Method and apparatus for scheduling maintenance operations

Abstract

Scheduling a maintenance operation on a vehicle (100; fig. 3) comprises obtaining (410) maintenance data (235; fig. 3) relating to vehicles. The maintenance data is indicative of historic maintenance

Description

TECHNICAL FIELD The present disclosure relates to scheduling maintenance operations on vehicles. Aspects of the invention relate to computer implemented methods, to a vehicle, and to computer readable instructions for performing a method. BACKGROUND It is known that vehicles, as with any complex machine, require maintenance in order to prolong a life of the vehicle. A maintenance operation may be a scheduled maintenance operation, where one or more maintenance actions are performed according to a predetermined schedule, which may depend upon a mileage or running time of the vehicle e.g. operational hours, or an age of the vehicle. Alternatively a maintenance operation may be performed according to a condition of the vehicle, including its component parts, i.e. if a determined condition of one or more components requires maintenance such as replacement of the one or more components. Problems have been identified with performing maintenance operations on a vehicle at a correct point in time. It is an aim of the present invention to address one or more of the disadvantages associated with the prior art. SUMMARY OF THE INVENTION Aspects and embodiments of the invention provide a method, a computer system, and computer software as claimed in the appended claims. According to an aspect of the present invention there is provided a computer-implemented method of scheduling a maintenance operation on a vehicle, the method comprising obtaining maintenance data relating to a plurality of vehicles, wherein the maintenance data is indicative of historic maintenance operations associated with each of the plurality of vehicles and comprises, for each vehicle, a plurality of categories of maintenance data, determining a maintenance indicator for each vehicle in dependence on the maintenance data, wherein the maintenance indicator is indicative of a historic maintenance profile forthe respective vehicle, and scheduling maintenance operations for a portion of the plurality of vehicles in dependence on the maintenance indicator associated with each of the portion of the plurality of vehicles. Advantageously the scheduling of the maintenance operations is determined in dependence on the historic maintenance profile for the respective vehicle. According to an aspect of the present invention there is provided a computer-implemented method of scheduling a maintenance operation on a vehicle, the method comprising obtaining maintenance data relating to a plurality of vehicles, wherein the maintenance data is indicative of historic maintenance operations associated with each of the plurality of vehicles and comprises, for each vehicle, a plurality of categories of maintenance data, generating weighted maintenance data comprising applying a plurality of weights to the maintenance data, wherein the each of the plurality of weights is associated with a respective one of the plurality of categories of maintenance data, determining a maintenance indicator for each vehicle in dependence on the weighted maintenance data, wherein the maintenance indicator is indicative of a historic maintenance profile for the respective vehicle, and scheduling maintenance operations for a portion of the plurality of vehicles in dependence on the maintenance indicator associated with each of the portion of the plurality of vehicles. Advantageously the scheduling of the maintenance operations is determined in dependence on the historic maintenance profile for the respective vehicle. The method optionally comprises determining a ranking value for each of the categories of maintenance data associated with each vehicle. Advantageously the ranking limits a range of values associated with each category of maintenance data, thereby improving processing of the maintenance data. The generating of the weighted maintenance data comprises applying the each of the plurality of weights to the ranking value associated with the respective one of the plurality of type of maintenance data to determine a weighted ranking value for each of the plurality of categories of maintenance data. Advantageously the weighting may reflect an importance of each category of maintenance data. The maintenance indicator may be determined in dependence on the weighted ranking value for each of the plurality of categories of maintenance data. Advantageously the maintenance indicator provides a single indication of the maintenance history of each vehicle. Optionally, the determining of the maintenance indicator comprises combining the weighted ranking values associated with the plurality of categories of maintenance data for each vehicle. Advantageously the maintenance indicator reflects the plurality of ranking values. The combining optionally comprises summing the weighted ranking values associated with the plurality of categories of maintenance data for each vehicle. Advantageously summing the plurality of ranking values provides a convenient way of combining the ranking values. The scheduling of maintenance operations for the portion of the plurality of vehicles