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Intelligent decision support for maintenance: A new role for audit trails

Turner, C., Emmanouilidis, C., Tomiyama, T., Tiwari, A. and Roy, R. ORCID: 0000-0001-5491-7437 (2018). Intelligent decision support for maintenance: A new role for audit trails. In: Liyanage, J., Amadi-Echendu, J. and Matthew, J. (Eds.), Engineering Assets and Public Infrastructures in the Age of Digitalization: Proceedings of the 13th World Congress on Engineering Asset Management (Lecture Notes in Mechanical Engineering). . Cham, Switzerland: Springer. ISBN 978-3-030-48020-2

Abstract

The changing nature of manufacturing, in recent years, is evident in in-dustries willingness to adopt network connected intelligent machines in their factory development plans. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by Internet of Things cre-ate new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of comprehensive framework for its processing, analysis and use should be an important goal in ad-dressing the new data analytics challenges for maintenance created by internet con-nected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data and the provision of a comprehensive framework for its processing analysis and use. The concept of ‘Human in the loop’ is also reinforced with the use of audit trails, allowing streamlined access to decision making and providing the ability to mine decisions.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: This is a post-peer-review, pre-copyedit version of a conference paper to be published in Engineering Assets and Public Infrastructures in the Age of Digitalization: Proceedings of the 13th World Congress on Engineering Asset Management (Lecture Notes in Mechanical Engineering). The final authenticated version will be available online at: http://dx.doi.org/10.1007/978-3-030-48021-9
Subjects: H Social Sciences > HD Industries. Land use. Labor
T Technology > TJ Mechanical engineering and machinery
Departments: School of Mathematics, Computer Science & Engineering
Date Deposited: 06 May 2020 09:32
URI: https://openaccess.city.ac.uk/id/eprint/24154
[img] Text - Accepted Version
This document is not freely accessible until 21 August 2022 due to copyright restrictions.

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