EHF2015ShortPaper_final_v.pdf (57.35 kB)
Implementation of remote condition monitoring system for predictive maintenance: an organisational challenge
conference contribution
posted on 2015-05-19, 15:34 authored by Luminita Ciocoiu, Ella-Mae HubbardElla-Mae Hubbard, Carys SiemieniuchThe “Health and Prognostic Assessment of Railway Assets for Predictive Maintenance” project is developing a Remote Condition Monitoring (RCM) system to manage asset degradation to enable predictive maintenance. Despite the benefits of the RCM systems, many of the programmes that seek to introduce them fail. Previous research shows that, beside technological challenges, there are organisational factors that contribute to the success of these programmes; the paper presents a three step approach taken to meet these challenges and some initial findings of the research.
Funding
The authors would like to thank London Underground and other partners in the project: Telent, Humaware and Nottingham University, as well as the project funding bodies Innovate UK and the RSSB.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Published in
CIEHF Annual ConferenceCitation
CIOCOIU, L., HUBBARD, E.-M. and SIEMIENIUCH, C.E., 2015. Implementation of remote condition monitoring system for predictive maintenance: an organisational challenge. IN: Sharples, S., Shorrock, S. and Waterson, P. (eds). Contemporary Ergonomics and Human Factors 2015: Proceedings of the International Conference on Ergonomics & Human Factors, 13th-16th April, Staverton Park, Daventry. Taylor and Francis, pp. 449-453.Publisher
© Taylor and FrancisVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2015Notes
This is a conference paper and is available here with the kind permission of Taylor and Francis.ISBN
9781138028036Language
- en