may comprise receiving a request for a maintenance operation associated with at least some of the plurality of vehicles and scheduling the maintenance operation for each vehicle proportional to the maintenance indicator. Advantageously the requests scheduling may be performed responsive to the requests. The method optionally comprises receiving a request for a maintenance operation associated with each of the portion of the plurality of vehicles. The requests may be received from another computer system. Advantageously the request may be received in dependence on the maintenance operation being required. The method optionally comprises determining a scaled maintenance indicator for each vehicle of the plurality of vehicles. The scaled maintenance indicator is optionally determined in dependence on a value of a maximum and a minimum maintenance indicator for the plurality of vehicles. Advantageously the scaling of the maintenance indicator allows convenient processing, such as to categorise the scaled maintenance indicator. The scaled maintenance indicator Xscaied for each vehicle may be determined by: ^max Amin where x is the maintenance indicator value forthe vehicle, xmax is a maximum maintenance indicator value and Xmin is a minimum maintenance indicator value forthe plurality of vehicles. The maintenance data is optionally obtained from the one or more vehicles. Advantageously the vehicle(s) may provide the maintenance data in an automated manner. The maintenance data may be obtained via communication with each of the one or more vehicles. The communication may be wired or wireless communication. The communication is optionally via an on-board diagnostic (OBD) port of each vehicle. According to an aspect of the present invention, there is provided a computer system for scheduling a maintenance operation on a vehicle, the computer system comprising one or more processors collectively configured to obtain maintenance data relating to a plurality of vehicles, wherein the maintenance data is indicative of historic maintenance operations associated with each of the plurality of vehicles and comprises, for each vehicle, a plurality of categories of maintenance data, generate weighted maintenance data comprising applying a plurality of weights to the maintenance data, wherein the each of the plurality of weights is associated with a respective one of the plurality of categories of maintenance data, determine a maintenance indicator for each vehicle in dependence on the weighted maintenance data, wherein the maintenance indicator is indicative of a historic maintenance profile for the respective vehicle, and schedule maintenance operations for a portion of the plurality of vehicles in dependence on the maintenance indicator associated with each of the portion of the plurality of vehicles. According to an aspect of the present invention, there are provided computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform a method as described above. Within the scope of this application it is expressly intended that the various aspects, embodiments, examples and alternatives set out in the preceding paragraphs, in the claims and / or in the following description and drawings, and in particular the individual features thereof, may be taken independently or in any combination. That is, all embodiments and / or features of any embodiment can be combined in anyway and / or combination, unless such features are incompatible. The applicant reserves the right to change any originally filed claim or file any new claim accordingly, including the right to amend any originally filed claim to depend from and / or incorporate any feature of any other claim although not originally claimed in that manner. BRIEF DESCRIPTION OF THE DRAWINGS One or more embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure 1 shows a vehicle for use with embodiments of the invention; Figure 2 shows a computer system according to an embodiment of the invention; Figure 3 shows a system according to an embodiment of the invention; and Figure 4 shows a method in accordance with an embodiment of the invention. DETAILED DESCRIPTION A vehicle 100 configured in accordance with an embodiment of the present invention is described herein with reference to the accompanying Figure 1. As shown in Figure 1, the vehicle 100 is a land-going i.e. wheeled vehicle, although it will be appreciated that embodiments of the present invention may be used with any type of vehicle such as aircraft and watercraft. Embodiments of the present invention may also be useful with any type of machine. The vehicle 100 shown in Figure 1 is a passenger vehicle 100 having a plurality of wheels, although embodiments of the invention may be used with goods or other types of vehicles. The vehicle 100 is a complex machine which requires maintenance which may be a scheduled maintenance or an unscheduled maintenance. The scheduled maintenance may be performed according to predetermined time periods e.g. according to a predetermined service schedule or usage conditions of the vehicle 100, such as mileage e.g. maintenance every 12000 km or in dependence on measured use of the vehicle 100. However, it can be observed from data relating to unscheduled maintenance of a plurality of vehicles e.g. hundreds (or more vehicles) that statistically