CN114662718A - Vehicle maintenance method based on routing operation scheduling - Google Patents
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Abstract
The invention relates to a vehicle maintenance method based on routing operation scheduling, in particular to the technical field of information technology, which comprises S1, obtaining multi-source data related to maintenance; s2, acquiring a specified standard; s3, performing data representation pretreatment on the multi-source data according to the designated standard value, and acquiring the pretreated multi-source data; s4, obtaining selection of maintenance scheduling time for the preprocessed multi-source data through a multi-factor selection algorithm based on the algorithm; s5, continuously fine-tuning the maintenance time scheduling according to the actual operation condition; and S6, automatically generating a refined maintenance operation plan book according to the processed data.
Description
Technical Field
The invention relates to the technical field of information technology, in particular to a vehicle maintenance method based on routing operation scheduling.
Background
Currently, for vehicles operated in a fixed line (such as buses, fixed-line passenger vehicles, freight vehicles and the like), the current maintenance planning method is used for making maintenance plans according to the recommended mileage of factory maintenance of the operated vehicles. For example, if 5000 kilometers of the traveled distance is given in a vehicle factory maintenance manual for one major or minor maintenance, the operating enterprise can estimate the traveled distance to arrange maintenance around 5000 kilometers according to actual operating conditions: approximate maintenance time is estimated as the average mileage over the previous 30 days, and maintenance is scheduled 500 km ahead.
In the actual vehicle running process, enterprises find that the compilation of maintenance plans according to the fixed mode of vehicle manufacturers has many unscientific parts: the traditional manual planning can not accurately predict the vehicle running mileage; the maintenance plan is generally about 500 kilometers ahead of the actual requirement according to the week, so that the maintenance cost is increased; the routing operation vehicle has relatively fixed road condition and passenger flow, and the abrasion condition can be roughly determined by comparing the same type of vehicles, so that the maintenance time of the same type of vehicles is increased and decreased.
Compared with vehicles operated in other modes, the running environment and the mileage of the vehicle operated in a routing manner can be controlled, so that the maintenance cycle can be predicted theoretically: the vehicle operation mileage CAN be obtained through a vehicle CAN bus or a GPS operation record, the states of main components of the vehicle CAN be partially obtained through the CAN bus in real time and CAN be completely obtained by combining with the component maintenance state record in maintenance, the mileage of each circle of the vehicle CAN be obtained through routing operation, and the running distance from the vehicle to a maintenance factory and a maintenance factory CAN be obtained. Therefore, the information in the vehicle dispatching system can be integrated, and a more scientific maintenance time plan can be customized for the running vehicle by combining the position of a vehicle maintenance factory, the time for providing maintenance service and special requirements of line running (such as the requirement of the online rate of all vehicles on the peak in the morning and evening, the maintenance is staggered from the peak in the morning and evening as much as possible, and some vehicle types with better quality can be allowed to exceed the maintenance mileage by 10 percent and the like).
Currently, there are some empirical approaches in enterprises operating in a line-determined manner (such as public transportation and line-determined passenger transportation enterprises): for example, according to the attribute of the running line and the experience of line operators and maintenance personnel, the maintenance mileage of certain lines and vehicle types is manually fine-tuned, for example, the use state of the replaced consumable parts can be better observed, and under the constraint that a solicited manufacturer gives the highest maintenance mileage, certain maintenance mileage can be added to other vehicles of the same type as appropriate or the service time of some unnecessary replacement accessories can be prolonged. In the above routing operation enterprises, there is no practice of comprehensively considering the above multiple factors, finely selecting the maintenance time point and communicating with the scheduling system.
Disclosure of Invention
The invention aims to provide a vehicle maintenance method based on routing operation scheduling, which has the effects of intelligently compiling a maintenance plan of a vehicle enterprise, saving human resources and reducing maintenance cost.
