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Progress in Predictive Asset Maintenance Management / Daniel Rees, Roderick Thomas

International Journal of Condition Monitoring and Diagnostics Engineering Management, Volume: 24, Issue: 3, Pages: 39 - 45

Swansea University Authors: Daniel Rees, Roderick Thomas

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Abstract

Optimised Asset Management in recent years has embraced a rapid diffusion of innovation and disruptive technology, especially with reference to conditionmonitoring and predictive maintenance. The integration of this technology and associated communication technologies are improving operational aspec...

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Published in: International Journal of Condition Monitoring and Diagnostics Engineering Management
ISSN: 1363-7681
Published: COMADEM International ,UK 2021
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa58036
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Abstract: Optimised Asset Management in recent years has embraced a rapid diffusion of innovation and disruptive technology, especially with reference to conditionmonitoring and predictive maintenance. The integration of this technology and associated communication technologies are improving operational aspectsof industry, including predicting condition asset failure. Some assets in the future will be connected to the Internet of Things (IoT), Cloud Computing, BigData including virtual and augmented reality which will be the gateway to enhanced communication including self-diagnosing capabilities driven by expertsystems. Asset connectivity and predictive analytics will discern patterns and algorithms leading to optimised plant production, and enhanced energyefficiency. Machine learning models will indicate future operation on a real-time basis using big data libraries, tabular databases especially with referenceto condition monitoring. This paper reviews the role maintenance has in optimising asset operation.
Keywords: Asset Management, Disruptive Technology, Condition Monitoring, Infrared Thermography, Reliability Based Maintenance.
College: School of Management
Issue: 3
Start Page: 39
End Page: 45