some vehicles require unscheduled maintenance more than others. Such need for additional unscheduled maintenance can be problematic for users of those vehicles. It is therefore desired to provide methods and apparatus for scheduling maintenance of vehicles to ameliorate such problematic experiences. With reference to Figure 2, there is illustrated a computer system 200 according to an embodiment of the invention which may be used with the vehicle 100. The computer system 200 is configured to receive data associated with the vehicle 100, as will be explained. The data may be maintenance data 235 as described below. The computer system 200 is arranged to schedule maintenance operations of a group of a plurality of vehicles, where the group includes the vehicle 100 in dependence on data associated with each vehicle including the vehicle 100. The computer system 200 as illustrated in Figure 2 comprises processing means 210 and memory means 220. The processing means 210 may be one or more electronic processing device 210 or one or more processors 210 which operably executes computer-readable instructions. The memory means 220 may be one or more memory device 220 or memory 220. The memory 220 is electrically coupled to the processing means or processor 210. The memory 220 is configured to store instructions, and the processor 210 is configured to access the memory 220 and execute the instructions stored thereon. The memory 220 may also store data for operation on by a process executing on the processor 210. The computer system 200 comprises a communication means 230. The communication means 230 may comprise an electrical input / output of the computer system 200. The communication means 230 may comprise a wired or wireless communication interface 230 of the computer system 200. In one embodiment, the communication means may be a network interface 230 of the computer system 230. The network interface 230 may communicably connect the computer system 200 to a wired network via which the computer system communicates with a wireless telecommunications network to communicate data 235 with the vehicle 100 as illustrated in Figure 3. The network interface 230 may also allow the computer system 200 to communicate data 245 with one or more other computer systems 300, such as hosting a data store e.g. a database, to retrieve and / or store data therein. The one or more other computer systems 300 may comprise a maintenance computer system 300 as illustrated in Figure 3. The maintenance computer system 300 may be arranged to initiate a maintenance operation of the vehicle 100 in dependence on maintenance data 245 received from the computer system 200 e.g. first computer system 200. The maintenance computer system may be a portable computer system which is for e.g. associated with a user who carries out roadside maintenance of vehicles and is used to capture data associated with the roadside maintenance. The data may comprise temporal maintenance data indicative of a time (including date) of the maintenance performed on the vehicle 100 and maintenance data indicative of maintenance performed such as parts replaced and operations carried out on the vehicle e.g. calibration or adjustment operations. The computer system 200 comprises a user interface 240 for receiving data from a user e.g. indicative of maintenance operations performed on the vehicle 100 and outputting notifications or indications to a user, such as maintenance schedule data. The user interface 240 may comprise at least one visual and / or audible output device. For example the user interface 240 may comprise a display device and one or more speakers. The user interface 240 may be used to output a notification to the user indicative of the requirement for a maintenance operation. Although the computer system 200 is shown in Figures 2 and 3 as a discrete computer system, and other computer systems are referred to below, it will be appreciated that the computer system 200 and other computer systems may be implemented as a cloud computing system where processes are executed by distributed processors and storage devices. Thus although the term computer system, first computer system etc. is referred to herein, it will be realised that these terms are not restrictive. Figure 4 illustrates a method 400 according to an embodiment of the invention. The method 400 is a computer-implemented method of scheduling a maintenance operation on a vehicle, such as the vehicle 100. The method 400 may determine a schedule or ordering of a plurality of vehicles on which to perform maintenance operations. The method may be performed by the computer system 200 illustrated in Figures 2 and 3, in particular computer executable instructions executed by the processor 210 to perform the method 400. The method 400 comprises a step 410 of obtaining maintenance data 235 relating to a plurality of vehicles, such as including the vehicle 100. For example, as denoted in the tables below, maintenance data for four vehicle is provided with it being understood that this is merely an illustrative example and that maintenance data 235 for other numbers of vehicles may be used. In particular, maintenance data for potentially hundreds, or even larger, numbers of vehicles may be obtained. The maintenance data 235 is indicative of historic maintenance