An intelligent framework and prototype for autonomous maintenance planning in the rail industry
dc.contributor.author | Turner, Christopher J. | |
dc.contributor.author | Tiwari, Ashutosh | |
dc.contributor.author | Starr, Andrew G. | |
dc.contributor.author | Durazo-Cardenas, Isidro | |
dc.contributor.author | Blacktop, K | |
dc.date.accessioned | 2015-12-21T16:26:40Z | |
dc.date.available | 2015-12-21T16:26:40Z | |
dc.date.issued | 2015-05 | |
dc.description.abstract | This paper details the development of the AUTONOM project, a project that aims to provide an enterprise system tailored to the planning needs of the rail industry. AUTONOM extends research in novel sensing, scheduling, and decision-making strategies customised for the automated planning of maintenance activities within the rail industry. This paper sets out a framework and software prototype and details the current progress of the project. In the continuation of the AUTONOM project it is anticipated that the combination of techniques brought together in this work will be capable of addressing a wider range of problem types, offered by Network rail and organisations in different industries. | en_UK |
dc.identifier.citation | Turner CJ, Tiwari A, Starr A, Durazo-Cardenas I & Blacktop K (2015) An intelligent framework and prototype for autonomous maintenance planning in the rail industry. Proceedings of the 1st International Conference on Vehicle Technology and Intelligent Transport Systems, (VEHITS 2015), 20 -22 May 2015, Lisbon, Portugal. | en_UK |
dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/9616 | |
dc.language.iso | en | en_UK |
dc.publisher | SciTePress | en_UK |
dc.subject | Rail industry | en_UK |
dc.subject | Computational intelligence | en_UK |
dc.subject | Data mining | en_UK |
dc.subject | Data fision | en_UK |
dc.subject | Autonomous operation | en_UK |
dc.subject | Planning | en_UK |
dc.title | An intelligent framework and prototype for autonomous maintenance planning in the rail industry | en_UK |
dc.type | Conference paper | en_UK |
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