core problems of high subjectivity, difficult problem positioning, and poor improvement targeting in traditional service quality evaluation through multi-dimensional integration of customer scores, path deviations, and time deviations.

[0140] As a preferred embodiment under the present embodiment, after obtaining the work order task score, the following steps are further included:

[0141] When it is continuously judged as unqualified for multiple times, reason analysis is performed,

[0142] If the normalized customer score and the position trajectory score are less than 0.50 for multiple times, it is determined that the engineer is the cause.

[0143] If the normalized delay time score is less than 0.50 for multiple times, it is determined that the system is the cause, and the engineering maintenance personnel configuration is adjusted according to the heat map of unqualified work order tasks.

[0144] The core purpose of the present embodiment is to accurately locate the problem source (engineer's personal ability or system configuration problem) through analysis of consecutive unqualified work order tasks, and take targeted improvement measures to improve the overall service quality and resource utilization efficiency.

[0145] If the work order task score of an engineer is continuously determined as "unqualified" (score <0.50) for 3 times or more, the reason analysis process is triggered. The customer score, position trajectory score, and delay time score are normalized to the range of [0, 1] for easy horizontal comparison.

[0146] If the normalized customer score and position trajectory score are both less than 0.50 for multiple times (such as continuously for 3 times), it is determined that the engineer has personal problems. For example, if the customer score of engineer A is normalized to 0.48 and the position trajectory score is normalized to 0.45, and this has been unqualified for 3 consecutive times, it is determined that the service attitude or path planning ability of the engineer is insufficient.

[0147] If the normalized delay time score is less than 0.50 for multiple times (such as continuously for 3 times), it is determined that the system has problems. For example, if the delay time score of engineer B is normalized to 0.40 due to traffic congestion in a certain area, and this has been unqualified for 3 consecutive times, it is determined that there is a problem with system scheduling or regional resource allocation. In this way, a training mechanism (such as path planning training, customer service skill training) is triggered. If the rectification is ineffective, the engineer's position is adjusted or the cooperation is terminated.

[0148] For system problems, the spatial distribution of all unqualified work order tasks is summarized to generate a heat map to identify high-frequency delay areas (such as congested road sections, signal blind areas). Through geographic information system (GIS) superposition of engineer position trajectory, delay time score, task endpoint distribution, etc., high-risk areas are marked.

[0149] Optimize resource allocation, increase personnel density, and increase the deployment of engineering maintenance personnel in high-frequency delay areas. Path optimization, adjust task allocation strategy, and assign engineers with shorter distances or higher historical scores to high-risk areas. System repair, optimize the path planning algorithm of the map API (such as avoiding high-frequency congestion sections). Analyze high-frequency problem areas through heat maps to avoid blindly increasing personnel density, but to optimize resource allocation and improve resource utilization efficiency. For example, increase the number of standby engineers in areas with severe traffic congestion instead of increasing the number of employees globally to reduce operating costs.

[0150] This embodiment triggers the rectification process (such as training or system optimization) through attribution analysis, forming a closed loop of "problem discovery - cause analysis - rectification measures - effect verification". For example, if an engineer is determined to have a low path deviation score due to personal problems, the system can automatically push a path planning training course and verify the improvement effect in subsequent tasks.

[0151] This embodiment solves the core problems of traditional service management modes, such as difficulty in distinguishing problem sources, low resource utilization, and rectification lag, through the innovative combination of multi-dimensional attribution analysis, heat map-driven resource allocation, and automated rectification processes.

[0152] The application also provides a storage medium,

[0153] The storage medium has a computer program stored thereon, and the computer program is executed to realize the steps of the service management method for engineering maintenance personnel.

[0154] Therefore, any effect of the service management method for engineering maintenance personnel can be achieved, which will not be repeated here.

[0155] The application further provides a processing device, comprising:

[0156] A memory for storing a computer program;

[0157] A processor for executing the computer program to realize the steps of the service management method for engineering maintenance personnel.

[0158] Therefore, any effect of the service management method for engineering maintenance personnel can be achieved, which will not be repeated here.

[0159] The application does not mention the places that can be implemented or borrowed from existing technology.

[0160] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0161] The above merely illustrates the embodiments of the present application but should not be taken as limitations. Various changes and modifications can be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application should be included in the scope of claims of the present application.

Claims

1. A service management method for engineering maintenance personnel, characterized by, The method comprises the following steps: According to the work order task of the engineering maintenance personnel, the starting point and the ending point of the task are obtained, and the planned path and the planned arrival time of the task are determined through a map API; The position data of the engineering maintenance personnel is obtained, and the deviation distance is obtained by comparing the planned path and the position data. The actual arrival time of the engineering maintenance personnel at the ending point of the task is obtained, and the delay time is obtained by comparing the actual arrival time and the planned arrival time; In response to the customer score, the work order task score of the engineering maintenance personnel is obtained by combining the deviation distance and the delay time.