operations associated with each of the plurality of vehicles indicative of maintenance operations previously performed with respect to that vehicle. The maintenance data 235 may also be indicative of one or more attributes of each vehicle, such as age or other attribute of each respective vehicle. The maintenance data 235 may comprise a plurality of categories or types of maintenance data. Each category of maintenance data is associated with a respective aspect of the vehicle’s maintenance or respective attribute associated with the vehicle to which the maintenance data relates. The maintenance data may be communicated to the computer system 200 from one or more sources. At least some of the maintenance data 235 may be communicated to the computer system 200 from the vehicle 100 e.g. from a communication module aboard the vehicle 100. For example, data indicative of historic maintenance operations may be stored in a memory associated with the vehicle 100 and communicated to the computer system 200. The communication may be over a wireless communications link e.g. via a telecommunications network or via a wired communication link such as the computer 300 communicating with the vehicle 100 via an on-board diagnostic (OBD) port. In some embodiments, at least some of the maintenance data 235 may be provided via the computer system 300 e.g. from input by a user using the user interface of the computer system 300 to enter the maintenance data, which is communicated to the computer system 200. For example, where the computer 300 is a portable computer associated with a mobile vehicle technician, data relating to maintenance operations carried out on vehicles may be entered. Similarly, where the computer 300 is associated with a maintenance location such as a garage. Table 1 below provides example maintenance data 235 for four vehicles, namely vehicles A, B, C and D. The example maintenance data 235 comprises five categories of maintenance data i.e. a first category, a second category, a third category, a fourth category and a fifth category of maintenance data. However it will be appreciated that the number and choice of categories illustrated is merely an example and that other numbers and categories of maintenance data may be used with embodiments of the invention. In the illustrated example, the first category of maintenance data 235 is indicative of a number of maintenance operations performed at a roadside i.e. away from a dedicated maintenance location. For example, a number of times the respective vehicle has been attended to by a maintenance operative whilst being located away from a maintenance location, such as at a user’s home, at a roadside or in a car park with other maintenance locations may be envisaged. Thus the term roadside is understood to include a variety of potential maintenance locations. In Table 1 the first category of maintenance data, ‘Roadside’ indicates that vehicle A has been seen twice at the roadside, whilst vehicle C has been seen once at the roadside. The second category of maintenance data, ‘Claims’, is indicative of a number of manufacturer or warranty claims made in respect of the vehicle e.g. with the manufacturer provided parts and / or consumables forthe vehicle. In Table 1 the second category of maintenance data, ‘Claims’, indicates that a claim in respect of vehicle A as being made six times whilst a claim in respect of the vehicle B has been made once. The third category of maintenance data, ‘Time’, is indicative of a period of time since a last maintenance requirement forthe vehicle i.e. a lower figure or value indicates that the associated vehicle required maintenance more recently, whereas a higher figure or value indicates that the vehicle was last maintained a long period of time ago. The third category of maintenance data is a unit relating to a period of time such as days. For example, the maintenance data in Table 1 indicates that vehicle A last required a maintenance operation 35 days ago, while vehicle D last required a maintenance operation 450 days ago. The fourth category of maintenance data, ‘Workshop’, is indicative of a number of workshop sessions being required in respect of the vehicle. It will be understood that a workshop session is considered to be a single requirement forthe vehicle to visit a maintenance location such as a workshop or garage. A workshop session may be utilised for e.g. diagnosing a maintenance issue e.g. performing one or more tests on the vehicle, or performing a maintenance operation of the vehicle e.g. replacing or adjusting one or more parts or systems of the vehicle. Thus each visit to a maintenance location is considered to be a workshop session. In Table 1, the vehicle A required ten workshop sessions, the vehicle B required two workshop sessions and vehicles C and D required one workshop session each. The fourth category of maintenance data may relate to an entire lifetime of each vehicle i.e. that vehicle A required ten workshop sessions during its lifetime, or may relate to predetermined period of time such as a proceeding number of years e.g. 5, 2 or 1 years. The fifth category of maintenance data, ‘Age’, is indicative of an age of the vehicle. In some embodiments, the maintenance data may relate to a period of time since a warranty covering the vehicle began. The age