The above object of the present invention is achieved by the following technical solutions:
the vehicle maintenance method based on routing operation scheduling comprises the following steps:
s1, obtaining multi-source data related to maintenance;
s2, acquiring a specified standard, namely a service peak period;
s3, performing data representation pretreatment on the multi-source data according to the designated standard value, and acquiring the pretreated multi-source data;
s4, obtaining selection of maintenance scheduling time for the preprocessed multi-source data through a multi-factor selection algorithm based on the algorithm;
s5, continuously fine-tuning the maintenance time scheduling according to the actual operation condition;
and S6, automatically generating a refined maintenance work plan according to the processed data.
Preferably, in step S1, the multi-source data includes:
A. the maintenance mileage specified by a manufacturer can be properly prolonged for certain high-quality vehicle types based on historical data analysis and maintenance operation experience;
B. obtaining the current driving mileage of the vehicle according to a CAN bus or a GPS information source of the vehicle, obtaining the subsequent approximate maintenance time L of the vehicle, calculating the average driving distance b c + d of each day according to the operation rule of the line, the approximate running number b of each circle of the vehicle model of the line, the distance c of each circle and the energy charging distance d, and predicting the maintenance needed after the number of days in the future according to the maintenance mileage t recommended by a manufacturer;
C. obtaining maintenance records of all vehicle types of lines, increasing and decreasing maintenance mileage t as appropriate, and determining whether the maintenance mileage can be properly prolonged after how many kilometers of a certain vehicle type are in combination with the sudden failure rate of the vehicle in different maintenance periods according to the state of the vehicle at each maintenance node recorded in the vehicle type maintenance records;
D. and acquiring the position of the maintenance factory and the distance l from the parking lot of the maintenance factory to the maintenance factory, wherein if the maintenance factory comprises a plurality of maintenance factories, the maintenance factories are respectively represented by l1, l2 and l3 … ….
Preferably, in step S4, the pre-processed multi-source data is subjected to a multi-factor selection algorithm based on an algorithm to obtain a selection of a shift schedule for maintenance, where the algorithm includes:
s41, giving time to each vehicle according to the 'approach maintenance mileage degree': according to the maintenance mileage t, the daily driving mileage b c + d, the maintenance factory distance l and the distance c of each circle obtained above, and the energy charging distance d, the optimal maintenance time of the vehicle in a certain time period Y of a certain day X is calculated, and the calculation formula is as follows:
(b*c+d)X+Y*c+d+l<t
Y<b
sequentially calculating the maximum value of X and the maximum value of Y, wherein the priority of X is greater than that of Y;
s42, adjusting the maintenance time arrangement according to the 'vehicle on-line rate guarantee in the peak service period', after obtaining the peak service period range, if Y belongs to the peak time periods in the morning and evening and the requirement that the on-line rate of the peak time periods in the morning and evening accounts for P1 needs to be met, counting the percentage of vehicles to be always registered by the vehicle enterprises in the peak time periods in the morning and evening as P2, if 1-P2< P1, adjusting the vehicles accounting for the total registration of the vehicle enterprises P1- (1-P2) to carry out maintenance in advance, and if Y does not belong to the peak time periods in the morning and evening, not adjusting Y;
s43, adjusting the maintenance scheduling according to the 'availability of service of the maintenance plant', if the maintenance plant can only maintain one vehicle at a time and two vehicles need to be maintained simultaneously according to the above algorithm, the l1 is changed into l2, and then the calculation process is repeated according to S41 and S42 again.
Preferably, in step S5, the fine tuning process includes:
s51, operating the algorithm and the rectification and adjustment parameters according to different time periods, operating the algorithm once in a whole enterprise every month, compiling a maintenance operation plan of the next month, and synchronously scheduling relevant data in the system and the maintenance operation system according to the maintenance operation plan;
then, the algorithm is operated once a week by the line, the data of the driving mileage L of the vehicle is updated, and particularly, optimization is carried out by combining manual judgment on multiple running turns or few running turns on a special date;
and finally, the time for maintaining the concrete is accurate to each hour.
Preferably, after step S51, the method further includes:
and S52, linking with a maintenance scheduling algorithm of the maintenance plant, synchronizing the maintenance operation plans arranged on the lines to each maintenance plant according to a period, and determining the number and time of the receivable maintenance operations by the maintenance plant.
