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P. Jain and L. Varghese
failure. Jbili et al. [2] also carried out a similar study to identify the reliability of
heavy vehicles and suggested that the vehicles travelling over long distances must
undergo frequent maintenance. It is always necessary to conduct studies pertaining
to assistance to vehicle maintenance perform and incorporate new technologies to
avoid car system failure [3, 4]. In a similar context, the study of Dobromirov et al. [5]
reviewed and examined the systematization of different automobile sector. Authors
concluded and suggested to enhance the use of new technologies associated with
of latest devices equipped for regular maintenance. Another factor which is also
essential to avoid sudden system failure is the vehicle to vehicle communication
[6]. Minimal literature was reported to examine the reliability of the automobile
subsystem of cars. The present study aims to analyse the reliability of car subsystem
Wagon-R. The reliability of different systems was calculated on the basis of distance
travelled by various cars.
2 Methodology
Data of car model Maruti Suzuki Wagon-R were collected from a private service
station and represented in Table 1. The categorization of data is done as per the travelled distance by the respective cars such as up to 25,000 km, between 25,001–50,000
and 50,001–75,000 km. In addition to this, the collected details were analysed, respectively, car systems like the clutch, front brake, suspension and rear brake system.
The collected data were analysed using the Weibull distribution method (WDM), as
the WDM results reasonably more accurate and also forecast with extremely small
sample size.
The following procedure is adopted to calculate the reliability of Wagon-R,
1. Plot a bar graph for each system of collected data and take abscissa as the number
of cars taken and ordinate as a distance before failure.
2. Then, we convert this distance before failure to time before failure by assuming
speed of vehicles as 60 km/h.
3. Find total average distance between failure and total average time to failure by
simply taking average of distance between failure by number of car failed, and
also, arrange in ascending order.
4. Find median rank using following equation
M.R.% =
i − 3
N + 4
× 100
(1)
where i = number of sample arranged in ascending order as failure, N = number
of sample taken.
P. Jain and L. Varghese
failure. Jbili et al. [2] also carried out a similar study to identify the reliability of
heavy vehicles and suggested that the vehicles travelling over long distances must
undergo frequent maintenance. It is always necessary to conduct studies pertaining
to assistance to vehicle maintenance perform and incorporate new technologies to
avoid car system failure [3, 4]. In a similar context, the study of Dobromirov et al. [5]
reviewed and examined the systematization of different automobile sector. Authors
concluded and suggested to enhance the use of new technologies associated with
of latest devices equipped for regular maintenance. Another factor which is also
essential to avoid sudden system failure is the vehicle to vehicle communication
[6]. Minimal literature was reported to examine the reliability of the automobile
subsystem of cars. The present study aims to analyse the reliability of car subsystem
Wagon-R. The reliability of different systems was calculated on the basis of distance
travelled by various cars.
2 Methodology
Data of car model Maruti Suzuki Wagon-R were collected from a private service
station and represented in Table 1. The categorization of data is done as per the travelled distance by the respective cars such as up to 25,000 km, between 25,001–50,000
and 50,001–75,000 km. In addition to this, the collected details were analysed, respectively, car systems like the clutch, front brake, suspension and rear brake system.
The collected data were analysed using the Weibull distribution method (WDM), as
the WDM results reasonably more accurate and also forecast with extremely small
sample size.
The following procedure is adopted to calculate the reliability of Wagon-R,
1. Plot a bar graph for each system of collected data and take abscissa as the number
of cars taken and ordinate as a distance before failure.
2. Then, we convert this distance before failure to time before failure by assuming
speed of vehicles as 60 km/h.
3. Find total average distance between failure and total average time to failure by
simply taking average of distance between failure by number of car failed, and
also, arrange in ascending order.
4. Find median rank using following equation
M.R.% =
i − 3
N + 4
× 100
(1)
where i = number of sample arranged in ascending order as failure, N = number
of sample taken.