category of maintenance data may be in predetermined units such as a number of days. For example, the age category maintenance data in Table 1 indicates that vehicle A is 270 days old, whereas vehicle C is 510 days old. Vehicle Roadside Claims Time Workshop Age A 2 6 35 10 270 B 0 1 385 2 500 C 1 0 400 1 510 D 0 0 450 1 480 Table 1 Block 420 of the method 400 comprises determining a ranking value for at least some of the plurality of vehicles for at least some of the plurality of categories of maintenance data. In some embodiments, a ranking value may be determined for each category of maintenance data and for each vehicle. Advantageously, the ranking value for each category of the maintenance data converts or scales values associated with the respective category maintenance data to within a known maximum range, which may be associated with the number of vehicles to which the maintenance data relates. For example, considering the first category of maintenance data ‘Roadside’ the numeric values associated with the first category may be ranked in block 420 according 7 to their magnitude such that a highest ranking value is given to one or more vehicles having received a greatest number of roadside maintenance operations. In the example of Table 1 vehicle A is associated with the largest number of roadside maintenance operations followed by, in decreasing order, vehicle C and then jointly vehicles B and D having the same number of roadside maintenance operations, namely zero. Thus the ranking associated with the first category maintenance data adopts values ranging from 3 to 1. It will be appreciated that had each vehicle been associated with a respective unique number of roadside maintenance operations then the associated ranking values will adopt values ranging from 4 to 1 i.e. the maximum ranking would have an equal to the number of vehicles associated with the maintenance data. Table 2 provides ranked maintenance data corresponding to the maintenance data of Table 1 for each of the vehicles A-D. Vehicle Roadside Incidents Time Workshop Age A 3 3 4 3 3 B 1 2 3 2 2 C 2 1 2 1 1 D 1 1 1 1 3 Table 2 Block 430 of the method 400 comprises generating weighted maintenance data. Each category of the maintenance data 235 is associated with one of a plurality of respective weight or weighting values. The weight or weighting value associated with each category of the maintenance data is indicative of an importance of the respective category to the scheduling of maintenance operations. Table 3 illustrates example weights for the 5 categories of maintenance data illustrated in Tables 1 and 2 above. Category Weight Roadside 0.25 Incidents 0.25 Time 0.2 Workshop 0.15 Age 0.15 Table 3 The example weights provided in Table 3 indicate that the number of roadside maintenance operations is considered to be relatively more important than the number of workshop sessions by adopting a weighting value of 0.25 compared to 0.2. It will be appreciated that the example weights in Table 3 are just one example, and that other weights and orders of weighting values may be selected in other examples. Block 430 of the method 400 comprises applying the plurality of weights to the maintenance data 235 to generate weighted maintenance data. In some embodiments, the plurality of weights are applied to the ranked maintenance data of Table 2. When applied to the ranked maintenance data, application of the weights generates a weighted ranking value for each of the plurality of categories of maintenance data. In some embodiments, applying the weights to the categories of maintenance data comprises multiplying the maintenance data for each vehicle by the weight value associated with each respective category of the maintenance data. For example, for vehicle A, the associated value ofthe first category of ranked maintenance data 3 is multiplied by the weight 0.25 to generate a weighted ranking value of 0.75. Similarly, for vehicle D the value of the fifth category of maintenance data, “Age”, 3 is multiplied by the associated weight 0.15 to generated a weighted ranking value of 0.45. Example weighted ranking values corresponding to the maintenance data of Tables 1 and 2 weighted according to the weights of Table 3 is provided below in Table 4. Vehicle Roadside Incidents Time Workshop Age A 0.75 0.75 0.8 0.45 0.6 B 0.25 0.5 0.6 0.3 0.3 C 0.5 0.25 0.4 0.15 0.15 D 0.25 0.25 0.2 0.15 0.45 Table 4 Thus, for each vehicle, block 430 generates a set of weighted ranking values. Block 440 of the method 400 comprises determining a maintenance indicator for each vehicle. The maintenance indicator is indicative of a historic maintenance profile for each respective vehicle. In particular, a value ofthe maintenance indicator is indicative of a magnitude or amount of maintenance required for each vehicle. The maintenance indicator is determined in block 440 in dependence on the weighted maintenance data. In some embodiments the maintenance indicator is determined in dependence on the weighted ranking values as illustrated in Table 4. Determining the maintenance indicator in block 440 comprises combining the weighted ranking values for the plurality of maintenance categories for each vehicle. For examples, by determining a sum total ofthe weighed ranking values across all categories of maintenance data for each vehicle. As