In conclusion, the invention has the beneficial effects that:
the beneficial effects are that: the workload of manual planning is reduced, and the scientificity of planning is improved; on the basis of safe operation, the operation mileage is increased and the maintenance cost is reduced by refining the selection of the maintenance time point; according to the maintenance plan, the use condition of consumables and manpower can be calculated, so that the stock and the manpower are arranged in advance, and the stock and the fund pressure are reduced.
The beneficial effects are that: and adjusting the maintenance plan according to the actual running condition of the line, so that the maintenance plan is better combined with the operation, and the waste of non-operation time of the vehicle is reduced.
Drawings
FIG. 1 is a schematic overall step diagram of the present invention;
FIG. 2 is a schematic diagram of the multi-source data category and its preprocessing result according to the present invention;
FIG. 3 is a block diagram of the algorithm step S4 for obtaining the selection of the shift schedule for the maintenance through the multi-factor selection algorithm for the pre-processed multi-source data according to the present invention;
fig. 4 is a specific calculation process of the algorithm step S4 in the present invention.
Detailed Description
In order to facilitate understanding of those skilled in the art, the present invention will be further described with reference to the following examples and drawings, which are not intended to limit the present invention. The present invention is described in detail below with reference to the attached drawings.
The present invention will be described in further detail with reference to the accompanying drawings.
Referring to fig. 1, the vehicle maintenance method based on routing operation scheduling includes the following steps:
s1, obtaining multi-source data related to maintenance;
s2, acquiring a specified standard, wherein the specified standard refers to a constant which does not change due to the change of multi-source data, such as a service peak period and the like;
s3, performing data representation preprocessing on the multi-source data according to a designated standard value, and acquiring the preprocessed multi-source data (such as average driving distance per day obtained according to vehicle running circles, single-circle distance and energy charging distance, and preprocessed data according to service rush hour time periods and time periods in which the automobile is located after each circle is finished);
s4, selecting the maintenance scheduling time through a multi-factor selection algorithm on the preprocessed multi-source data based on the algorithm;
s5, continuously fine-adjusting the maintenance time scheduling according to the actual operation condition;
and S6, automatically generating a refined maintenance work plan according to the processed data.
In the specific embodiment of the invention, various data required by the generation of the maintenance schedule are collected firstly, the data are generally constant, then some data are preprocessed, then the most preferable maintenance scheduling time selection is obtained by the collected multi-source data which are preprocessed or not preprocessed through an algorithm, maintenance mileage is not wasted as much as possible, and then fine adjustment is carried out according to the actual running condition, so that a more accurate maintenance schedule is obtained, the workload of manual compilation is reduced in the process, and the scientificity of the planning compilation is improved; on the basis of safe operation, the operation mileage is increased by selecting refined maintenance time points, and the maintenance cost is reduced; according to the maintenance plan, the consumable and manpower use conditions can be calculated, so that goods can be prepared in advance, and the inventory and capital pressure can be reduced.
Referring to fig. 2, in step S1, the multi-source data includes:
A. the manufacturer generally carries out maintenance compilation according to vehicle driving mileage or maintenance interval time, maintenance mileage specified by the manufacturer can be properly prolonged for certain high-quality vehicle types according to historical data analysis and maintenance operation experience, for example, the quality of vehicles of some manufacturers is good, the manufacturer recommends that the vehicle can be maintained after driving a certain number of mileage, or a bus can be maintained according to maintenance experience of different vehicle types (for example, the quality of a certain type of imported vehicle is good, and the vehicle can be maintained after driving 10% of recommended mileage).
B. The method comprises the steps of obtaining the current driving mileage of a vehicle according to sources such as a CAN bus or vehicle GPS information and obtaining the subsequent approximate maintenance time L of the vehicle, calculating the average driving distance b c + d of each day according to the operation rule of the line, the number of the runs of a certain vehicle type of the line approximately every day, the distance c of each circle and the charging distance d, and predicting the maintenance needed after the number of days in the future according to the maintenance mileage t recommended by a manufacturer.
