Essop, Ismael ORCID: 0000-0002-5583-0306 and Gao, Xiaoyu ORCID: 0000-0001-5625-3654 (2015) Opportunities and challenges in using Big Data for product maintenance in the power generation industry. In: Proceedings of the International Conference on Manufacturing Research. ICMR 2015, 13th International Conference on Manufacturing Research. ISBN 1857901878

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Abstract

In an age of globalised manufacturing, Big Data can be harnessed to improve decision making in the maintenance of products. The manufacturing sector is plagued with outdated legacy systems and data. Some manufacturers are using predictive-maintenance and condition-monitoring analytics on their assets to keep operations “up and running” by identifying problems before they occur. However, Big Data is a virtually untapped asset for the Power Generation Industry. A lot of data related to product manufacturing and services in this sector has been collected for years, but have not been analysed and used.This paper reports the results of an industrial investigation, proposing a roadmap to make use of sensors to assess the maintenance statuses of equipment, and a Big Data architecture for the
implementation of a predictive analytics application.

Item Type:	Conference Proceedings
Title of Proceedings:	Proceedings of the International Conference on Manufacturing Research
Additional Information:	Conference dates: 08/09/2015 - 10/09/2015 Location: University of Bath (UK)
Uncontrolled Keywords:	Big Data; Product maintenance; Predictive analytics
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > Centre for Innovative & Smart Infrastructure
Related URLs:	Organisation
Last Modified:	28 Feb 2021 19:55
URI:	http://gala.gre.ac.uk/id/eprint/13877

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