A Framework for Railway Maintenance Function Allocation

Fan Yang, Edward Stewart, Clive Roberts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

the demands for reliable, well-maintained rolling stock systems have been increasing. Automation has become the smarter solution in various railway applications to enhance the capacity, reliability, and efficiency of the railway system. Automation systems such as visual inspection and industrial robot arms play a critical role in heavy manipulation and dangerous operations. Maintenance efficiency and overall safety would be greatly improved. There is a research gap for systematic approaches to making decisions on which certain maintenance tasks are suitable for automation. This paper presents a generic railway maintenance function allocation framework, which helps decision making in allocating maintenance tasks at the early stages of introducing automation solutions into modern rolling stock maintenance depot. Depot working environments are analysed and an example of robotic wheelset inspection is presented.

Original languageEnglish
Title of host publication2018 International Conference on Intelligent Rail Transportation, ICIRT 2018
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781538675281
DOIs
Publication statusPublished - 2 Jul 2018
Event2018 International Conference on Intelligent Rail Transportation, ICIRT 2018 - Singapore, Singapore
Duration: 12 Dec 201814 Dec 2018

Publication series

Name2018 International Conference on Intelligent Rail Transportation, ICIRT 2018

Conference

Conference2018 International Conference on Intelligent Rail Transportation, ICIRT 2018
Country/TerritorySingapore
CitySingapore
Period12/12/1814/12/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • automation
  • function allocation
  • railway maintenance

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Management Science and Operations Research
  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Transportation

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