C. And acquiring maintenance records of all vehicle types of the line and increasing and decreasing the maintenance mileage t as required. According to the states of the vehicles at the maintenance nodes recorded in the vehicle model maintenance record (the overall vehicle state evaluation given after each maintenance, such as better, worse, poor and the like), the sudden failure rate of the vehicles in different maintenance periods (such as whether the failure rate of 2 kilometers reaches more than 5%) is combined to determine whether the maintenance mileage of a certain vehicle model can be properly prolonged after the certain vehicle model is over the kilometer. For example, after a certain vehicle is guaranteed for 5000 kilometers, the overall state of the vehicle is maintained to be better than that of the vehicle, and the sudden failure rate of ten kilometers after the vehicle is guaranteed for 5000 kilometers is lower than 1%, so that the maintenance mileage of small protection and large protection can be increased by 10%; for a certain vehicle, the failure rate of ten thousand kilometers is more than 5%, and the maintenance mileage is reduced by 10%.
D. And acquiring the position of a maintenance factory and the distance l from the parking lot of the company. Generally, 1 or several maintenance factories are fixed near a certain vehicle type of a certain route, and are respectively represented by l1, l2 and l3, and for each vehicle type, maintenance factory information (maintenance position, approximate driving distance and time, working time of large and small maintenance) and time (how many maintenance stations and working time periods exist; time period of special maintenance work such as engine overhaul) for providing maintenance service around the vehicle type are recorded.
In the embodiment of the present invention, the above multi-source data are collected respectively to prepare the constants required for the calculation in the next step S4, so as to perform further calculation and analysis.
Referring to fig. 3 and 4, in step S4, the algorithm includes:
s41, giving time to each vehicle according to the 'approach maintenance mileage degree': and calculating the optimal maintenance time of the vehicle in a certain time period Y of a certain day X according to the maintenance mileage t, the driving mileage b × c + d, the maintenance factory distance l and the distance c of each circle obtained in the above steps and the energy charging distance d.
The calculation formula is as follows:
(b*c+d)X+Y*c+d+l<t
Y<b
(wherein b, c, d, l and t are all constants), and sequentially calculating the maximum value of X and the maximum value of Y (the priority of X is greater than that of Y). For example, a car is reserved after 2000 km, the length of a circuit cycle is 50 km, the car runs 4 cycles per day on average, plus 30 km for adding oil and gas or charging every day, the driving mileage is 230 km per day, and the car is 10 km away from a maintenance factory, so that the car is preferably maintained after running two cycles after 8 days (230 x 7+2 x 50+30+10 ═ 1980<2000), the time after running 2 cycles is about 13 o' clock, plus the time of travel to the maintenance factory is 20 minutes, the best maintenance of the car is 13:20 to 15:20 in the afternoon after 8 days (assuming that the time of reservation is 2 hours), and the car can be scheduled to be used in the late peak operation activities in the afternoon.
S42, adjusting the maintenance time arrangement according to the 'vehicle on-line rate guarantee in peak service period', after obtaining the peak service period range, if Y belongs to the peak time period in the morning and evening and simultaneously the requirement that the on-line rate in the peak time period in the morning and evening accounts for P1 is required to be met, counting the percentage of the vehicles to be always registered in the vehicle enterprises in the peak time period in the morning and evening to be P2, if 1-P2 is less than P1, the vehicles accounting for the total time of the vehicles to be always registered in P1- (1-P2) are required to be adjusted to be maintained in advance, the priority of the adjustment of the maintenance in advance is prioritized according to the vehicle closest to the maintenance mileage, if Y does not belong to the peak time period in the morning and evening, the adjustment of Y is not required, for example, the length of a circuit loop is 45 kilometers, and then calculating that the vehicles are best maintained after the 3 rd loop (late peak time) on the 8 th day. At this time, in order to guarantee vehicles with late peaks, the vehicles need to be adjusted and then the vehicles need to be maintained after the 2 nd circle is completed.
