Analysis of passenger rolling stock faults and its statistics in Lithuania

Gelumbickas, Gintaras; Vaičiūnas, Gediminas

doi:10.3846/16484142.2011.618190

Use this URL to cite this publication: https://hdl.handle.net/20.500.14911/130582

Analysis of passenger rolling stock faults and its statistics in Lithuania

Details

Publication Type (CRIS)

Straipsnis Web of Science ir Scopus duomenų bazėje / Article in Web of Science and Scopus database (S1)

Publication Type (eLABa)

Straipsnis Web of Science DB / Web of Science DB article (S1)

Author(s)

Author	Affiliation
Gelumbickas, Gintaras	Mobiliųjų mašinų ir geležinkelių transporto katedra / Department of Mobile Machinery and Railway Transport (0746)
Vaičiūnas, Gediminas	Mobiliųjų mašinų ir geležinkelių transporto katedra / Department of Mobile Machinery and Railway Transport (0746)

Title

Analysis of passenger rolling stock faults and its statistics in Lithuania

[en]

Gintaras Gelumbickas, Gediminas Vaičiūnas

Is part of

Transport

Published In

Year	Volume	Issue	Start Page	End Page
2011	26	3	315	319

Publisher

Vilnius : Technika

Publisher (trusted)

Technika

Referenced in Database(s)(DBs)

Index Copernicus

ICONDA

SCOPUS

Science Citation Index Expanded (Web of Science)

VINITI RAN

Compendex

Extent

p. 315-319

URI

URI	Access Rights
https://hdl.handle.net/20.500.14911/130582
https://journals.vgtu.lt/index.php/Transport/article/view/5652	Viso teksto dokumentas (atviroji prieiga) / Full Text Document (Open Access)

DOI

10.3846/16484142.2011.618190

Cited references

Science / Art Area

Technologijos mokslai / Technological sciences (T)

Field of Science / Art

Transporto inžinerija / Transport engineering (T003)

Keywords (en)

Abstract (en)

Performed data analysis aims to determine the number of rolling stock breakdowns and how it depends on rolling stock age, the number of passengers and operations. The mathematical model, stated below, analyses correlation between passenger fleet upgrade intensity and the number of faults. When planning to buy some new rolling stock (3÷6 wagons electric or diesel trains) while using this model, the number of faults can be predicted up to five years.