an example, the maintenance indicator value for vehicle A is determined as 0.75 + 0.75 + 0.8 + 0.45 + 0.6 = 3.35. A respective maintenance indicator is determined for each vehicle in the same way, with example results being provided in Table 5. Vehicle Maintenance Indicator Scaled Maintenance Indicator A 3.35 1.00 B 1.95 0.32 C 1.45 0.07 D 1.3 0.00 Table 5 The method 400 may comprise a block 450 of determining a scaled maintenance indictor. Block 450 comprises scaling each maintenance indicator determined in block 440. The scaling in block 450 is to generate the scaled maintenance indicator as a value between predetermined minimum and maximum values, such as 0 to 1. In other words, block 450 normalises the maintenance indicators determined in block 440. In some embodiments, the scaling performed in block 450 is min-max scaling. The min-max scaling is determined in dependence on a maximum maintenance indicator value (xmax) and a minimum maintenance indicator (xmin) from the maintenance indicator values determined in block 440 for the plurality of vehicles. In the example discussed here, xmax=3.35 for vehicle A and Xmin^ .3 for vehicle D. The scaling may be performed using Equation 1: _ x ^min xscaled — ~ _ ■^max ^min Equation 1 Where x is the maintenance indicator value from Table 5 for which the scaled maintenance indicator value Xscaied is being determined. As an example, for vehicle B, Xscaied is determined as: _ 1.95 - 1.3 _ Xscaled “ 3.35-1.3 “ °'32 Example scaled maintenance indicators for the vehicle A-D are provided in Table 5. Advantageously determining the scaled maintenance indicator allows a predetermined range of maintenance indicators to be determined i.e. between the predetermined minimum and maximum values e.g. 0 and 1. As such, the scaled maintenance indicator value for each vehicle may be categorised in an automated manner as in block 460 described below. In some embodiments, the method 400 comprises a block 460 of categorising each maintenance indicator. In some embodiments, the scaled maintenance indicator associated with each vehicle may be categorised or banded into one of a plurality of categories of bands. Each of the plurality of categories or bands may be defined by first and second, or upper and lower, threshold values. For example, the plurality of categories may comprise four categories, although it will be appreciated that other numbers of categories may be used. The four example categories may be denoted as very high, high, medium and low in some embodiments, with it being appreciated that categories names are merely illustrative. Each category may be associated with the upper and lower threshold values, such as: Very high = 1-0.76, high = 0.75-0.51, medium = 0.5-0.26, low = 0.25-0 wherein a total range ofthe category values is between 1 and 0. Each maintenance mdictor may be categorised according to the set of upper and lower threshold associated with the plurality of categories. In some embodiments, the scaled maintenance indicators may be categorised, which advantageously may prove computationally faster since the total range of category values 1-0 matches a maximum range ofthe scaled maintenance indicators. Categorising the scaled maintenance indicators associated with the vehicles A-D provides categories as illustrated in Table 6. Vehicle Category A Very high B Medium C Low D Low Table 6 It can be seen that the categorisation provides an indication of a troublesome nature of a maintenance history of each vehicle. In block 470 ofthe method 400, one or more maintenance operations are scheduled for the plurality of vehicles. In some embodiments, a request is received fora maintenance operation of at least some ofthe vehicles e.g. for at least some ofthe group of vehicles A-D. As an example, requests to perform maintenance on vehicles A and C may be received in block 470. A scheduling ofthe maintenance operations on the at least some of the plurality of vehicles is determined in dependence on the maintenance indicator associated with each vehicle. In some embodiments, the scheduling is determined in dependence on a value ofthe maintenance indicator, the scaled maintenance indicator or the categorised maintenance indicator associated with each vehicle. A vehicle having a higher maintenance indicator value, or scaled maintenance indicator value, may have a maintenance operation scheduled with a higher priority i.e. performed more quickly than a vehicle associated with a lower maintenance indicator value, or scaled maintenance indicator value. In some embodiments, vehicles within the same category may be given equal priority for scheduling of a maintenance operation e.g. vehicles C and D. Furthermore in some embodiments, users associated with vehicles having higher maintenance indicator values, or scaled maintenance indicator values, may be given preferential treatment or customer care. For example, users of vehicles having high or very high categorised maintenance indicators may be given preferential treatment, such as being proactively contacted or provided with additional benefits in relation to the maintenance history ofthe vehicles with which they are associated. It will be appreciated that various changes and modifications can be made to the present invention without departing from the scope ofthe present application.