S43, adjusting the maintenance schedule according to the maintenance factory service availability. If the maintenance plant can only maintain one vehicle at a time, and there are two vehicles to be maintained simultaneously according to the above algorithm, l1 is changed to l2, and then the calculation process is repeated again according to S41 and S42. For example, if a maintenance factory can only maintain one vehicle at a time, and there are two vehicles that need to be maintained simultaneously according to the above algorithm, then the maintenance time and location adjustment is needed, such as: and adjusting one vehicle to two maintenance factories which are far away, and performing major maintenance on one vehicle one day in advance or performing overtime work on the maintenance factory according to the situation.
In the specific embodiment of the invention, the maintenance execution days and the number of circles in the maximum safety range are obtained through the calculation of the three steps, the economic value of automobile transportation is lost when the maintenance time point is collided with a service peak period, and whether the maintenance factory in a preset time has a vacancy or not is known in advance, so that the maintenance factory can be replaced in advance, the maintenance plan is accurately modified, and the influence of the waste of the maintenance time on the transportation value is prevented.
In step S5, continuously fine-tuning the shift schedule of the maintenance time according to the actual operation condition, wherein the fine-tuning process includes:
and S51, operating the algorithm according to different time periods (such as monthly, weekly and daily) and adjusting the parameters. For example, the algorithm is operated once per month in the whole enterprise, a maintenance operation plan of the next month is compiled, relevant data in a scheduling system and a maintenance operation system are synchronously scheduled according to the algorithm, so that a maintenance plant can conveniently stock in advance and arrange manpower, and a line can conveniently know the degree of influence of maintenance operation in a peak period so as to carry out compensation arrangement (for example, shunting from other lines or enlarging service intervals in certain time periods);
then, the algorithm is operated once a day (or a week) by the line, data such as vehicle driving mileage and the like are updated, and particularly, optimization is carried out by combining the maintenance operation plan of the next 2 days with manual judgment: if the vehicle runs for a plurality of times and reaches maintenance mileage, whether maintenance needs to be performed one day in advance or not is found, and what the maintenance factory has to do is found; some vehicles run with insufficient mileage, whether maintenance needs to be carried out from morning to afternoon or from 2 nd day, whether maintenance can be carried out by a maintenance plant, and the like.
Finally, the specific maintenance time can be accurate to every hour, for example, when a certain vehicle runs to the 1 st round, the vehicle is collected at 10 am, the vehicle is started for 15 minutes to a nearby maintenance plant, the maintenance plant is 10:20 ready to receive the vehicle and starts maintenance, and after about 2 hours of maintenance, the vehicle can return to the line to operate again at 12:40 noon.
In the specific embodiment of the invention, the fine adjustment method can timely correct the mileage of more or less operation of a driver under special conditions and regularly feed the mileage back to a maintenance plant, thereby improving the precision of the mileage maintenance schedule and facilitating the arrangement and scheduling of the maintenance plant according to the self condition.
Further optimized in S5 as:
s52, the maintenance scheduling algorithm of the maintenance plant is synchronously linked, the maintenance resources of the maintenance plant are not infinite, the maintenance resources are limited in a plurality of aspects such as stations, personnel, consumables and the like, the maintenance operation plan arranged on the line needs to be synchronized to each maintenance plant according to the week or day, and the maintenance plant determines the number and time of the maintenance operation which can be received.
Although the present invention has been described with reference to the above preferred embodiments, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. The vehicle maintenance method based on routing operation scheduling is characterized by comprising the following steps of:
s1, obtaining multi-source data related to maintenance;
s2, acquiring a specified standard, namely a service peak period;
s3, performing data representation pretreatment on the multi-source data according to the designated standard value, and acquiring the pretreated multi-source data;
s4, obtaining selection of maintenance scheduling time for the preprocessed multi-source data through a multi-factor selection algorithm based on the algorithm;
s5, continuously fine-adjusting the maintenance time scheduling according to the actual operation condition;
and S6, automatically generating a refined maintenance operation plan according to the processed data.