2. The service management method for engineering maintenance personnel according to claim 1, characterized by, Before determining the work order task of the engineering maintenance personnel, the method further comprises the following steps: The position data of the corresponding engineering maintenance personnel is obtained by screening the engineering maintenance personnel who does not execute the work order task; According to the distance between the position data and the ending point of the task, the engineering maintenance personnel who executes the work order task is determined by combining the historical work order task score of the engineering maintenance personnel and the task level of the work order task.

3. The service management method for engineering maintenance personnel according to claim 1, characterized by, The starting point and the ending point of the task are obtained, and the planned path and the planned arrival time of the task are determined through a map API. Specifically, According to the starting point and the ending point of the task, the map API is called to determine the arrival time of each path in the path set based on real-time traffic, weather and traffic restriction rules; The planned path and the planned arrival time of the task are determined according to the arrival time.

4. The service management method for engineering maintenance personnel according to claim 1, characterized by, The deviation distance is obtained by comparing the planned path and the position data. Specifically, The position data is obtained by a mobile device through GPS / Beidou / cellular network. The deviation distance is obtained by comparing the planned path and the position data; If the mobile device is offline for more than 5 minutes, an abnormal device alarm is triggered to notify the operation and maintenance personnel.

5. The service management method for engineering maintenance personnel according to claim 1, characterized by, The actual arrival time of the engineering maintenance personnel at the ending point of the task is obtained. Specifically, In response to the photographing punch-in of the engineering maintenance personnel, the photographing photo has a time stamp and a geographical position watermark; The matching of the geographical position watermark and the ending point of the task is verified. If the deviation between the two is less than or equal to 50 m, it is confirmed that they match, and the actual arrival time is obtained through the time stamp; Otherwise, it is confirmed that they do not match, marked as false punch-in, and the operation and maintenance personnel are notified.

6. The service management method for engineering maintenance personnel according to Claim 1, wherein In response to the customer score, the work order task score of the engineering maintenance personnel is obtained by combining the deviation distance and the delay time. Specifically, According to the deviation distance, when the deviation distance is less than or equal to 500 m, it is judged that there is no deviation, and the position reference score is set, When the deviation distance is greater than 500 m, it is judged that there is deviation, the position reference score is adjusted, and the position trajectory score is obtained, which is negatively correlated with the deviation distance; According to the delay time, when the delay time is greater than or equal to -10 minutes and less than or equal to 10 minutes, it is judged that there is no delay, and the time reference score is set, When the delay time is less than -10 minutes, it is judged that there is advance, the time reference score is adjusted, and the delay time score is obtained, which is negatively correlated with the delay time, When the delay time is greater than 10 minutes, the delay is determined, the time reference is adjusted, a delay time score is obtained, and the delay time score is negatively correlated with the delay time; In response to the customer evaluation, a customer score is obtained; According to the customer score, in combination with the position trajectory score and the delay time score, the work order task score is obtained.

7. The service management method for engineering maintenance personnel according to claim 6, characterized by, The work order task score is obtained, specifically: According to the customer score, the position trajectory score, and the delay time score, normalization processing is performed, and a work order task score is obtained by weighting; According to the work order task score, when the work order task score is greater than or equal to 0.85, it is determined to be excellent, When the work order task score is less than 0.85 and greater than or equal to 0.70, it is determined to be good, When the work order task score is less than 0.70 and greater than or equal to 0.50, it is determined to be qualified, When the work order task score is less than 0.50, it is determined to be unqualified.

8. The service management method for engineering maintenance personnel according to claim 7, characterized by, After obtaining the work order task score, it further includes: After continuously determining unqualified for multiple times, reason analysis is performed, If the normalized customer score and the position trajectory score are less than 0.50 for multiple times, it is determined to be an engineer reason; If the normalized delay time score is less than 0.50 for multiple times, it is determined to be a system reason, and the configuration of the engineering maintenance personnel is adjusted according to the heat map of the unqualified work order task.

9. A storage medium, characterized in that, The storage medium stores a computer program, and the computer program is executed to implement the steps of the service management method for engineering maintenance personnel according to any one of claims 1 to 8.

10. A processing device, characterized by Including: A memory for storing a computer program; A processor for executing the computer program to implement the steps of the service management method for engineering maintenance personnel according to any one of claims 1 to 8.

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