Abstract
Earthmoving equipment has a determinant role in the successful realisation of most civil engineering projects. However, it may suffer significant downtime due to the continuous and intense use in harsh working conditions. This downtime may be associated with certain deterioration parameters, which if known, would allow more accurate estimations to be made. For this purpose, the data sets from two large Greek construction companies containing the characteristics of 126 earthmoving trucks (capacity, age, kilometres travelled to date, maintenance class and condition level) have been analysed using discriminant analysis. The analysis allows for the assessment of the connection of each characteristic with the condition level of the sample trucks and also leads to rules that can be used for the prediction of the condition level of other trucks.
| Original language | English |
|---|---|
| Pages (from-to) | 397-413 |
| Number of pages | 17 |
| Journal | International Journal of Project Organisation and Management |
| Volume | 4 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2012 |
| Externally published | Yes |
Fingerprint
Keywords
- classification
- condition prediction
- data mining
- deterioration
- discriminant analysis
- downtime
- earthmoving trucks
- equipment
- failures
- Greece
- maintenance
- project management
ASJC Scopus subject areas
- Strategy and Management
Cite this
Investigation of earthmoving trucks deterioration using discriminant analysis. / Marinelli, Marina; Lambropoulos, Sergios; Pantouvakis, John Paris.
In: International Journal of Project Organisation and Management, Vol. 4, No. 4, 2012, p. 397-413.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Investigation of earthmoving trucks deterioration using discriminant analysis
AU - Marinelli, Marina
AU - Lambropoulos, Sergios
AU - Pantouvakis, John Paris
PY - 2012
Y1 - 2012
N2 - Earthmoving equipment has a determinant role in the successful realisation of most civil engineering projects. However, it may suffer significant downtime due to the continuous and intense use in harsh working conditions. This downtime may be associated with certain deterioration parameters, which if known, would allow more accurate estimations to be made. For this purpose, the data sets from two large Greek construction companies containing the characteristics of 126 earthmoving trucks (capacity, age, kilometres travelled to date, maintenance class and condition level) have been analysed using discriminant analysis. The analysis allows for the assessment of the connection of each characteristic with the condition level of the sample trucks and also leads to rules that can be used for the prediction of the condition level of other trucks.
AB - Earthmoving equipment has a determinant role in the successful realisation of most civil engineering projects. However, it may suffer significant downtime due to the continuous and intense use in harsh working conditions. This downtime may be associated with certain deterioration parameters, which if known, would allow more accurate estimations to be made. For this purpose, the data sets from two large Greek construction companies containing the characteristics of 126 earthmoving trucks (capacity, age, kilometres travelled to date, maintenance class and condition level) have been analysed using discriminant analysis. The analysis allows for the assessment of the connection of each characteristic with the condition level of the sample trucks and also leads to rules that can be used for the prediction of the condition level of other trucks.
KW - classification
KW - condition prediction
KW - data mining
KW - deterioration
KW - discriminant analysis
KW - downtime
KW - earthmoving trucks
KW - equipment
KW - failures
KW - Greece
KW - maintenance
KW - project management
UR - http://www.scopus.com/inward/record.url?scp=84898864427&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84898864427&partnerID=8YFLogxK
U2 - 10.1504/IJPOM.2012.050332
DO - 10.1504/IJPOM.2012.050332
M3 - Article
VL - 4
SP - 397
EP - 413
JO - International Journal of Project Organisation and Management
JF - International Journal of Project Organisation and Management
SN - 1740-2891
IS - 4
ER -