2. The vehicle maintenance method based on routing operation scheduling according to claim 1, wherein in step S1, the multi-source data includes:
A. the maintenance mileage specified by a manufacturer can be properly prolonged for certain high-quality vehicle types based on historical data analysis and maintenance operation experience;
B. obtaining the current driving mileage of the vehicle according to a CAN bus or a GPS information source of the vehicle, obtaining the subsequent approximate maintenance time L of the vehicle, calculating the average driving distance b c + d of each day according to the operation rule of the line, the approximate running number b of each circle of the vehicle model of the line, the distance c of each circle and the energy charging distance d, and predicting the maintenance needed after the number of days in the future according to the maintenance mileage t recommended by a manufacturer;
C. obtaining maintenance records of all vehicle types of lines, increasing and decreasing maintenance mileage t as appropriate, and determining whether the maintenance mileage can be properly prolonged after how many kilometers of a certain vehicle type are in combination with the sudden failure rate of the vehicle in different maintenance periods according to the state of the vehicle at each maintenance node recorded in the vehicle type maintenance records;
D. and acquiring the position of the maintenance factory and the distance l from the parking lot of the maintenance factory to the maintenance factory, wherein if the maintenance factory comprises a plurality of maintenance factories, the maintenance factories are respectively represented by l1, l2 and l3 … ….
3. The vehicle maintenance method based on routing operation scheduling according to claim 2, wherein in step S4, the pre-processed multi-source data is subjected to maintenance scheduling time selection through a multi-factor selection algorithm based on an algorithm, and the algorithm comprises:
s41, time is arranged for each vehicle according to the 'degree of approaching to the maintenance mileage', the optimal maintenance time of the vehicle in a certain time period Y of a certain day X is calculated according to the maintenance mileage t, the driving mileage b c + d, the maintenance factory distance l, the distance c of each circle and the energy charging distance d, wherein the calculation formula is as follows:
(b*c+d)X+Y*c+d+l<t
Y<b
sequentially calculating the maximum value of X and the maximum value of Y, wherein the priority of X is greater than that of Y;
s42, adjusting the maintenance time arrangement according to the service peak period vehicle on-line rate guarantee, after obtaining a service peak period range, if Y belongs to the peak time periods in the morning and evening and the requirement that the on-line rate of the vehicle occupies P1 in the peak time periods in the morning and evening is required to be met, counting the percentage of the vehicles occupying the vehicle enterprise in the peak time periods in the morning and evening to be P2, if 1-P2 is less than P1, adjusting the vehicles occupying the vehicle enterprise in the P1- (1-P2) to perform maintenance in advance, and if Y does not belong to the peak time periods in the morning and evening, not adjusting Y;
s43, adjusting the maintenance scheduling according to the 'availability of service of the maintenance plant', if the maintenance plant can only maintain one vehicle at a time and two vehicles need to be maintained simultaneously according to the above algorithm, the l1 is changed into l2, and then the calculation process is repeated according to S41 and S42 again.
4. The vehicle maintenance method based on routing operation scheduling according to claim 3, wherein within step S5, the fine tuning process comprises:
s51, operating the algorithm and the rectification and adjustment parameters according to different time periods, operating the algorithm once in a whole enterprise every month, compiling a maintenance operation plan of the next month, and synchronously scheduling relevant data in the system and the maintenance operation system according to the maintenance operation plan;
then, the algorithm is operated once a week by the line, the data of the driving mileage L of the vehicle is updated, and particularly, optimization is carried out by combining manual judgment on multiple running turns or few running turns on a special date;
and finally, the time for maintaining the concrete is accurate to each hour.
5. The vehicle maintenance method based on routing operation scheduling according to claim 4, further comprising after step S51:
and S52, linking with a maintenance scheduling algorithm of the maintenance plant, synchronizing the maintenance operation plans arranged on the lines to each maintenance plant according to a period, and determining the number and time of the receivable maintenance operations by the maintenance plant.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117516586A (en) * | 2024-01-08 | 2024-02-06 | 安徽中科中涣信息技术有限公司 | Method for automatically counting non-operation mileage of vehicle based on GPS information |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117516586A (en) * | 2024-01-08 | 2024-02-06 | 安徽中科中涣信息技术有限公司 | Method for automatically counting non-operation mileage of vehicle based on GPS information |
| CN117516586B (en) * | 2024-01-08 | 2024-04-05 | 安徽中科中涣信息技术有限公司 | Method for automatically counting non-operation mileage of vehicle based on GPS information |
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