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Operation Classification of Heavy Vehicles

Johansson, Fredrik (2004) MIO920
Production Management
Abstract
Within Scania there is a need to classify vehicles depending on the prevailing
operation conditions. Different vehicles are exposed to various loads and this will
influence the need for R&M greatly. The systems that are presently used for
classification purposes are subjective and the owner’s negotiation skills can affect
the outcome. Simultaneously there is a lack of knowledge concerning the influence
specific factors have on vehicle wear.
The goal with the project was to develop a method which could be used for
classification, based on information that is possible to measure. Information which
can be extracted from the engine control unit, which all vehicles are equipped with,
served as a starting point. This type of data is... (More)
Within Scania there is a need to classify vehicles depending on the prevailing
operation conditions. Different vehicles are exposed to various loads and this will
influence the need for R&M greatly. The systems that are presently used for
classification purposes are subjective and the owner’s negotiation skills can affect
the outcome. Simultaneously there is a lack of knowledge concerning the influence
specific factors have on vehicle wear.
The goal with the project was to develop a method which could be used for
classification, based on information that is possible to measure. Information which
can be extracted from the engine control unit, which all vehicles are equipped with,
served as a starting point. This type of data is commonly called operation data.
Since a new classification, in order to be meaningful, must be based on factors
which influence the need for R&M activity it became an important part of the
project to identify such factors.
In order to investigate the connection between operation data and wear several
different types of information were evaluated and used. In the initial analysis
operation data was compared with warranty information but no link could be
discovered. The conclusion was that warranty information is unsuitable for the
evaluation of operation data. Warranty information mainly reflects problems which
arise due to quality problems and not due to wear.
Problems caused by wear can be expected to develop over time. Hence, it is
important to have access to R&M statistics which cover a rather longer period of
time. The only source of information available within Scania which contain
comprehensive R&M information is RAMAS, used by the market organisation to
evaluate R&M contracts. Unfortunately it is in most cases not possible to access
operation data from contract vehicles. A collection of such data has been initiated
but an evaluation of the material was not possible to fit within the timeframe of the
project. However, an analysis of the available material showed that there most
likely is a connection between wear on certain parts of the drive train and fuel
consumption.
The collection of operation information requires a coordinated strategy.
Investigating why damage is initiated and how it propagates is important to identify
crucial operation factors. A thorough analysis of operation data needs to be done
and the connection between wear and fuel consumption must be verified. A
classification system based on the influence of operation conditions will not be
static but develop over time. (Less)
Please use this url to cite or link to this publication:
author
Johansson, Fredrik
supervisor
organization
course
MIO920
year
type
M1 - University Diploma
subject
other publication id
04/5206
language
English
id
2007141
date added to LUP
2011-06-30 11:36:31
date last changed
2011-06-30 11:36:31
@misc{2007141,
  abstract     = {Within Scania there is a need to classify vehicles depending on the prevailing
operation conditions. Different vehicles are exposed to various loads and this will
influence the need for R&M greatly. The systems that are presently used for
classification purposes are subjective and the owner’s negotiation skills can affect
the outcome. Simultaneously there is a lack of knowledge concerning the influence
specific factors have on vehicle wear.
The goal with the project was to develop a method which could be used for
classification, based on information that is possible to measure. Information which
can be extracted from the engine control unit, which all vehicles are equipped with,
served as a starting point. This type of data is commonly called operation data.
Since a new classification, in order to be meaningful, must be based on factors
which influence the need for R&M activity it became an important part of the
project to identify such factors.
In order to investigate the connection between operation data and wear several
different types of information were evaluated and used. In the initial analysis
operation data was compared with warranty information but no link could be
discovered. The conclusion was that warranty information is unsuitable for the
evaluation of operation data. Warranty information mainly reflects problems which
arise due to quality problems and not due to wear.
Problems caused by wear can be expected to develop over time. Hence, it is
important to have access to R&M statistics which cover a rather longer period of
time. The only source of information available within Scania which contain
comprehensive R&M information is RAMAS, used by the market organisation to
evaluate R&M contracts. Unfortunately it is in most cases not possible to access
operation data from contract vehicles. A collection of such data has been initiated
but an evaluation of the material was not possible to fit within the timeframe of the
project. However, an analysis of the available material showed that there most
likely is a connection between wear on certain parts of the drive train and fuel
consumption.
The collection of operation information requires a coordinated strategy.
Investigating why damage is initiated and how it propagates is important to identify
crucial operation factors. A thorough analysis of operation data needs to be done
and the connection between wear and fuel consumption must be verified. A
classification system based on the influence of operation conditions will not be
static but develop over time.},
  author       = {Johansson, Fredrik},
  language     = {eng},
  note         = {Student Paper},
  title        = {Operation Classification of Heavy Vehicles},
  year         = {2004},
}