Managing rail infrastructure for a digital future: Future-proofing of asset information

Peter E.D. Love, Jingyang Zhou, Jane Matthews, Matthew Lavender and Troy Morse

Transportation Research Part A: Policy and Practice, 2018, vol. 110, issue C, 161-176

Abstract: Rail infrastructure that operates at its optimum will be economical and sustainable and thus positively contribute to the productivity and competitiveness of an economy. The health of rail infrastructure, however, needs to be monitored, measured and maintained, which falls within the remit of asset managers who are often charged with balancing costs, opportunities and risks against the desired performance of the assets and their respective systems at varying levels. Having appropriate and reliable information about an asset is pivotal for enabling asset management to support decision-making, planning and execution of activities and tasks of assets, particularly during operations and maintenance. But, having access to the right information at the right time, has been and remains a pervasive problem, hinders an asset owner’s ability to ensure their rail infrastructure performance is being optimized. A new approach to facilitate the acquisition and integration of information to support digital asset management (DAM) for rail infrastructure is presented. The research uses a case study to empirically assess the quality of ‘as-built’ documentation for electrical systems of Bayswater railway station that forms an integral part of the Forrestfield Airport Linkage project, in Perth Western Australia. Errors, omissions and information redundancy contained within the existing ‘as-built’ documentation is quantified. Then, a case for the adoption of a Systems Information Model is put forward as the rail industry moves toward a digital future and seeks to future-proof their assets and networks.

Keywords: Asset management; Digitization; System information model; Rail; Future-proof (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.tra.2018.02.014

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