Claims

1. A computer-implemented method of scheduling a maintenance operation on a vehicle, the method comprising:obtaining maintenance data relating to a plurality of vehicles, wherein the maintenance data is indicative of historic maintenance operations associated with each of the plurality of vehicles and comprises, for each vehicle, a plurality of categories of maintenance data;generating weighted maintenance data which comprises applying a plurality of weights to the maintenance data, wherein the each of the plurality of weights is associated with a respective one of the plurality of categories of maintenance data;determining a maintenance indicator for each vehicle in dependence on the weighted maintenance data, wherein the maintenance indicator is indicative of a historic maintenance profile forthe respective vehicle; andscheduling maintenance operations for a portion of the plurality of vehicles in dependence on the maintenance indicator associated with each of the portion of the plurality of vehicles.

2. The computer-implemented method of claim 1, further comprising:determining a ranking value for each of the categories of maintenance data associated with each vehicle;wherein the generating the weighted maintenance data comprises applying the each of the plurality of weights to the ranking value associated with the respective one of the plurality of categories of maintenance data to determine a weighted ranking value for each of the plurality of categories of maintenance data.

3. The computer-implemented method of claim 2, wherein the maintenance indicator is determined in dependence on the weighted ranking value for each of the plurality of categories of maintenance data.

4. The computer-implemented method of claim 2 or 3, wherein the determining the maintenance indicator comprises combining the weighted ranking values associated with the plurality of categories of maintenance data for each vehicle.

5. The computer-implemented method of any preceding claim, wherein the scheduling maintenance operations forthe portion of the plurality of vehicles comprises receiving a request fora maintenance operation associated with at least some of the plurality of vehicles and scheduling the maintenance operation for each vehicle proportional to the maintenance indicator.

6. The computer-implemented method of any preceding claim, wherein the scheduling maintenance operations forthe portion of the plurality of vehicles comprises receiving a request fora maintenance operation associated with each ofthe portion of the plurality of vehicles.

7. The computer-implemented method of any preceding claim, comprising determining a scaled maintenance indicator for each vehicle ofthe plurality of vehicles.

128. The computer-implemented method of claim 7, wherein the scaled maintenance indicator is determined in dependence on a value of a maximum and a minimum maintenance indicator value for the plurality of vehicles.

9. The computer-implemented method of claim 7 or 8, wherein the scaled maintenance indicator Xscaied for each vehicle is determined by:^scaled ~ _Xmax %minwhere x is the maintenance indicator value forthe vehicle, Xma* is a maximum maintenance indicator value and Xmin is a minimum maintenance indicator value forthe plurality of vehicles.

10. The computer-implemented method of any preceding claim, wherein the maintenance data is obtained from the one or more vehicles.

11. A computer system for scheduling a maintenance operation on a vehicle, the computer system comprising one or more processors collectively configured to:obtain maintenance data relating to a plurality of vehicles, wherein the maintenance data is indicative of historic maintenance operations associated with each of the plurality of vehicles and comprises, for each vehicle, a plurality of categories of maintenance data;generate weighted maintenance data which comprises applying a plurality of weights to the maintenance data, wherein the each of the plurality of weights is associated with a respective one of the plurality of categories of maintenance data;determine a maintenance indicator for each vehicle in dependence on the weighted maintenance data, wherein the maintenance indicator is indicative of a historic maintenance profile forthe respective vehicle; andschedule maintenance operations for a portion of the plurality of vehicles in dependence on the maintenance indicator associated with each of the portion of the plurality of vehicles.

12. Computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the method according to any of claims 1 to 10.

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