Knowledge management for maintenance, repair and service of manufacturing
Wan, Shan, Gao, James ORCID: 0000-0001-5625-3654, Li, Dongbo and Evans, Richard (2014) Knowledge management for maintenance, repair and service of manufacturing. In: Advances in Manufacturing Technology XXVIII. Proceedings of the 12th International Conference on Manufacturing Research (ICMR2014). Hampshire Press Ltd, Southampton, UK, pp. 65-70. ISBN 978-0-9926958-4-2 ISSN 2053-3373
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Abstract
Manufacturing equipment, such as numerical controlled machines and assembly cranes, requires constant maintenance and service in their operating lifecycle. Equipment maintenance plays an important role in avoiding unexpected failures and ensuring production efficiency. During maintenance operations, much data is generated and stored in databases. It is essential for manufacturing companies to develop a system to integrate equipment condition monitoring, fault prediction and knowledge base to support maintenance decisions. A case study, carried out within a power generator manufacturing organisation, was conducted to understand what the maintenance process is and how maintenance knowledge is currently managed. It was concluded that maintenance process is less efficient, and maintenance records, stored within internal databases, are not consistent, which makes knowledge hard to share, learn from and reuse. This paper proposes a Knowledge Management System for Maintenance, Repair and Service in Manufacturing Systems to support better maintenance decision and improve maintenance efficiency.
Item Type: | Conference Proceedings |
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Title of Proceedings: | Advances in Manufacturing Technology XXVIII. Proceedings of the 12th International Conference on Manufacturing Research (ICMR2014) |
Additional Information: | Advances in Manufacturing Technology XXVIII, 9th -11th September 2014, Southampton (UK) © Southampton Solent University 2014 |
Uncontrolled Keywords: | Maintenance, Knowledge management, Product lifecycle management |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science |
Related URLs: | |
Last Modified: | 08 Nov 2019 12:59 |
URI: | http://gala.gre.ac.uk/id/eprint/12837 |
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