Volltext-Downloads (blau) und Frontdoor-Views (grau)
The search result changed since you submitted your search request. Documents might be displayed in a different sort order.
  • search hit 24 of 40
Back to Result List

Predictive Analytics in Utility Vehicle Maintenance

  • In public transportation, the motor pool often consists of various different vehicles bought over a duration of many years. Sometimes, they even differ within one batch bought at the same time. This poses a considerable challenge in the storage and allocation of spare parts, especially in the event of damage to a vehicle. Correctly assigning these parts before the vehicle reaches the workshopIn public transportation, the motor pool often consists of various different vehicles bought over a duration of many years. Sometimes, they even differ within one batch bought at the same time. This poses a considerable challenge in the storage and allocation of spare parts, especially in the event of damage to a vehicle. Correctly assigning these parts before the vehicle reaches the workshop could significantly reduce both the downtime and, therefore, the actual costs for companies. In order to achieve this, the current software uses a simple probability calculation. To improve the performance, the data of specific companies was analysed, preprocessed and used with several modelling techniques to classify and, therefore, predict the spare parts to be used in the event of a faulty vehicle. We summarize our experience running through the steps of the Cross Industry Standard Process for Data Mining and compare the performance to the previously used probability. Gradient Boosting Trees turned out to be the best modeling technique for this special case.show moreshow less

Export metadata

Additional Services

Search Google Scholar

Statistics

frontdoor_oas
Metadaten
Document Type:Conference Proceeding
Conference Type:Konferenzartikel
Zitierlink: https://opus.hs-offenburg.de/3109
Bibliografische Angaben
Title (English):Predictive Analytics in Utility Vehicle Maintenance
Conference:International Conference on Data Analytics (7. : 18.-22. November 2018 : Athens, Greece)
Author:Stephan TrahaschStaff MemberORCiDGND, Jürgen PrinzbachStaff MemberGND
Year of Publication:2018
First Page:97
Last Page:102
Parent Title (English):DATA ANALYTICS 2018 : The Seventh International Conference on Data Analytics
ISBN:978-1-61208-681-1
ISSN:2308-4464
URL:https://www.thinkmind.org/index.php?view=article&articleid=data_analytics_2018_7_10_60055
Language:English
Inhaltliche Informationen
Institutes:Fakultät Elektrotechnik und Informationstechnik (E+I) (bis 03/2019)
Institutes:Bibliografie
Formale Angaben
Open Access: Open Access 
Licence (German):License LogoUrheberrechtlich geschützt