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Identifying rail asset maintenance processes: a human-centric and sensemaking approach

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journal contribution
posted on 2020-06-15, 15:29 authored by Genovefa Kefalidou, David Golightly, Sarah Sharples
Efficient asset maintenance is key for delivering services such as transport. Current rail maintenance processes have been mostly reactive with a recent shift towards exploring proactive modes. The introduction of new ubiquitous technologies and advanced data analytics facilitates the embedding of a ‘predict-and-prevent’ approach to managing assets. Successful, user-centred integration of such technology is still, however, a sparsely understood area. This study reports results from a set of interviews, based on critical decision method, with rail asset maintenance and management experts regarding current procedural aspects of asset management and maintenance. We analyse and present the results from a human-centric sensemaking timeline perspective. We found that within a complex socio-technical environment such as rail transport, asset maintenance processes apply not only just at local levels, but also at broader, strategic levels that involve different stakeholders and necessitate different levels of expertise. This is a particularly interesting aspect within maintenance that has not been discussed as of yet within a process-based and timeline-based models of asset maintenance. We argue that it is important to consider asset maintenance activities within both micro (local)- and macro (broader)-levels to ensure reliability and stability in transport services. We also propose that the traditionally distinct notions of individual, collaborative and artefact-based sensemaking are in fact all in evidence in this sensemaking context, and argue that a more holistic view of sensemaking is therefore appropriate by placing these results within an amended recognition-primed decision-making model.

Funding

Innovate UK-funded project PCIPP: People-Centred Infrastructure for Intelligent, Proactive and Predictive Assets Maintenance with Condition Monitoring project number 101698.

History

Citation

Kefalidou, G., Golightly, D. & Sharples, S. Identifying rail asset maintenance processes: a human-centric and sensemaking approach. Cogn Tech Work 20, 73–92 (2018). https://doi.org/10.1007/s10111-017-0452-0

Author affiliation

Department of Informatics

Version

  • VoR (Version of Record)

Published in

Cognition, Technology & Work

Volume

20

Issue

1

Pagination

73 - 92 (20)

Publisher

SPRINGER LONDON LTD

issn

1435-5558

eissn

1435-5566

Acceptance date

2017-11-30

Copyright date

2018

Available date

2018-01-16

Language

English

Publisher version

https://link.springer.com/article/10.1007/s10111-017-0452-0